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Archive for the ‘Statistical Methods for Research Evaluation’ Category

Diagnostics and Biomarkers: Novel Genomics Industry Trends vs Present Market Conditions and Historical Scientific Leaders Memoirs

Larry H Bernstein, MD, FCAP, Author and Curator

This article has two parts:

  • Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

and

  • Part 2: Historical Scientific Leaders Memoirs

 

Part 1: Novel Genomics Industry Trends in Diagnostics and Biomarkers vs Present Market Transient Conditions

 

Based on “Forging a path from companion diagnostics to holistic decision support”, L.E.K.

Executive Insights, 2013;14(12). http://www.LEK.com

Companion diagnostics and their companion therapies is defined here as a method enabling

  • LIKELY responders to therapies that are specific for patients with ma specific molecular profile.

The result of this statement is that the diagnostics permitted to specific patient types gives access to

  • novel therapies that may otherwise not be approve or reimbursed in other, perhaps “similar” patients
  • who lack a matching identification of the key identifier(s) needed to permit that therapy,
  • thus, entailing a poor expected response.

The concept is new because:

(1) The diagnoses may be closely related by classical criteria, but at the same time they are
not alike with respect to efficacy of treatment with a standard therapy.
(2) The companion diagnostics is restricted to dealing with a targeted drug-specific question
without regard to other clinical issues.
(3) The efficacy issue it clarifies is reliant on a deep molecular/metabolic insight that is not available, except through
emergent genomic/proteomic analysis that has become available and which has rapidly declining cost to obtain.

The limitation example given is HER2 testing for use of Herceptin in therapy for non-candidates (HER2 negative patients).
The problem is that the current format is a “one test/one drug” match, but decision support  may require a combination of

  • validated biomakers obtained on a small biopsy sample (technically manageable) with confusing results.

While HER2 negative patients are more likely to be pre-menopausal with a more aggressive tumor than postmenopausal,

  • the HER2 negative designation does not preclude treatment with Herceptin.

So the Herceptin would be given in combination, but with what other drug in a non-candidate?

The point that L.E.K. makes is that providing highly validated biomarkers linked to approved therapies, it is necessary to pursue more holistic decision support tests that interrogate multiple biomarkers (panels of companion diagnostic markers) and discovery of signatures for treatments that are also used with a broad range of information, such as,

  • traditional tests,
  • imaging,
  • clinical trials,
  • outcomes data,
  • EMR data,
  • reimbursement and coverage data.

A comprehensive solution of this nature appears to be a distance from realization.  However, is this the direction that will lead to tomorrows treatment decision support approaches?

 Surveying the Decision Support Testing Landscape

As a starting point, L.E.K. characterized the landscape of available tests in the U.S. that inform treatment decisions compiled from ~50 leading diagnostics companies operating in the U.S. between 2004-2011. L.E.K. identified more than 200 decision support tests that were classified by test purpose, and more specifically,  whether tests inform treatment decisions for a single drug/class (e.g., companion diagnostics) vs. more holistic treatment decisions across multiple drugs/classes (i.e., multiagent response tests).

 Treatment Decision Support Tests

Companion Diagnostics
Single drug/class
Predict response/safety or guide dosing of a single drug or class

HercepTest   Dako
Determines HER2 protein overexpression for Herceptin treatment selection

Multiple drugs/classes

Vysis ALK Break
Apart FISH
Abbott Labs Predicts the NSCLC patient response to Xalkori

Other Decision Support
Provide prognostic and predictive information on the benefit of treatment

Oncotype Dx    Genomic Health, Inc.
Predicts both recurrence of breast cancer and potential patient benefit to chemotherapy regimens

PML-RARα     Clarient, Inc.
Predicts response to all-trans retinoic acid (ATRA) and other chemotherapy agents

TRUGENE    Siemens
Measures resistence to multiple  HIV-1 anti-retroviral agents

Multi-agent Response

Inform targeted therapy class selection by interrogating a panel of biomarkers
Target Now  Caris Life Sciences
Examines tumor’s molecular profile to tailor treatment options

ResponseDX: Lung    Response Genetics, Inc.
Examines multiple biomarkers to guide therapeutic treatment decisions for NSCLC patients

Source: L.E.K. Analysis

Includes IVD and LDT tests from

  1. top-15 IVD test suppliers,
  2. top-four large reference labs,
  3. top-five AP labs, and
  4. top-20 specialty reference labs.

For descriptive purposes only, may not map to exact regulatory labeling

Most tests are companion diagnostics and other decision support tests that provide guidance on

  • single drug/class therapy decisions.

However, holistic decision support tests (e.g., multi-agent response) are growing the fastest at 56% CAGR.
The emergence of multi-agent response tests suggests diagnostics companies are already seeing the need to aggregate individual tests (e.g., companion diagnostics) into panels of appropriate markers addressing a given clinical decision need. L.E.K. believes this trend is likely to continue as

  • increasing numbers of  biomarkers become validated for diseases and multiplexing tools
  • enabling the aggregation of multiple biomarker interrogations into a single test

to become deployed in the clinic.

Personalized Medicine Partnerships

L.E.K. also completed an assessment of publicly available personalized medicine partnership activity from 2009-2011 for ~150 leading organizations operating in the U.S. to look at broader decision support trends and emergence of more holistic solutions beyond diagnostic tests.

Survey of partnerships deals was conducted for

  • top-10 academic medical centers research institutions,
  • top-25 biopharma,
  • top-four healthcare IT companies,
  • top-three healthcare imaging companies,
  • top-20 IVD manufacturers,
  • top-20 laboratories,
  • top-10 payers/PBMs,
  • top-15 personalized healthcare companies,
  • top-10 regulatory/guideline entities, and
  • top-20 tools vendors for the period of 01/01/2009 – 12/31/2011.
    Source: Company websites, GenomeWeb, L.E.K. analysis

Across the sample we identified 189 publicly announced partnerships of which ~65% focused on more traditional areas (biomarker discovery, companion diagnostics and targeted therapies). However, a significant portion (~30%) included elements geared towards creating more holistic decision support models.

Partnerships categorized as holistic decision support by L.E.K. were focused on

  • mining large patient datasets (e.g., from payers or providers),
  • molecular profiling (e.g., deploying next-generation sequencing),
  • creating information technology (IT) infrastructure needed to enable holistic decision support models and
  • integrating various datasets to create richer decision support solutions.

Interestingly, holistic decision support partnerships often included stakeholders outside of biopharma and diagnostics such as

  • research tools,
  • payers/PBMs,
  • healthcare IT companies as well as
  • emerging personalized healthcare (PHC) companies (e.g., Knome, Foundation Medicine and 23andMe).

This finding suggests that these new stakeholders will be increasingly important in influencing care decisions going forward.

Holistic Treatment Decision Support

Holistic Decision   Support Focus

Technology Provider Partners
Stakeholder Deploying the Solution

Holistic Decision
Support Activities
Molecular Profiling

Life Technologies

TGEN/US
Oncology

Sequencing of triple-negative breast  cancer patients to identify potential treatment strategies

Foundation Medicine

Novartis

Deployment of cancer genomics analysis platform to support Novartis clinical research efforts
Predictive genomics

Clarient, Inc.
(GE Healthcare)

Acorn
Research

Biomarker profiling of patients within Acorn’s network of providers to support clinical research efforts

GenomeQuest

Beth Israel Deaconess
Medical Center

Whole genome analysis and to guide patient management
Outcomes Data Mining

AstraZeneca

WellPoint

Evaluate comparative effectiveness of selected marketed therapies

23andMe

NIH

Leverage information linking drug response and CYP2C9/CYP2C19 variation

Pfizer

Medco

Leverage patient genotype, phenotype and outcome for treatment decisions and target therapeutics
Healthcare IT Infrastructure

IBM

WellPoint

Deploy IBM’s Watson-based solution to evidence-based healthcare decision-making support

Oracle

Moffitt Cancer Center

Deploy Oracle’s informatics platform to store and manage patient medical information
Data Integration

Siemens Diagnostics

Susquehanna Health

Integration of imaging and laboratory diagnostics

Cernostics

Geisinger
Health

Integration of advanced tissue diagnostics, digital pathology, annotated biorepository and EMR
to create solutions
next-generation treatment decision support solutions

CardioDx

GE Healthcare

Integration of genomics with imaging data in CVD

Implications

L.E.K. believes the likely debate won’t center on which models and companies will prevail. It appears that the industry is now moving along the continuum to a truly holistic capability.
The mainstay of personalized medicine today will become integrated and enhanced by other data.

The companies that succeed will be able to capture vast amounts of information

  • and synthesize it for personalized care.

Holistic models will be powered by increasingly larger datasets and sophisticated decision-making algorithms.
This will require the participation of an increasingly broad range of participants to provide the

  • science, technologies, infrastructure and tools necessary for deployment.

There are a number of questions posed by this study, but only some are of interest to this discussion:

Group A.    Pharmaceuticals and Devices

  •  How will holistic decision support impact the landscape ?
    (e.g., treatment /testing algorithms, decision making, clinical trials)

Group B.     Diagnostics and   Decision Support

  •   What components will be required to build out holistic solutions?

– Testing technologies

– Information (e.g., associations, outcomes, trial databases, records)

– IT infrastructure for data integration and management, simulation and reporting

  •  How can various components be brought together to build seamless holistic  decision support solutions?

Group C.      Providers and Payers

  •  In which areas should models be deployed over time?
  • Where are clinical and economic arguments  most compelling?

Part 2: Historical Scientific Leaders Memoirs – Realtime Clinical Expert Support

Gil David and Larry Bernstein have developed, in consultation with Prof. Ronald Coifman,
in the Yale University Applied Mathematics Program,

A software system that is the equivalent of an intelligent Electronic Health Records Dashboard that

  • provides empirical medical reference and
  • suggests quantitative diagnostics options.

The current design of the Electronic Medical Record (EMR) is a linear presentation of portions of the record

  • by services
  • by diagnostic method, and
  • by date, to cite examples.

This allows perusal through a graphical user interface (GUI) that partitions the information or necessary reports

  • in a workstation entered by keying to icons.

This requires that the medical practitioner finds the

  • history,
  • medications,
  • laboratory reports,
  • cardiac imaging and
  • EKGs, and
  • radiology in different workspaces.

The introduction of a DASHBOARD has allowed a presentation of

  • drug reactions
  • allergies
  • primary and secondary diagnoses, and
  • critical information

about any patient the care giver needing access to the record.

The advantage of this innovation is obvious.  The startup problem is what information is presented and

  • how it is displayed, which is a source of variability and a key to its success.

We are proposing an innovation that supercedes the main design elements of a DASHBOARD and utilizes

  • the conjoined syndromic features of the disparate data elements.

So the important determinant of the success of this endeavor is that

  • it facilitates both the workflow and the decision-making process with a reduction of medical error.

Continuing work is in progress in extending the capabilities with model datasets, and sufficient data because

  • the extraction of data from disparate sources will, in the long run, further improve this process.

For instance, the finding of  both ST depression on EKG coincident with an elevated cardiac biomarker (troponin), particularly in the absence of substantially reduced renal function. The conversion of hematology based data into useful clinical information requires the establishment of problem-solving constructs based on the measured data.

The most commonly ordered test used for managing patients worldwide is the hemogram that often incorporates

  • the review of a peripheral smear.

While the hemogram has undergone progressive modification of the measured features over time the subsequent expansion of the panel of tests has provided a window into the cellular changes in the

  • production
  • release
  • or suppression

of the formed elements from the blood-forming organ into the circulation. In the hemogram one can view

  • data reflecting the characteristics of a broad spectrum of medical conditions.

Progressive modification of the measured features of the hemogram has delineated characteristics expressed as measurements of

  • size
  • density, and
  • concentration,

resulting in many characteristic features of classification. In the diagnosis of hematological disorders

  • proliferation of marrow precursors, the
  • domination of a cell line, and features of
  • suppression of hematopoiesis

provide a two dimensional model.  Other dimensions are created by considering

  • the maturity of the circulating cells.

The application of rules-based, automated problem solving should provide a valid approach to

  • the classification and interpretation of the data used to determine a knowledge-based clinical opinion.

The exponential growth of knowledge since the mapping of the human genome enabled by parallel advances in applied mathematics that have not been a part of traditional clinical problem solving.

As the complexity of statistical models has increased

  • the dependencies have become less clear to the individual.

Contemporary statistical modeling has a primary goal of finding an underlying structure in studied data sets.
The development of an evidence-based inference engine that can substantially interpret the data at hand and

  • convert it in real time to a “knowledge-based opinion”

could improve clinical decision-making by incorporating

  • multiple complex clinical features as well as duration of onset into the model.

An example of a difficult area for clinical problem solving is found in the diagnosis of SIRS and associated sepsis. SIRS (and associated sepsis) is a costly diagnosis in hospitalized patients.   Failure to diagnose sepsis in a timely manner creates a potential financial and safety hazard.  The early diagnosis of SIRS/sepsis is made by the application of defined criteria by the clinician.

  • temperature
  • heart rate
  • respiratory rate and
  • WBC count

The application of those clinical criteria, however, defines the condition after it has developed and

  • has not provided a reliable method for the early diagnosis of SIRS.

The early diagnosis of SIRS may possibly be enhanced by the measurement of proteomic biomarkers, including

  • transthyretin
  • C-reactive protein
  • procalcitonin
  • mean arterial pressure

Immature granulocyte (IG) measurement has been proposed as a

  • readily available indicator of the presence of granulocyte precursors (left shift).

The use of such markers, obtained by automated systems

  • in conjunction with innovative statistical modeling, provides
  • a promising approach to enhance workflow and decision making.

Such a system utilizes the conjoined syndromic features of

  • disparate data elements with an anticipated reduction of medical error.

How we frame our expectations is so important that it determines

  • the data we collect to examine the process.

In the absence of data to support an assumed benefit, there is no proof of validity at whatever cost.
This has meaning for

  • hospital operations,
  • for nonhospital laboratory operations,
  • for companies in the diagnostic business, and
  • for planning of health systems.

The problem stated by LL  WEED in “Idols of the Mind” (Dec 13, 2006): “ a root cause of a major defect in the health care system is that, while we falsely admire and extol the intellectual powers of highly educated physicians, we do not search for the external aids their minds require”.  HIT use has been

  • focused on information retrieval, leaving
  • the unaided mind burdened with information processing.

We deal with problems in the interpretation of data presented to the physician, and how through better

  • design of the software that presents this data the situation could be improved.

The computer architecture that the physician uses to view the results is more often than not presented

  • as the designer would prefer, and not as the end-user would like.

In order to optimize the interface for physician, the system would have a “front-to-back” design, with
the call up for any patient ideally consisting of a dashboard design that presents the crucial information

  • that the physician would likely act on in an easily accessible manner.

The key point is that each item used has to be closely related to a corresponding criterion needed for a decision.

Feature Extraction.

This further breakdown in the modern era is determined by genetically characteristic gene sequences
that are transcribed into what we measure.  Eugene Rypka contributed greatly to clarifying the extraction
of features in a series of articles, which

  • set the groundwork for the methods used today in clinical microbiology.

The method he describes is termed S-clustering, and

  • will have a significant bearing on how we can view laboratory data.

He describes S-clustering as extracting features from endogenous data that

  • amplify or maximize structural information to create distinctive classes.

The method classifies by taking the number of features

  • with sufficient variety to map into a theoretic standard.

The mapping is done by

  • a truth table, and each variable is scaled to assign values for each: message choice.

The number of messages and the number of choices forms an N-by N table.  He points out that the message

  • choice in an antibody titer would be converted from 0 + ++ +++ to 0 1 2 3.

Even though there may be a large number of measured values, the variety is reduced

  • by this compression, even though there is risk of loss of information.

Yet the real issue is how a combination of variables falls into a table with meaningful information. We are concerned with accurate assignment into uniquely variable groups by information in test relationships. One determines the effectiveness of each variable by

  • its contribution to information gain in the system.

The reference or null set is the class having no information.  Uncertainty in assigning to a classification is

  • only relieved by providing sufficient information.

The possibility for realizing a good model for approximating the effects of factors supported by data used

  • for inference owes much to the discovery of Kullback-Liebler distance or “information”, and Akaike
  • found a simple relationship between K-L information and Fisher’s maximized log-likelihood function.

In the last 60 years the application of entropy comparable to

  • the entropy of physics, information, noise, and signal processing,
  • has been fully developed by Shannon, Kullback, and others, and has been integrated with modern statistics,
  • as a result of the seminal work of Akaike, Leo Goodman, Magidson and Vermunt, and work by Coifman.

Gil David et al. introduced an AUTOMATED processing of the data available to the ordering physician and

  • can anticipate an enormous impact in diagnosis and treatment of perhaps half of the top 20 most common
  • causes of hospital admission that carry a high cost and morbidity.

For example: anemias (iron deficiency, vitamin B12 and folate deficiency, and hemolytic anemia or myelodysplastic syndrome); pneumonia; systemic inflammatory response syndrome (SIRS) with or without bacteremia; multiple organ failure and hemodynamic shock; electrolyte/acid base balance disorders; acute and chronic liver disease; acute and chronic renal disease; diabetes mellitus; protein-energy malnutrition; acute respiratory distress of the newborn; acute coronary syndrome; congestive heart failure; disordered bone mineral metabolism; hemostatic disorders; leukemia and lymphoma; malabsorption syndromes; and cancer(s)[breast, prostate, colorectal, pancreas, stomach, liver, esophagus, thyroid, and parathyroid].

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH (Chairman). Prealbumin in Nutritional Care Consensus Group.

Measurement of visceral protein status in assessing protein and energy malnutrition: standard of care. Nutrition 1995; 11:169-171.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering, 33(7):2170–2174, July 1994.

R. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

Realtime Clinical Expert Support and validation System

We have developed a software system that is the equivalent of an intelligent Electronic Health Records Dashboard that provides empirical medical reference and suggests quantitative diagnostics options.

The primary purpose is to

  1. gather medical information,
  2. generate metrics,
  3. analyze them in realtime and
  4. provide a differential diagnosis,
  5. meeting the highest standard of accuracy.

The system builds its unique characterization and provides a list of other patients that share this unique profile, therefore utilizing the vast aggregated knowledge (diagnosis, analysis, treatment, etc.) of the medical community. The

  • main mathematical breakthroughs are provided by accurate patient profiling and inference methodologies
  • in which anomalous subprofiles are extracted and compared to potentially relevant cases.

As the model grows and its knowledge database is extended, the diagnostic and the prognostic become more accurate and precise. We anticipate that the effect of implementing this diagnostic amplifier would result in

  • higher physician productivity at a time of great human resource limitations,
  • safer prescribing practices,
  • rapid identification of unusual patients,
  • better assignment of patients to observation, inpatient beds,
    intensive care, or referral to clinic,
  • shortened length of patients ICU and bed days.

The main benefit is a real time assessment as well as diagnostic options based on

  • comparable cases,
  • flags for risk and potential problems

as illustrated in the following case acquired on 04/21/10. The patient was diagnosed by our system with severe SIRS at a grade of 0.61 .

Graphical presentation of patient status

The patient was treated for SIRS and the blood tests were repeated during the following week. The full combined record of our system’s assessment of the patient, as derived from the further hematology tests, is illustrated below. The yellow line shows the diagnosis that corresponds to the first blood test (as also shown in the image above). The red line shows the next diagnosis that was performed a week later.

Progression changes in patient ICU stay with SIRS

Chemistry of Herceptin [Trastuzumab] is explained with images in

http://www.chm.bris.ac.uk/motm/herceptin/index_files/Page450.htm

 

REFERENCES

The Cost Burden of Disease: U.S. and Michigan CHRT Brief. January 2010.
@www.chrt.org

The National Hospital Bill: The Most Expensive Conditions by Payer, 2006. HCUP Brief #59.

Rudolph RA, Bernstein LH, Babb J: Information-Induction for the diagnosis of myocardial infarction. Clin Chem 1988;34:2031-2038.

Bernstein LH, Qamar A, McPherson C, Zarich S, Rudolph R. Diagnosis of myocardial infarction: integration of serum markers and clinical descriptors using information theory. Yale J Biol Med 1999; 72: 5-13.

Kaplan L.A.; Chapman J.F.; Bock J.L.; Santa Maria E.; Clejan S.; Huddleston D.J.; Reed R.G.; Bernstein L.H.; Gillen-Goldstein J. Prediction of Respiratory Distress Syndrome using the Abbott FLM-II amniotic fluid assay. The National Academy of Clinical Biochemistry (NACB) Fetal Lung Maturity Assessment Project.  Clin Chim Acta 2002; 326(8): 61-68.

Bernstein LH, Qamar A, McPherson C, Zarich S. Evaluating a new graphical ordinal logit method (GOLDminer) in the diagnosis of myocardial infarction utilizing clinical features and laboratory data. Yale J Biol Med 1999; 72:259-268.

Bernstein L, Bradley K, Zarich SA. GOLDmineR: Improving models for classifying patients with chest pain. Yale J Biol Med 2002; 75, pp. 183-198.

Ronald Raphael Coifman and Mladen Victor Wickerhauser. Adapted Waveform Analysis as a Tool for Modeling, Feature Extraction, and Denoising. Optical Engineering 1994; 33(7):2170–2174.

  1. Coifman and N. Saito. Constructions of local orthonormal bases for classification and regression. C. R. Acad. Sci. Paris, 319 Série I:191-196, 1994.

W Ruts, S De Deyne, E Ameel, W Vanpaemel,T Verbeemen, And G Storms. Dutch norm data for 13 semantic categories and 338 exemplars. Behavior Research Methods, Instruments, & Computers 2004; 36 (3): 506–515.

De Deyne, S Verheyen, E Ameel, W Vanpaemel, MJ Dry, WVoorspoels, and G Storms.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts.  Behavior Research Methods 2008; 40 (4): 1030-1048

Landauer, T. K., Ross, B. H., & Didner, R. S. (1979). Processing visually presented single words: A reaction time analysis [Technical memorandum].  Murray Hill, NJ: Bell Laboratories. Lewandowsky, S. (1991).

Weed L. Automation of the problem oriented medical record. NCHSR Research Digest Series DHEW. 1977;(HRA)77-3177.

Naegele TA. Letter to the Editor. Amer J Crit Care 1993:2(5):433.

Retinal prosthetic strategy with the capacity to restore normal vision, Sheila Nirenberg and Chethan Pandarinath

http://www.pnas.org/content/109/37/15012

 

Other related articles published in http://pharmaceuticalintelligence.com include the following:

 

  • The Automated Second Opinion Generator

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/08/13/the-automated-second-opinion-generator/

 

  • The electronic health record: How far we have travelled and where is journeys end

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2012/09/21/the-electronic-health-record-how-far-we-have-travelled-and-where-is-journeys-end/

 

  • The potential contribution of informatics to healthcare is more than currently estimated.

Larry H Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2013/02/18/the-potential-contribution-of-informatics-to-healthcare-is-more-than-currently-estimated/

 

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  • Demonstration of a diagnostic clinical laboratory neural network applied to three laboratory data conditioning problems

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https://pharmaceuticalintelligence.com/2013/01/03/the-acuity-pci-score-will-it-replace-four-established-risk-scores-timi-grace-syntax-and-clinical-syntax/

 

  • Coronary artery disease in symptomatic patients referred for coronary angiography: Predicted by Serum Protein Profiles

Aviva Lev-Ari, PhD, RN 12/29/2012

https://pharmaceuticalintelligence.com/2012/12/29/coronary-artery-disease-in-symptomatic-patients-referred-for-coronary-angiography-predicted-by-serum-protein-profiles

 

  • New Definition of MI Unveiled, Fractional Flow Reserve (FFR)CT for Tagging Ischemia

Aviva Lev-Ari, PhD, RN 8/27/2012

https://pharmaceuticalintelligence.com/2012/08/27/new-definition-of-mi-unveiled-fractional-flow-reserve-ffrct-for-tagging-ischemia/
 

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Read Full Post »

Reporter: Aviva Lev-Ari, PhD, RN

 

Medicare Reveals Hospital Charge Information

By David Pittman, Washington Correspondent, MedPage Today

Published: May 08, 2013

 

WASHINGTON — The Obama administration made public on Wednesday previously unpublished hospital charges for the 100 most common inpatient treatments in 2011, saying a similar release of physician data is on the horizon.

The massive data file reveals wide variation in charges for these 100 services listed in hospitals’ “chargemasters” — industry jargon for what hospitals charge. The data set represents added transparency the administration hopes will influence consumer behavior.

“Making this available for free for the first time will save consumers money by arming them with information that can help them make better choices,” Health and Human Services Secretary Kathleen Sebelius said in a call with reporters Wednesday.

The data only include inpatient hospital services, but when asked about physician fees and other inpatient services, a top Centers for Medicare & Medicaid Services (CMS) official said those data could come later as the agency expands its price transparency initiative.

“We don’t have a set timetable for expansion for this data release,” Jonathan Blum, PhD, acting principal deputy administrator at CMS, said on the same call as Sebelius. “I think it is fair to say we intend to build upon this data release.”

Blum said multiple times in his call with reporters that CMS will study the impact this information has on consumer behavior and what value the public places on it.

Journalist Steven Brill — who wrote a March 4 Time magazine cover story on healthcare-pricing practices largely credited for CMS’ action Wednesday — said in a blog that Sebelius and CMS should next focus on outpatient services.

“The Feds need to publish chargemaster and Medicare pricing for the most frequent outpatient procedures and diagnostic tests at clinics — two huge profit venues in the medical world,” Brill wrote. “This will be harder — the government doesn’t collect that data as comprehensively — but those outpatient centers and clinics provide a huge portion of American medical care.”

A quick scan of the hospital data released Wednesday reveals wide variation for the same procedure in the same town.

For example, St. Dominic Hospital in Jackson, Miss., charged nearly $26,000 to implant a pacemaker while the University of Mississippi Medical Center across town charged more than $57,000 for the same procedure.

In Washington, the George Washington University Hospital charged nearly $69,000 for a lower-leg joint replacement without major complications. That same procedure cost just under $30,000 at Sibley Memorial Hospital — a nonprofit community hospital 5 miles away.

A joint replacement ranged from $5,300 at a hospital in Ada, Okla., to $223,000 at a hospital in Monterey Park, Calif., CMS said.

“Hospitals that charge two or three times the going rate rightfully face greater scrutiny,” Sebelius said.

Said Blum, “We’re really trying to help elevate the conversation and continue the conversation and to ask questions why there is so much variation.”

Common explanations for the varying costs — patients’ health status, hospital payer mix, teaching status — don’t seem accurate or clear from data CMS released, Blum said, adding that making such information public will help researchers, consumers, and others better ask questions and engage in debate over costs.

Opponents to such transparency note that chargemaster prices are irrelevant to most patients. Private insurance companies and Medicare negotiate their own prices with hospitals.

Instead, it’s only the uninsured who face the prices on the chargemaster.

“Most perniciously, uninsured people are the ones who usually pay the highest prices for their hospital care,” Ron Pollack, executive director of the liberal patient rights group Families USA here,said in a statement. “It is absurd – and, indeed, unconscionable – that the people least capable of paying for their hospital care bear the largest, and often unaffordable, cost burdens.”

The American Hospital Association (AHA) said healthcare’s “charge” system is a matter of financing that urgently needs updating.

“The complex and bewildering interplay among ‘charges,’ ‘rates,’ ‘bills’ and ‘payments’ across dozens of payers, public and private, does not serve any stakeholder well, including hospitals,”AHA president and chief executive Rich Umbdenstock said in a statement. “This is especially true when what is most important to a patient is knowing what his or her financial responsibility will be.”

The Federation of American Hospitals declined to comment.

 

David Pittman

 

David Pittman is MedPage Today’s Washington Correspondent, following the intersection of policy and healthcare. He covers Congress, FDA, and other health agencies in Washington, as well as major healthcare events. David holds bachelors’ degrees in journalism and chemistry from the University of Georgia and previously worked at the Amarillo Globe-News in Texas,Chemical & Engineering News and most recently FDAnews.

 

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On Devices and On Algorithms: Arrhythmia after Cardiac Surgery Prediction and ECG Prediction of Paroxysmal Atrial Fibrillation Onset

Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC

and

Article Curator: Aviva Lev-Ari, PhD, RN

Cleveland Clinic research spurs a device that could predict arrhythmia after cardiac surgery

April 30, 2013 9:03 am by  |

ECG

Heart doctors at the Cleveland Clinic  hope to give doctors a way to tell which patients might develop arrhythmia after cardiac surgery.

Atrial fibrillation (AFIB) is one of the most common complications of heart surgeries, and also occurs as a complication of elevated alcohol use, high blood pressure, valve disease or thyroid disease. Atrial fibrillation consists of the round parts of the Valentine heart (the atria) shivering chaotically instead of beating rhythmically. Atrial fibrillation is a common arrhythmia, eventually affecting 20% of adults. There are 3 varieties: paroxysmal (intermittent), persistent (continual) and permanent (unremitting).  When AFIB lasts longer than 24-48 hours the risk of forming a blood clot in the atria rises, which in turn can cause a stroke or a heart attack. AFIB often results in fast heart rates which may cause low blood pressure and its possible consequences (organ injury, heart attack). Also, prolonged fast rates weaken the heart (reversible rate-related cardiomyopathy), which can persist for months after regaining target ranges for the heart rates (target for rate control is 60-80/minute instead of the fast rates of 100-180/min that are common with untreated AFIB).

A scoring system (CHADS2) can predict who may suffer from a stroke due to AFIB that lasts >24-48 hours, and in particular, who may benefit from longterm anticoagulation (blood thinners to interfere with clot formation). A pill-in-the-pocket can stop AFIB within hours.  Amiodarone, a highly toxic medication (10% long-term uses face side effects of serious damage to liver, lung, thyroid or eyes), is often prescribed “off-label” (without FDA endorsement) because it is 70% effective in preventing AFIB recurrence, and it has less anticontractility (weakening of the strength of heart beats) than most other rhythm medications. Then next most effective medication for suppression of AFIB long-term is sotalol, which reduces the strength of heart contraction (may not be tolerated by patients with severe heart failure) and it prolongs QT interval of repolarization after each heartbeat, a risk factor for a deadly rhythm called torsades de pointes. Interventional cures (“AFIB ablation”) have been developed to prevent recurrences.

Predicting AFIB may have several benefits: (1) potentially, earlier use of pill-in-the-pocket could prevent episodes rather that wait for them to occur, get noticed, and then treated, as only ~50% of AFIB episodes are noticed by the patient, according to electrographic monitor reports; (2) surrogate endpoint (prediction of onset) may offer useful guidance as to sufficiency of a suppressive therapy to enable lower dosing of toxic treatments; (3)  surrogate endpoint (prediction of onset) may offer useful guidance as to sufficient lowering of alohol intake, sufficient control of blood pressure, sufficient control of thyroid abnormalities, and other prevention opportunities; (4) surrogate endpoints may facilitate AFIB ablation.

Work done in the lab of Dr. C. Allen Bashour indicated that most patients who experience atrial fibrillation after heart surgery show clues beforehand in the form of subtle changes in their ECG readings that aren’t detected with the way they’re monitored now.

Rindex Medical is commercializing a tool that would enable physicians to predict which patients will experience AF so they can receive prophylactic treatment before it occurs.

“Right now they basically guess, or treat everyone prophylactically,” said co-founder Alex Arrow. “Some clinicians say they have an intuition about who will get it, but it’s mostly guesswork.”

Rindex’s A-50 AF Prediction System uses algorithms developed at the Clinic to analyze a patient’s ECG signals through 17 steps and produce a score, from 1 to 100, of how likely that patient is to experience AF. Arrow said the final product will be a touch-screen monitor that displays a score and tracks the score over a nine-hour period.

The Redwood City, California, company has been issued the first of its patents for the device and the exclusive license from Cleveland Clinic to develop the technology. Self-funded by Arrow and co-founders Denis Hickey and Lucas Fairfield, Rindex has a working prototype and is making progress on preparations for its 510(k) application. Arrow said the company shouldn’t need to raise a series A until it’s ready for a clinical trial.

Many other research groups have explored ways to predict AF in its various forms from natriuretic peptides to ECG changes, but no method has been established as reliably for this purpose.

Read more: http://medcitynews.com/2013/04/cleveland-clinic-research-spurs-a-device-that-could-predict-arrhythmias-after-cardiac-surgery/#ixzz2ScbxIyW0

http://medcitynews.com/2013/04/cleveland-clinic-research-spurs-a-device-that-could-predict-arrhythmias-after-cardiac-surgery/?goback=%2Egde_1503357_member_237204073

Dec 13, 2012

ECG predicts atrial fibrillation onset

Atrial fibrillation (AF), the most common cardiac arrhythmia, is categorized by different forms. One sub-type is paroxysmal AF (PAF), which refers to episodes of arrhythmia that generally terminate spontaneously after no more than a few days. Although the underlying causes of PAF are still unknown, it’s clear that predicting the onset of PAF would be hugely beneficial, not least because it would enable the application of treatments to prevent the loss of sinus rhythm.

Many research groups are tackling the issue of predicting the onset of PAF. Now, however, researchers in Spain have developed a method that assesses the risk of PAF at least one hour before its onset. To date, the approach has not only successfully discriminated healthy individuals and PAF patients, but also distinguished patients far from and close to PAF onset (Physiol. Meas. 33 1959).

“The ability to assess the risk of arrhythmia at least one hour before its onset is clinically relevant,” Arturo Martinez from the University of Castilla-La Mancha told medicalphysicsweb. “Our method assesses the P-wave feature time course from single-lead long-term ECG recordings. Using a single ECG lead reduces the computational burden, paving the way for a real-time system in future.”

Analysing sinus rhythm

If the heart is beating normally, the sinus rhythm observed on an ECG will contain certain generic features, such as a P-wave that reflects the atrial depolarization and a large characteristic R peak flanked by two minima representing the depolarization of the heart’s right and left ventricles. If an irregular heart beat is suspected, an ECG will be used and typical findings include the absence of a P-wave.

“We hypothesized that different stages of AF could be identified when analysing long-term recordings extracted from patients prone to AF,” commented Martinez. “Our method differs to others in that we also use just one single lead to detect small differences in features from the P-wave time course.”

P for paroxysmal

Martinez and his collaborators, Raul Alcaraz and Jose Rieta, studied 24-hour Holter ECG recordings from 24 patients in whom PAF had been detected for the first time. For each patient, the longest sinus rhythm interval in the recording was selected, and the two hours preceding the onset of PAF were analysed. These readings were compared with those from 28 healthy individuals. In all cases, only the trace from the V1 ECG lead was considered.

A major challenge for the researchers was to extract the P-wave from the baseline noise. To overcome this, they used an automatic delineator algorithm based on a phasor transform that determines the precise time point relating to the onset, peak and offset of the P-wave. The authors described this algorithm in a previous research paper (Physiol. Meas. 31 1467).

“All of the recordings in our study were visually supervised by expert cardiologists who corrected the P-wave fiducial points when needed,” said Martinez. “Even in the presence of noise, which generated an incredible amount of P-wave distortion, our delineator provided location errors lower than 8 ms.”

In order to assess which time course features might be useful to predict the onset of PAF, the researchers analysed a number of variables. First, they examined factors representing the duration of the P-wave (Pdur), such as the distance between the P-wave onset and peak (Pini) and the distance between the P-wave peak and its offset (Pter). They then studied factors relating P- to R-waves, such as the distance between the two waves’ peaks (PRk) and, finally, beat-to-beat P-wave factors, such as the distance between two consecutive P-wave onset points (PPon).

“The most remarkable trends were provided by the features measuring P-wave duration,” report the authors in their paper. “Pduridentified appropriately 84.21% of all the analysed patients, obtaining a discriminant accuracy of 90.79% and 83.33% between healthy subjects and PAF patients far from PAF and close to PAF, respectively. The metrics related to the PR interval showed the most limited ability to identify patient groups.”

About the author

Jacqueline Hewett is a freelance science and technology journalist based in Bristol, UK.

http://medicalphysicsweb.org/cws/article/research/51820

Original Article

Physiol Meas. 2010 Nov;31(11):1467-85. doi: 10.1088/0967-3334/31/11/005. Epub 2010 Sep 24.

Application of the phasor transform for automatic delineation of single-lead ECG fiducial points.

Martínez AAlcaraz RRieta JJ.

Source

Innovation in Bioengineering Research Group, University of Castilla La Mancha, Spain. arturo.martinez@uclm.es

Abstract

This work introduces a new single-lead ECG delineator based on phasor transform. The method is characterized by its robustness, low computational cost and mathematical simplicity. It converts each instantaneous ECG sample into a phasor, and can precisely manage P and T waves, which are of notably lower amplitude than the QRS complex. The method has been validated making use of synthesized and real ECG sets, including the MIT-BIH arrhythmia, QT, European ST-T and TWA Challenge 2008 databases. Experiments with the synthesized recordings reported precise detection and delineation performances in a wide variety of ECGs, with signal-to-noise ratios of 10 dB and above. For real ECGs, the QRS detection was characterized by an average sensitivity of 99.81% and positive predictivity of 99.89%, for all the analyzed databases (more than one million beats). Regarding delineation, the maximum localization error between automatic and manual annotations was lower than 6 ms and its standard deviation was in agreement with the accepted tolerances for expert physicians in the onset and offset identification for QRS, P and T waves. Furthermore, after revising and reannotating some ECG recordings by expert cardiologists, the delineation error decreased notably, becoming lower than 3.5 ms, on average, and reducing by a half its standard deviation. This new proposed strategy outperforms the results provided by other well-known delineation algorithms and, moreover, presents a notably lower computational cost.

SOURCES:

Original Database

MIT-BIH Polysomnographic Database

This database is described in

Ichimaru Y, Moody GB. Development of the polysomnographic database on CD-ROM. Psychiatry and Clinical Neurosciences 53:175-177 (April 1999).

Please cite this publication when referencing this material, and also include the standard citation for PhysioNet:

Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation 101(23):e215-e220 [Circulation Electronic Pages; http://circ.ahajournals.org/cgi/content/full/101/23/e215]; 2000 (June 13).

The MIT-BIH Polysomnographic Database is a collection of recordings of multiple physiologic signals during sleep. Subjects were monitored in Boston’s Beth Israel Hospital Sleep Laboratory for evaluation of chronic obstructive sleep apnea syndrome, and to test the effects of constant positive airway pressure (CPAP), a standard therapeutic intervention that usually prevents or substantially reduces airway obstruction in these subjects. The database contains over 80 hours’ worth of four-, six-, and seven-channel polysomnographic recordings, each with an ECG signal annotated beat-by-beat, and EEG and respiration signals annotated with respect to sleep stages and apnea. For further information, see Signals and Annotations.

The database consists of 18 records, each of which includes 4 files:

Sleep/apneaannotations Beatannotations Signals Header View waveforms *
slp01a.st slp01a.ecg slp01a.dat slp01a.hea
slp01b.st slp01b.ecg slp01b.dat slp01b.hea
slp02a.st slp02a.ecg slp02a.dat slp02a.hea
slp02b.st slp02b.ecg slp02b.dat slp02b.hea
slp03.st slp03.ecg slp03.dat slp03.hea
slp04.st slp04.ecg slp04.dat slp04.hea
slp14.st slp14.ecg slp14.dat slp14.hea
slp16.st slp16.ecg slp16.dat slp16.hea
slp32.st slp32.ecg slp32.dat slp32.hea
slp37.st slp37.ecg slp37.dat slp37.hea
slp41.st slp41.ecg slp41.dat slp41.hea
slp45.st slp45.ecg slp45.dat slp45.hea
slp48.st slp48.ecg slp48.dat slp48.hea
slp59.st slp59.ecg slp59.dat slp59.hea
slp60.st slp60.ecg slp60.dat slp60.hea
slp61.st slp61.ecg slp61.dat slp61.hea
slp66.st slp66.ecg slp66.dat slp66.hea
slp67x.st slp67x.ecg slp67x.dat slp67x.hea

(*) You may follow these links to view the signals and st annotations using either WAVE (under Linux, SunOS, or Solaris) or WVIEW (under MS-Windows). To do so successfully, you must have configured your browser to use wavescript (for WAVE) or wvscript (for WVIEW) as a helper application, as described in the WAVE User’s Guide(see the section titled WAVE and the Web) and in Setting up WVSCRIPT.

Andrew Walsh observed that the calibration originally provided for the BP signal of record slp37 is incorrect (since it yielded negative BPs). slp37.hea now contains an estimated BP calibration that yields more plausible BPs; these should not be regarded as accurate, however, since there is no independent calibration standard available for this recording.

SOURCE:
Original Article
Proc Inst Mech Eng H. 2010;224(1):27-42.

Finding events of electrocardiogram and arterial blood pressure signals via discrete wavelet transform with modified scales.

Ghaffari AHomaeinezhad MRAkraminia MDavaeeha M.

Source

Cardiovascular Research Group, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran.

Abstract

A robust electrocardiogram (ECG) wave detection-delineation algorithm that can be applied to all ECG leads is developed in this study on the basis of discrete wavelet transform (DWT). By applying a new simple approach to a selected scale obtained from DWT, this method is capable of detecting the QRS complex, P-wave, and T-wave as well as determining parameters such as start time, end time, and wave sign (upward or downward). In the proposed method, the selected scale is processed by a sliding rectangular window of length n and the curve length in each window is multiplied by the area under the absolute value of the curve. In the next step, an adaptive thresholding criterion is conducted on the resulted signal. The presented algorithm is applied to various databases including the MIT-BIH arrhythmia database, European ST-T database, QT database, CinC Challenge 2008 database as well as high-resolution Holter data gathered in the DAY Hospital. As a result, the average values of sensitivity and positive prediction Se = 99.84 per cent and P+ = 99.80 per cent were obtained for the detection of QRS complexes with an average maximum delineation error of 13.7, 11.3, and 14.0 ms for the P-wave, QRS complex, and T-wave respectively. The presented algorithm has considerable capability in cases of a low signal-to-noise ratio, high baseline wander, and in cases where QRS complexes and T-waves appear with abnormal morphologies. Especially, the high capability of the algorithm in the detection of the critical points of the ECG signal, i.e. the beginning and end of the T-wave and the end of the QRS complex was validated by the cardiologist and the maximum values of 16.4 and 15.9 ms were recognized as absolute offset error of localization respectively. Finally, in order to illustrate an alternative capability of the algorithm, it is applied to all 18 subjects of the MIT-BIH polysomnographic database and the end-systolic and end-diastolic points of the blood pressure waveform were extracted and values of sensitivity and positive prediction Se = 99.80 per cent and P+ = 99.86 per cent were obtained for the detection of end-systolic, end-diastolic pulses.

http://www.ncbi.nlm.nih.gov/pubmed/20225455

Original Article

A robust wavelet-based multi-lead electrocardiogram delineation algorithm

  • a Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran
  • b CardioVascular Research Group (CVRG), Iran
  • c Non-invasive Cardiac Electrophysiology Laboratory, DAY Hospital, Tehran, Iran

Abstract

A robust multi-lead ECG wave detection-delineation algorithm is developed in this study on the basis of discrete wavelet transform (DWT). By applying a new simple approach to a selected scale obtained from DWT, this method is capable of detecting QRS complex, P-wave and T-wave as well as determining parameters such as start time, end time, and wave sign (upward or downward). First, a window with a specific length is slid sample to sample on the selected scale and the curve length in each window is multiplied by the area under the absolute value of the curve. In the next step, a variable thresholding criterion is designed for the resulted signal. The presented algorithm is applied to various databases including MIT-BIH arrhythmia database, European ST-T Database, QT Database, CinC Challenge 2008 Database as well as high resolution Holter data of DAY Hospital. As a result, the average values of sensitivity and positive predictivity Se = 99.84% and P+ = 99.80% were obtained for the detection of QRS complexes, with the average maximum delineation error of 13.7 ms, 11.3 ms and 14.0 ms for P-wave, QRS complex and T-wave, respectively. The presented algorithm has considerable capability in cases of low signal-to-noise ratio, high baseline wander, and abnormal morphologies. Especially, the high capability of the algorithm in the detection of the critical points of the ECG signal, i.e. the beginning and end of T-wave and the end of the QRS complex was validated by cardiologists in DAY hospital and the maximum values of 16.4 ms and 15.9 ms were achieved as absolute offset error of localization, respectively.

Abbreviations

  • ACL, area-curve length;
  • ECG, electrocardiogram;
  • DWT, discrete wavelet transform;
  • QTDB, QT database;
  • MITDB, MIT-BIH arrhythmia database; 
  • TWADB, T-wave alternans database;
  • CSEDB, common standards for electrocardiography database;
  • EDB, European ST-T database;
  • P+, positive predictivity (%);
  • Se,sensitivity (%);
  • FIR, finite-duration impulse response;
  • LE, location error;
  • CHECK#0, procedure of evaluating obtained results using MIT annotation files;
  • CHECK#1, procedure of evaluating obtained results consulting with a control cardiologist;
  • CHECK#2, procedure of evaluating obtained results consulting with a control cardiologist and also at least with 3 residents

Keywords

  • ECG delineation;
  • Discrete wavelet transform;
  • Variable threshold;
  • Validation

Figures and tables from this article:

Full-size image (14 K)
Fig. 1. FIR filter-bank implementation to generate discrete wavelet transform based on à trous algorithm.
Full-size image (12 K)
Fig. 2. Graphical representation of the logic of the proposed simple transformation for detecting onset and offset edges. In case I, both area and curve length are minimum, (ACLI < ACLII ≤ ACLIII).
Full-size image (58 K)
Fig. 3. The flow-chart of the proposed wavelet-aided electrocardiogram delineation algorithm (rectangle: operation, ellipse: result).
Full-size image (113 K)
Fig. 4. An excerpted segment from a total delineated ECG. Delineated (a) P-waves, (b) QRS complexes and (c) T-waves. (Circles: edges of event, triangles: peak of events, Partition A: lead I, Partition B: lead II).
Full-size image (76 K)
Fig. 5. Procedure of detecting and delineating of P and T-waves using ACL signal between two successive QRS complexes. (a) Simultaneously depiction of ACL, original ECG and the corresponding selected DWT scale, (b) QRS delineation, and (c) P and T-waves delineation.
SOURCE:

Volume 31, Issue 10, December 2009, Pages 1219–1227

http://www.sciencedirect.com/science/article/pii/S1350453309001647

Other related articles published on this Open Access Online Scientific Journal include the following:

Sustained Cardiac Atrial Fibrillation: Management Strategies by Director of the Arrhythmia Service and Electrophysiology Lab at The Johns Hopkins Hospital   http://pharmaceuticalintelligence.com/2012/10/16/sustained-cardiac-atrial-fibrillation-management-strategies-by-director-of-the-arrhythmia-service-and-electrophysiology-lab-at-the-johns-hopkins-hospital/

Cardiac Arrhythmias: A Risk for Extreme Performance Athletes                                                                                                                                                       http://pharmaceuticalintelligence.com/2012/08/08/cardiac-arrhythmias-a-risk-for-extreme-performance-athletes/

Acute Chest Pain/ER Admission: Three Emerging Alternatives to Angiography and PCI    http://pharmaceuticalintelligence.com/2013/03/10/acute-chest-painer-admission-three-emerging-alternatives-to-angiography-and-pci/

Dilated Cardiomyopathy: Decisions on implantable cardioverter-defibrillators (ICDs) using left ventricular ejection fraction (LVEF) and Midwall Fibrosis: Decisions on Replacement using late gadolinium enhancement cardiovascular MR (LGE-CMR)
http://pharmaceuticalintelligence.com/2013/03/10/dilated-cardiomyopathy-decisions-on-implantable-cardioverter-defibrillators-icds-using-left-ventricular-ejection-fraction-lvef-and-midwall-fibrosis-decisions-on-replacement-using-late-gadolinium/

Ablation Devices Market to 2016 – Global Market Forecast and Trends Analysis by Technology, Devices & Applications
http://pharmaceuticalintelligence.com/2012/12/23/ablation-devices-market-to-2016-global-market-forecast-and-trends-analysis-by-technology-devices-applications/

Read Full Post »

Biomaterials Technology: Models of Tissue Engineering for Reperfusion and Implantable Devices for Revascularization

Author and Curator: Larry H Bernstein, MD, FACP

and

Curator: Aviva Lev-Ari, PhD, RN

http://pharmaceuticalintelligence.com/5_04_2013/bernstein_lev-ari/Bioengineering_of_Vascular_and_Tissue_Models

This is the THIRD of a three part series on the evolution of vascular biology and the studies of the effects of biomaterials
in vascular reconstruction and on drug delivery, which has embraced a collaboration of cardiologists at Harvard Medical School , Affiliated Hospitals, and MIT,
requiring cardiovascular scientists at the PhD and MD level, physicists, and computational biologists working in concert, and
an exploration of the depth of the contributions by a distinguished physician, scientist, and thinker.

The FIRST part – Vascular Biology and Disease – covered the advances in the research on

Drug Eluting Stents: On MIT’s Edelman Lab’s Contributions to Vascular Biology and its Pioneering Research on DES

  • vascular biology,
  • signaling pathways,
  • drug diffusion across the endothelium and
  • the interactions with the underlying muscularis (media),
  • with additional considerations for type 2 diabetes mellitus.

The SECOND part – Stents and Drug Delivery – covered the

Vascular Repair: Stents and Biologically Active Implants

  • purposes,
  • properties and
  • evolution of stent technology with
  • the acquired knowledge of the pharmacodynamics of drug interactions and drug distribution.

In this THIRD part, on Problems and Promise of Biomaterials Technology, we cover the biomaterials used and the design of the cardiovascular devices, extension of uses, and opportunities for improvement

Biomaterials Technology: Tissue Engineering and Vascular Models –

Problems and Promise

We have thus far elaborated on developments in the last 15 years that have led to significant improvements in cardiovascular health.

First, there has been development of smaller sized catheters that can be introduced into

  • not only coronary arteries, but into the carotid and peripheral vasculature;

Second, there has been specific design of coated-stents that can be placed into an artery

  • for delivery of a therapeutic drug.

This began with a focus on restenosis, a serious problem after vascular repair, beginning
with the difficult problem of  control of heparin activity given intravenously, and was
extended to modifying the heparan-sulfate molecular structure

  • to diminish vascular endothelial hyperplasia,
  • concurrent with restriction of the anticoagulant activity.

Third, the ability to place stents with medicated biomaterials locally has extended to

  • the realm of chemotherapy, and we shall see where this progresses.

The Engineered Arterial Blood Flow Models

Biomedical engineers, in collaboration with physicians, biologists, chemists, physicists, and
mathematicians, have developed models to predict vascular repair by knowledge of

  • the impact of interventions on blood flow.

These models have become increasingly sophisticated and precise, and they propel us
toward optimization of cardiovascular therapeutics in general and personalizing treatments
for patients with cardiovascular disease. (1)
The science of vascular biology has been primarily stimulated by the clinical imperative to

  • combat complications that ensue from vascular interventions.

Thus, when a novel vascular biological finding or cardiovascular medical/surgical technique
is presented, we are required to ask the 2-fold question:

  • what have we learned about the biology of the blood vessel?
  • how might this knowledge be used to enhance clinical perspective and treatment?

The innovative method of engineering arterial conduits presented by Campbell et al. in
Circulation Research presents us with just such a challenge, and we deal with it’s biological and clinical ramifications.

Each of four pivotal studies in vascular tissue engineering has been an important advance
in the progression to a tissue-engineered blood vessel that can serve as a

  • living graft, responsive to the biological environment as
  • a self-renewing tissue with an inherent healing potential.
  • Weinberg and Bell taught us that a tissue-engineered graft could be constructed
  • and could be composed of human cells.

L’heureux et al demonstrated that the mechanical strength of such a material

  • derived in major part from the extracellular matrix and
  • production of matrix and integrity of cellular sheets
  • could be enhanced by alterations in culture conditions.

Niklason et al. noted that grafts are optimally formed

  • when incubated within environmental conditions that they will confront in vivo
  • or would have experienced if formed naturally.

Campbell et al. now demonstrate that it is possible to remove

  • the immune reaction and acute rejection that may follow cell-based grafting
  • by culturing tissues in the anticipated host and
  • address a fundamental issue of whether cell source or site of cell placement
  • dictates function after cell implantation.

It appears that the vascular matrix can be remodeled by the body according to the needs of the environment. It may
very well be that the ultimate configuration of autologous cell-based vascular graft need not be determined at
outset by the cells that comprise the device, but rather

  • by a dynamics that is established by environmental needs, wherein the body molds
  • tissue-engineered constructs to meet
    • local flow,
    • metabolic, and
    • inflammatory requirements.

In other words, cell source for tissue reconstruction may be secondary to
cell pliability to environmental influence.

Endothelial and smooth muscle cells from many, perhaps any,

  • vascular bed can be used to create new grafts and will then
  • achieve secondary function once in place in the artery.

The environmental remodeling observed after implantation

  • may modify limitations of grafts that are composed of nonvascular peritoneal cells whose initial structure
    is not either venous or arterial. (2)
  • The trilaminate vascular architecture provides biochemical regulation and mechanical integrity.
  • Yet regulatory control can be regained after injury without recapitulating tertiary structure.

Tissue-engineered (TE) endothelium controls repair even when

  • placed in the perivascular space of injured vessels.

It remains unclear from vascular repair studies whether endothelial implants recapitulate the vascular
epithelial lining
or expose injured tissues to endothelial cells (ECs) with unique healing potential because

  • ECs line the vascular epithelium and the vasa vasorum.

Authors examined this issue in a nonvascular tubular system, asking whether airway repair is controlled by

  • bronchial epithelial cells (EPs) or by
  • Endothelial Cells (ECs) of the perfusing bronchial vasculature.

Localized bronchial denuding injury

  • damaged epithelium, narrowed bronchial lumen, and led to
  • mesenchymal cell hyperplasia, hypervascularity, and inflammatory
  • cell infiltration. Peribronchial TE constructs embedded with

EPs or ECs limited airway injury, although optimum repair was obtained

  • when both cells were present in TE matrices.

EC and EP expression of

  • PGE2, TGF1, TGF2, GM-CSF, IL-8, MCP-1, and soluble VCAM-1
  • and ICAM-1 was altered by matrix embedding,

but expression was altered most significantly when both,

  • EC and EP,  cells were present simultaneously.

EPs may provide for functional control of organ injury and fibrous response, and

ECs may provide for preservation of tissue perfusion and the epithelium in particular.

Together the two cells

  • optimize functional restoration and healing, suggesting that
  • multiple cells of a tissue contribute to the differentiated biochemical function and repair
    of a tissue, but 
    need not assume
  • a fixed, ordered architectural relationship, as in intact tissues, to achieve these effects. (3)

Matrix-embedded Endothelial Cells (MEECs) Implants

The implantation of matrix-embedded endothelial cells (MEECs)

  • is considered to have therapeutic potential in controlling the vascular response to injury and
  • maintaining patency in arteriovenous anastomoses.

Authors considered the 3-dimensional microarchitecture of the tissue engineering scaffold to be
a key regulator of endothelial behavior in MEEC constructs.

Notably, Authors found that

  • ECs in porous collagen scaffold had a markedly altered cytoskeletal structure with oriented actin
    fibers
    and rearranged focal adhesion proteins, in comparison to cells grown on 2D surfaces.

Examining the immunomodulatory capabilities of MEECs revealed, MEECs were able to reduce the recruitment
of monocytes
to an inflamed endothelial monolayer by 5-fold compared to EC on 2D surfaces.

An analysis of secreted factors from the cells revealed

  • an 8-fold lower release of Monocyte Chemotactic Protein-1 (MCP-1) from MEECs.

Differences between 3D and 2D cultured cells were abolished in the presence of

  • inhibitors to the focal adhesion associated signaling molecule Src, suggesting that
  • adhesion-mediated signaling is essential in controlling the potent immunomodulatory
    effects of MEEC. (4)

Cardiogenesis is regulated by a complex interplay between transcription factors. How do these interactions
regulate the transition from mesodermal precursors to cardiac progenitor cells (CPCs)?

Yin Yang 1 (YY1), a member of the GLI-Kruppel

  • family of DNA-binding zinc finger transcription factor (TF), can
  • activate or inhibit transcription in a context-dependent manner.

Bioinformatic-based Transcription Factor Genome-wide Sequencing Analysis

These investigators performed a bioinformatic-based transcription factor genome-wide sequencing analysis

  • binding  site analysis on upstream promoter regions of genes that are enriched in embryonic stem cell–derived CPCs
  • to identify novel regulators of mesodermal cardiac lineage

From 32 candidate transcription factors screened, they found that

  • Yin Yang 1 (YY1), a repressor of sarcomeric gene expression, is present in CPCs.

They uncovered the ability of YY1 to transcriptionally activate Nkx2.5,

  • Nkx2.5 as a key marker of early cardiogenic commitment.
  • YY1 regulates Nkx2.5 expression via a 2.1-kb cardiac-specific enhancer as demonstrated by in vitro
  1. luciferase-based assays,
  2. in vivo chromatin immunoprecipitation,
  3. and genome-wide sequencing analysis.

Furthermore, the ability of YY1 to activate Nkx2.5 expression depends on its cooperative interaction with Gata4.

Cardiac mesoderm–specific loss-of-function of YY1 resulted in early embryonic lethality.

This was corroborated in vitro by embryonic stem cell–based assays which showed the

  • overexpression of YY1 enhanced the cardiogenic differentiation of embryonic stem cells into CPCs.

The results indicate an essential and unexpected role for YY1

  • to promote cardiogenesis as a transcriptional activator of Nkx2.5
  • and other CPC-enriched genes. (5)

Proportional Hazards Models to Analyze First-onset of Major
Cardiovascular Disease Events

Various measures of arterial stiffness and wave reflection are considered to be cardiovascular risk markers.

Prior studies have not assessed relations of a comprehensive panel of stiffness measures to prognosis

Authors used Proportional Hazards Models to analyze first-onset of major cardiovascular disease events 

  • myocardial infarction,
  • unstable angina,
  • heart failure, or
  • stroke

In relation to arterial stiffness measured by

  • pulse wave velocity [PWV]
  • wave reflection
  • augmentation index [AI]
  • carotid-brachial pressure amplification [PPA]
  • and central pulse pressure [CPP]

in 2232 participants (mean age, 63 years; 58% women) in the Framingham Heart Study.

During median follow-up of 7.8 (range, 0.2 to 8.9) years,

  • 151 of 2232 participants (6.8%) experienced an event.

In multivariable models adjusted for

  • age,
  • sex,
  • systolic blood pressure,
  • use of antihypertensive therapy,
  • total and high-density lipoprotein cholesterol concentrations,
  • smoking, and
  • presence of diabetes mellitus,

Higher aortic PWV was associated with a 48% increase in

  • cardiovascular disease risk
    (95% confidence interval, 1.16 to 1.91 per SD; P0.002).

After PWV was added to a standard risk factor model,

  • integrated discrimination improvement was 0.7%
    (95% confidence interval, 0.05% to 1.3%; P < 0.05).

In contrast, AI, CPP, and PPA were not related to

  • cardiovascular disease outcomes in multivariable models.

(1) Higher aortic stiffness assessed by PWV is associated with

  • increased risk for a first cardiovascular event.

(2) Aortic PWV improves risk prediction when added to standard risk factors

  • and may represent a valuable biomarker of CVD risk in the community. (6)

1. Engineered arterial models to correlate blood flow to tissue biological response. J Martorell, P Santoma, JJ Molins,
AA Garcıa-Granada, JA Bea, et al.  Ann NY Acad Sci 2012: 1254:51–56. (Issue: Evolving Challenges in Promoting
Cardiovascular Health)    http://dx.doi.org/10.1111/j.1749-6632.2012.06518.x

2.  Vascular Tissue Engineering. Designer Arteries. Elazer R. Edelman. Circ Res. 1999; 85:1115-1117
http://www.circresaha.org  http://dx.doi.org/10.1161/01.RES.85.12

3.  Tissue-engineered endothelial and epithelial implants differentially and synergistically regulate airway repair.
BG Zani, K Kojima, CA Vacanti, and ER Edelman.   PNAS 13, 2008; 105(19):7046–7051.
http://www.pnas.org/cgi/doi/10.1073/pnas.0802463105

4.  The role of scaffold microarchitecture in engineering endothelial cell immunomodulation.
L Indolfi, AB Baker, ER Edelman. Biomaterials 2012; http://dx.doi.org/10.1016/j.biomaterials.2012.06.052

5.  Essential and Unexpected Role of Yin Yang 1 to Promote Mesodermal Cardiac Differentiation. S Gregoire, R Karra,
D Passer, Marcus-André Deutsch, et al.  Circ Res. 2013;112:900-910. http://dx.doi.org/10.1161/CIRCRESAHA.113.259259
http://circres.ahajournals.org/doi:10.1161/CIRCRESAHA.113.259259

6.  Arterial Stiffness and Cardiovascular Events. The Framingham Heart Study.
GF Mitchell, Shih-Jen Hwang, RS Vasan, MG Larson, et al.  Circulation. 2010;121:505-511.
http://circ.ahajournals.org/doi/10.1161/CIRCULATIONAHA.109.886655

Cardiology Diagnosis of ACS and Stents – 2012

The Year in Cardiology 2012: Acute Coronary Syndromes.

Nick E.J. West      http://www.medscape.com/viewarticle/779039

The European Society of Cardiology (ESC) produced updated guidance on management of STEMI in 2012.
It also produced a third version of the Universal Definition of Myocardial Infarction.
The importance of early diagnosis is stressed, with first ECG in patients

  • with suspected STEMI recommended within 10 min of first medical contact (FMC)
  • and primary percutaneous coronary intervention (PPCI) for STEMI
  • ideally within 90 min (rated ‘acceptable’ out to a maximum of 120 min).

The guidance highlights the importance of collaborative networks

  • to facilitate achievement of such targets.
  • the importance of prompt assessment
  • management of atypical presentations not always considered under the umbrella of STEMI, including
    • left bundle branch block (LBBB),
    • paced rhythms, and
    • isolated ST-segment elevation in lead aVR,

especially when accompanied by symptoms consistent with myocardial ischaemia.

Therapeutic hypothermia is now recommended for

  • all resuscitated patients with STEMI complicated by cardiac arrest
  •  immediate coronary angiography with a view to follow-on PPCI
  • when the ECG demonstrates persistent ST-segment elevation.

In the light of recently published studies and meta-analyses,

  • including that of Kalesan et al., drug-eluting stents (DES) are
  • now routinely preferred to bare metal stents (BMS) in view of
  • the reduced need for repeat revascularization and the lack of
  • previously perceived hazard for stent thrombosis.

The more potent antiplatelet agents prasugrel and ticagrelor are also preferred

  • to clopidogrel for all STEMI cases, with duration of dual antiplatelet therapy (DAPT)
  • ideally for 1 year, but reduced to a strict
  • minimum of 6 months for patients receiving DES.

The Third Universal Definition of Myocardial Infarction was published
simultaneously with the STEMI guidance. This guideline endorses

  • cardiac troponin as the biomarker of choice to detect myocardial necrosis
  • with spontaneously occurring myocardial infarction (MI) defined as an
  • elevation above the 99th percentile upper reference value for the assay.

There is further development and clarification of MI in different settings

  • to allow standardization across trials and registries

in particular after revascularization procedures: after CABG with normal baseline troponin

  • MI is defined as a rise to a value 10 times greater than baseline in the first 48 h, and
  • a rise to 5 times greater than 99th percentile upper reference after PCI

in patients with a normal baseline level (or a 20% rise when troponin is elevated and stable or falling pre-procedure).

ACCF/AHA  updated guidance on the management of unstable angina/non-STEMI:

angiography with a view to revascularization

  • is now recommended within 12–24 h of presentation, with
  • DAPT pre-loading prior to PCI procedures also now advocated.

Ticagrelor and prasugrel are cited as acceptable alternatives to clopidogrel.
The maintenance dose of aspirin recommended for the majority of cases is 81 mg daily.
This guideline brings about transatlantic agreement in most areas.

Risk Stratification

Identification and appropriate triage of patients presenting to emergency departments
with acute chest pain remains a difficult dilemma:

  • many are low-risk and have a non-cardiac origin
  • a significant minority with coronary artery disease may not be picked up
    on clinical grounds even when accompanied by appropriate tests,

    • including ECG and biomarker estimation used in conjunction
    • with a clinical risk score (e.g. GRACE, TIMI).

As endorsed in ESC guidance, there has been increasing interest in

  • non-typical ECG patterns for the diagnosis of STEMI; although LBBB is
  • an accepted surrogate

Widimsky et al.  retrospectively analysed 6742 patients admitted to hospital with acute MI

  • in patients presenting with right bundle branch block, a blocked epicardial vessel was
  • more common (51.7 vs. 39.4%; P < 0.001) and incidence of both shock and mortality
  • comparable with LBBB (14.3 vs. 13.1%; P = NS; and 15.8 vs. 15.4%; P = NS, respectively).

Wong et al. demonstrated the importance of ST-elevation in lead aVR,

  • often viewed as indicative of left main stem occlusion, having increased mortality
  • in patients presenting with both inferior and anterior infarction.

Perhaps the most important data regarding the ECG in 2012 were also the most simple:

  • Antoni et al. highlighted a powerful and very simple method of risk stratification;
  •  heart rate measured on a 12-lead ECG at discharge after Primary PCI (PPCI) is an
  • independent predictor of mortality at 1 and 4 years of follow-up.

Patients with a discharge heart rate of ≥70 b.p.m. had a two-fold higher mortality at both follow-up
time points, with every increase of 5 b.p.m. in heart rate

  • equating to a 29% increase in mortality at 1 year and 24% at 5 years.

These findings have important implications for the optimization of patient therapies after MI (including the use of
rate-limiting agents such as beta-blockers, calcium channel-blockers, and ivabradine), although large randomized
trials are needed to confirm that

  • interventions to reduce heart rate will replicate the benefits observed in this study.

http://img.medscape.com/article/779/039/779039-thumb1.png

Figure 1.  Kaplan–Meier time-to-event plots for heart rate at discharge divided by quartiles and all-cause mortality
(A and C) and cardiovascular mortality (B and D) at 1-year (A and B) and 4-year (C and D) follow-up,
demonstrating relationship between discharge heart rate and mortality after PPCI for STEMI.
Modified from Antoni et al.

Coronary Intervention and Cardioprotection in Acute Coronary Syndromes

Microvascular obstruction during PCI for ACS/STEMI is associated with increased infarct size and adverse prognosis;
its pathophysiology is thought to be a combination of

  • mechanical distal embolization of thrombus and plaque constituents during PCI,  coupled with
  • enhanced constriction/hyperreactivity of the distal vascular bed.

The most novel Strategy to Reduce Infarct Size

is the use of a Bare Metal Stent (BMS) covered on its outer surface with a mesh micronet designed to
trap and hold potentially friable material that might embolize distally at the time of PCI.

The MASTER study randomized 433 STEMI patients to PPCI

  • with conventional BMS or DES at the operator’s discretion vs.
  • the novel MGuard stent (InspireMD, Tel Aviv, Israel);

the primary endpoint of complete ST-segment resolution was better

  • in patients receiving MGuard (57.85 vs. 44.7%; P = 0.008), as was
  • the achievement of TIMI grade 3 flow in the treated vessel (91.7 vs. 82.9%; P = 0.006).

Nevertheless, median ST-segment resolution did not differ

  • between treatment groups,
  • myocardial blush grade was no different, and
  • safety outcomes at 30 days (death, adverse events) as well as
  • overall MRI-determined infarct mass.

Higher TVR rates may accrue with a BMS platform when compared with

  • current-generation DES (as now endorsed for PPCI in ESC guidance).

In comparing the four studies in cardioprotection, there remains little to choose between strategies as evidenced by

  • the relatively minor differences between surrogate endpoints employed regardless of
  • therapeutic intervention chosen (Figure 2).

http://img.medscape.com/article/779/039/779039-fig2.jpg

Figure 2.  Comparison of study endpoints for reduction in infarct size in STEMI.
Study endpoints listed on the x-axis. STR, ST-segment resolution; TIMI 3, thrombolysis in
myocardial infarction grade 3 antegrade flow; myocardial blush grade 2/3 (MBG 2/3).

Recent advances in

  • PCI equipment,
  • peri-procedural pharmacology,
  • technique, and safety, as well as
  • convergence of national guidance,

are leading to the point where

  • even in the highest risk patients such as those presenting with ACS, small improvements
  • may be difficult to discern despite large well-designed and -conducted studies.

References

  1. a. The Task Force on the management of ST-segment elevation acute myocardial infarction
    of the European Society of Cardiology. ESC guidelines for the management of acute
    myocardial infarction in patients presenting with ST-segment elevation. Eur Heart J
    2012;33:2569–2619.  b. Management of acute myocardial infarction in patients presenting
    with ST-segment elevation. The Task Force on the Management of Acute Myocardial
    Infarction of the European Society of Cardiology.  Eur Heart J 2003; 24 (1): 28-66.
    http://dx.doi.org/10.1093/eurheartj/ehs215
  2. ESC Guidelines for the management of acute coronary syndromes in patients presenting
    without persistent ST-segment elevation: The Task Force for the management of acute
    coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation
    of the European Society of Cardiology (ESC).  http://dx.doi.org/10.1093/eurheartj/ehr236
  3. Thygesen K, Alpert JS, Jaffe AS, Simoons ML, Chaitman BS, White HD. The Writing Group on
    behalf of the Joint ESC/ACCF/AHA/WHF Task Force for the Universal Definition of
    Myocardial Infarction. Third universal definition of myocardial infarction.
    Eur Heart J 2012;33:2551–2567.  http://dx.doi.org/10.1093/eurheartj/ehm355
  4. Kalesan B, Pilgrim T, Heinimann K, Raber L, Stefanini GG, et al. Comparison of drug-eluting
    stents with bare metal stents in patients with ST-segment elevation myocardial infarction.
    Eur Heart 2012;33:977–987.
  5. Jneid H, Anderson JL, Wright RS, Adams CS, et al. 2012 ACCF/AHA Focused Update of the
    Guideline for the Management of Patients with Unstable Angina/Non-ST-Elevation Myocardial
    Infraction (Updating the 2007 Guideline and Replacing the 2011 Focused Update). A Report
    of the American College of CardiologyFoundation/American Heart Association Task Force
    on Practice Guidelines. J Am Coll Cardiol 2012;60:645–681.
  6. Widimsky P, Rohác F, Stásek J, Kala P, Rokyta R, et al. Primary angioplasty in acute myocardial
    infarction with right bundle branch block: should new onset right bundle branch block be added
    to future guidelines as an indication for reperfusion therapy? Eur HeartJ 2012;33:86–95.
  7. Wong CK, Gao W, Stewart RA, French JK, and the HERO-2 Investigators. The prognostic meaning of
    the full spectrum of aVR ST-segment changes in acute myocardial infarction.
    Eur Heart J 2012;33:384–392.
  8. Antoni L, Boden H, Delgado V, Boersma E, et al. Relationship between discharge heart rate and mortality
    in patients after myocardial infarction treated with primary percutaneous coronary intervention.
    Eur Heart J 2012;33:96–102.
  9. Stone GW, Abizaid A, Silber S, Dizon JM, Merkely B, et al. Prospective, randomised, multicenter evaluation
    of a polyethylene terephthalate micronet mesh-covered stent (MGuard) in ST-segment elevation myocardial
    infarction. The MASTER Trial. J Am Coll Cardiol. doi:pii:S0735-1097(12)04506-8. 10.1016/j.jacc.2012.09.004. 
  10. Zhou C, Yao Y, Zheng Z, Gong J, Wang W, Hu S, Li L. Stenting technique, gender, and age are associated with
    cardioprotection by ischaemic postconditioning in primary coronary intervention: a systematic review of
    10 randomized trials. Eur Heart J 2012;33:3070–3077.

Resistant Hypertension.

Robert M. Carey.
Hypertension. 2013;61:746-750.  http://dx.doi.org/10.1161/HYPERTENSIONAHA.111.00601

Resistant hypertension is defined as failure to achieve goal blood pressure (BP) <140/90 mm Hg
(or <130/80 mm Hg in patients with diabetes mellitus or chronic kidney disease) in patients with

  • hypertension who are compliant with maximum tolerated doses of an appropriate antihypertensive drug regimen consisting of a minimum of 3 agents of different classes, including a diuretic.
  • Patients who meet the criteria for resistant hypertension but whose BP can be controlled on maximum tolerated
    doses of ≥4 antihypertensive agents are classified as having controlled resistant hypertension.

Although the number of failed antihypertensive drugs required for the classification of resistant hypertension is arbitrary,

  • this diagnosis identifies patients at high risk for having a potentially curable form of hypertension, and
  • those who may benefit from specific therapeutic approaches to lower BP.

Summary

The first portion of this document shows the impact that ER Edelman and his peers have had in the development
of interventional cardiology, and in carrying out studies to test, validate, or reject assumptions about the interaction of
biomaterials with

  • vascular and smooth muscle tissue in the repair of injured vessels, by
  1. trauma
  2. inflammatory injury
  3. stent placement.

In the second portion of this discussion, I introduce current views about complications in implanted devices, evolving
standards, and the current definitions of stable, unstable, and previously unclassified ACS risk.

Pushing Drug-Eluting Stents Into Uncharted Territory

Simpler Than You Think—More Complex Than You Imagine

Campbell Rogers, MD; Elazer R. Edelman, MD, PhD.  Circulation 2006; 113: 2262-2265.
http://dx.doi.org/10.1161/​CIRCULATIONAHA.106.623470

Mechanical failure is a characteristic of a material or a device and not necessarily an indication of inadequacy. All devices
will fail under some specific stress. It is only failure at the lowest levels of stress that may represent inadequacy. Stress on
a material, for example, rises with strain until a critical load is exceeded, at which point the material fatigues and loses
mechanical integrity. Failure analysis, the science by which these conditions are rigorously defined, is an important
component of device design, development, and use. Once the transition point to failure is identified, material use can be
restricted to the zone of safety or modified so as to have this zone expanded. Just as the characterization of a material is
incomplete unless pushed to the limits of load bearing, characterization of an implantable device is incomplete unlesspreclinical and clinical environments test the limits of device functionality. It was in this light in 1999 that the Authors noted the impossibility of defining the functional limits of novel bare metal stents in head-to-head trials, which, by necessity, could only include lesions into which the predicate device (the Palmaz-Schatz stent, Cordis, Warren, NJ) could have be placed.

New School Percutaneous Interventions

Over the past 5 years, the number of percutaneous interventions has grown by 40%. This expansion derives from an
increased breadth of cases, as percutaneous interventions are now routinely performed in diabetic, small-vessel, multilesion,diffuse disease, and acute coronary syndrome settings. Contemporaneously, widespread adoption of drug-eluting stents has emboldened clinicians and provided greater security in the use of these devices in lesions or patients previously thought to

Head-to-head randomized trial data have accumulated so that analysis may demonstrate differences among drug-eluting stents. The playing field for prospective randomized trials could enhance the weight of evidence to unanswered questions about what underlying factors determine device failure.

Complexity Simplified

Drug-eluting stent “failure” can be defined operationally in the same way as material failure:

  • inadequate function in the setting of a given load or strain.

The inability to withstand stress may take many forms that can change over time. Failure may be manifest acutely as

  • the inability to deliver a stent to the desired location,
  • subacutely as stent thrombosis or
  • postprocedural myonecrosis, and later as
  • restenosis

“Simple lesions” are those in which few devices should fail;“Complex” lesions have a heightened risk of failure. To be of value, each scale of advancing complexity must provoke higher failure rates.  For any device may fail sooner than another along one such “complexity” scale and later along another. As advanced drug-eluting stent designs have enhanced deliverability and reduced restenosis rates, 7 randomized trials comparing directly the two Food and Drug Administration (FDA)-approved drug-eluting stents, Cypher (Cordis-Johnson and Johnson) and Taxus (Boston Scientific, Boston, Mass), have been reported.  These trials report a broad range of restenotic failure as evidenced by the need for revascularization. Across these trials, driven by a variety of factors, revascularization rates vary quite widely.

The clinical end point of target lesion revascularization (TLR) becomes

  • a single measure of device failure.

When the 7 trials are depicted in order of increasing TLR, the rate of failure increases more slowly with 1 device than
the other.  This gives two regression plots for Taxus vs Cypher with different slopes, as complexity increases, and the

  • separation between the failure rates of the two devices broadens plotted against “degree of complexity” assigned by the  slopes of the lines.

Finally, the correlation between TLR rates for Taxus and Cypher stents indicates that trial-specific events and conditions determined TLR (with a sharp slope of Taxus vs Cypher (r-sq = 0.85).  The ratio of TLR (the slope) wasgreater than 3, suggesting that although both devices are subject to increasing failure as complexity increases,

  • one device becomes ever-more likely than the other to fail when applied in settings with ever-higher TLR risk.

In other words, composite medical devices with a wide range of

  • structural,
  • geometric, and
  • pharmacological differences
    • can be shown to produce different clinical effects
    • as the environments in which they are tested become increasingly complex.

What the Individual Trials Cannot Tell Us

The progressive difference between the performances of the 2 FDA-approved drug-eluting stents as they are pushed into
more complex settings is precisely what one would anticipate from medical devices with different performance signatures.
Most randomized trials, even if they include high complexity, are unable to identify predictors of failure because of the low numbers of patients enrolled, and the problem gets worse as the number of subsets increase. Consequently, device development, and clinical practice, knowing which patient or lesion characteristics confer higher failure rates is critical.
This analysis has centered on restenosis. Other failure modes to be considered are

  • stent thrombosis,
  • postprocedural myonecrosis
  • late plaque rupture
  • vascular disease away from the site
  • heightened inflammatory reaction
    • are no less critical and may be determined by
    • completely different device or patient characteristics.

Well-executed registry or pooled data

It is in this light that the registry report of Kastrati et al. in the current issue of Circulation is of greatest value. There are
two ways in which well-executed registry or pooled data can be most complementary to randomized trials.

First, large numbers of patients provide a higher incidence of rare failure modes as well as allow more granular determination of lesion- or patient-specific predictors of failure (meta-analysis or better, combined data file). A pooled analysis of several head-to-head randomized bare metal stent trials allowed identification of clear risk factors for stent thrombosis that had eluded analysis of the individual (smaller) trials.

Second, registry or pooled data may incorporate a broader range of patient characteristics, allowing greater discrimination between devices. The report of Kastrati et al may fall into this category as well, as it includes “high risk” populations from several randomized trials. They report on more than 2000 lesions in 1845 patients treated with either Taxus or Cypher drug-eluting stents at two hospitals.  The study population is from a series of randomized trials comparing Taxus and Cypher stents.   Using multivariate analysis to identify what lesion and patient characteristics predict failure (restenosis), they identified risk factors that included

  • prior history of coronary bypass surgery
  • calcification
  • smaller vessel size
  • greater degree of prestent and poststent stenosis.

Use of a Cypher rather than Taxus stent was independently associated with lower restenosis risk.

An interesting negative finding was the absence of diabetes as a significant predictor, at odds with strong suggestions from several other analyses. A better understanding from preclinical or clinical studies of the effect of diabetic states on restenosis is critical.

Author’s opinion voiced:

This Author (LHB), considers the study underpowered to answer that question because of further partitioning with several variables. Pooled data with

  • rigorous ascertainment and
  • careful statistical methodology, taken
  • together with randomized trial data, open a door to device choice based on the knowledge that risk of failure (complexity) does vary, and
  • the higher the complexity, the greater the incremental benefit of choosing one device over another.

A decision algorithm is therefore possible, whereby multiple failure modes and risk factors are weighed, and

  • an optimum stent choice made which balances
  • safety and efficacy based on the totality of evidence, rather than anecdote and loose comparisons of disparate subgroups from individual trials.

Evaluating Clinical Trials

The subject of trial(s) is difficult… the aim and meaning of all the trials… is

  • to let people know what they ought to do or what they must believe

It was perhaps naïve to imagine that devices as different one from another as the two current FDA-approved drug-eluting
stents would produce identical clinical results. If so, it ought not to come as a surprise that head-to-head randomized trial
data from many different countries in complex settings are now indicating just how differently the 2 devices may perform.

Future trials should be designed and evaluated to examine why these differences exist. Trials residing
only in previous safety and complexity domains

  • are unlikely to offer deeper insights into
    1. device performance,
    2. patient care decisions, or
    3. discrimination of alternative therapies.

We look forward to more trials that will examine what we currently believe to be the limits of

  • drug-eluting stents and interventional cardiology and to

help define in simple terms differences

  • between complex devices applied to complex problems.

This 2009 article was an excellent demonstration of comparing two commonly used coated-stents, and then extending the argument to the need for more data to further delineated the factors that explain the differences they found. In the previous article, the SECOND in the three article series,  Stents and Drug Delivery

Vascular Repair: Stents and Biologically Active Implants

we concentrated on stents and drug delivery, and not on stent failure.  But the following article in J Control Release,

was published the following year, and is another example of this method of explanatory approach to the problem.

Lesion Complexity Determines Arterial Drug Distribution After Local Drug Delivery

AR Tzafriri,  N Vukmirovic, VB Kolachalama, I Astafieva, ER Edelman. J Control Release. 2010; 142(3): 332–338.
http://:dx. doi:.org/10.1016/j.jconrel.2009.11.007       PMCID: PMC2994187

Local drug delivery from endovascular stents has transformed how we treat coronary artery disease. Yet, few drugs are in fact effective when delivered from endovascular implants and those that possess a narrow therapeutic window. The width of this window is predicated to a great degree upon the extent of drug deposition and distribution through the arterial wall.

  • Drugs that are retained within the blood vessel are far more effective than those that are not.

Thus, for example, heparin regulates virtually every aspect of the vascular response to injury, but it is so soluble and diffusible that it simply cannot stay in the artery for more than minutes after release.

  • Heparin has no effect on intimal hyperplasia when eluted from a stent.
  • Paclitaxel and sirolimus in contradistinction are far smaller compounds with perhaps more narrow and specific effects than heparin.

These drugs bind tenaciously to tissue protein elements and specific intracellular targets and remain beneath stent struts long after release.

The clinical efficacy of paclitaxel and sirolimus at reducing coronary artery restenosis rates following elution from stents appears incontrovertible. Emerging clinical and preclinical data suggest that the benefit of the local release of these drugs is beset by significant complications, that rise with lesion complexity as

  • the native composition and layered ultrastructure of the native artery is more significantly disrupted.

Virmani and others have hypothesized that the attraction of lipophilic drugs like paclitaxel and sirolimus to fat should affect their retention within and effects upon atheromatous lesions.

Though stents are deployed in diseased arteries drug distribution has only been quantified in intact, non-diseased vessels.

Authors @ MIT, correlated steady-state arterial drug distribution with tissue ultrastructure and composition in abdominal aortae from atherosclerotic human autopsy specimens and rabbits

  • with lesions induced by dietary manipulation and controlled injury.

Drug and compositional metrics were quantified and correlated at a compartmental level, in each of the tunica layers, or at an intra-compartmental level. All images were processed to

  • eliminate backgrounds and artifacts, and
  • pixel values between thresholds were extracted for all zones of interest.

Specific algorithms analyzed each of the histo/immuno-stained arterial structures. Intra-compartmental analyses were

  • performed by sub-dividing arterial cross-sections into 2–64 equal sectors and
  • evaluating the pixel-average luminosity for each sector.

Linear regression of drug versus compositional luminosities asymptotically approached steady state after subdivision into 16 sectors. This system controlled delivered dose and removed the significant unpredictability in release that is imposed by variability

  • in stent position relative to the arterial wall,
  • inflation techniques and stent geometry.
As steady state tissue distribution results were obtained under constant source conditions, without washout by flowing blood,
  • they constitute upper bounds for arterial drug distribution
  • following transient modes of in vivo drug delivery wherein
  • only a fraction of the eluted dose is absorbed by the artery

Paclitaxel, everolimus, and sirolimus deposition in human aortae was maximal in the media and scaled inversely with lipid content.

Net tissue paclitaxel and everolimus levels were indistinguishable in mildly injured rabbit arteries independent of diet. Yet, serial sectioning of cryopreserved arterial segments demonstrated

  • a differential transmural deposition pattern that was amplified with disease and
  • correlated with expression of their intracellular targets, tubulin and FKBP-12.

Tubulin distribution and paclitaxel binding increased with

  • vascular injury and macrophage infiltration, and
  • were reduced with (reduced) lipid content.

Sirolimus analogues and their specific binding target FKBP-12 were less sensitive to alterations of diet
in mildly injured arteries, presumably reflecting a faster transient response of FKBP-12 to injury.

The idea that drug deposition after balloon inflation and stent implantation within diseased, atheromatous and sclerotic vessels tracks so precisely with specific tissue elements is

  • an important consideration of drug-eluting technologies and
  • may well require that we consider diseased rather than naïve tissues in preclinical evaluations.

Another publication in the same year reveals the immense analytical power used in understanding the complexities
of drug-eluting stents.

Luminal Flow Amplifies Stent-Based Drug Deposition in Arterial Bifurcations

Kolachalama VB, Levine EG, Edelman ER.    PLoS ONE 2009; 4(12): e8105.
 http://dx.doi.org/10.1371/journal.pone.0008105

Treatment of arterial bifurcation lesions using drug-eluting stents (DES) is now common clinical practice.
Arterial drug distribution patterns become challenging to analyze if the lesion involves more than a vessel
such as in the case of bifurcations.  As use extends to nonstraightforward lesions and complex geometries,
questions abound

  • regarding DES longevity and safety

Indeed, there is no consensus on best stent placement scenario, no understanding as to

  • whether DES will behave in bifurcations as they do in straight segments, and
  • whether drug from a main-branch (MB) stent can be deposited within a side-branch (SB).

It is not evident how to

  • efficiently determine the efficacy of local drug delivery and
  • quantify zones of excessive drug that are
  • harbingers of vascular toxicity and thrombosis,
  • and areas of depletion that are associated
  • with tissue overgrowth and
  • luminal re-narrowing.

Geometry modeling and governing equations

Authors @MIT constructed two-phase computational models of stent-deployed arterial bifurcations

  • simulating blood flow and drug transport to investigate the
  • factors modulating drug distribution when the main-branch (MB) was treated using a DES.

The framework for constructing physiologically realistic three dimensional computational models of single
and bifurcated arterial vessels was SolidWorks (Dassault Systemes) (Figs. 1A–1B, Movie S1). The geometry
generation algorithm allowed for controlled alteration of several parameters including

  • stent location
  • strut dimensions
  • stent-cell shape
  • lumen diameter to arterial tissue thickness ratio
  • lengths of the arterial branches
  • extent of stent apposition and
  • the bifurcation angle.

For the current study, equal lengths (2LS) were assumed for the proximal and distal sections of the MB from the bifurcation. The SB was constructed at an angle of 300. The inlet conditions were based on

  • mean blood flow and
  • diameter measurements

obtained from human left anterior descending coronary artery (LAD).

The diameter of the lumen (DMB) and thickness (TMB) for the MB were defined such that DMB=TMB~10 and

  • this ratio was also maintained for the SB.

Schematics of the computational models used for the study. A stent of length LS is placed at the upstream section of the arterial vessel in the (A) absence and in the (B) presence of a bifurcation, respectively.

  • Insets in (B) denote delta wing stent design (i),
  • strut thickness (d) (ii), and
  • the outlets of the side-branch in (iii) and
  • and the main-branch in (iv).

A delta wing-shaped cell design belonging to the class of slotted-tube stents was used for all simulations.
The length (LS) and diameter (DS) were

  • fixed at 9|10-2 m and 3|10-2 m, respectively, for the MB stent.

All stents were assumed to be perfectly apposed to the lumen of MB and the intrinsic strut shape was modeled as

  • square with length 10-4 m.

The continuity and momentum equations were solved within the arterial lumen, where

vf , rho~1060 kg=m3, P and m are

  • velocity
  • density
  • pressure and the
  • viscosity of blood.

In order to capture boundary layer effects at the lumen-wall (or mural) surface, a Carreau model was employed for

  • all the simulations to account for shear thinning behavior of blood at low shear rates

In the arterial lumen, drug transport followed advection-diffusion process.  Similar to the momentum transport in the arterial lumen, the continuity equation was solved within the arterial wall by assuming it as a porous medium.

A finite volume solver (Fluent, ANSYS Inc.) was utilized to perform the coupled flow and drug transport simulations. The semi-implicit method for pressure-linked equations-consistent (SIMPLEC) algorithm was used with second order spatial accuracy. A second order discretization scheme was used to solve the pressure equation and second order  upwind schemes were used for the momentum and concentration variables.

Simulations for each case were performed

  • for at least 2500 iterations or
  • until there was a 1028 reduction in the mass transport residual.

Drug distribution in non-bifurcating vessels

Constant flow simulations generate local recirculation zones juxtaposed to the stent which in turn act as

  • secondary sources of drug deposition and
  • induce an asymmetric tissue drug distribution profile in the longitudinal flow direction.

Our3D computational model predicts a far more extensive fluid mechanic effect on drug deposition than previously appreciated in two-dimensional (2D) domains.

Within the stented region, drug deposition on the mural interface quantified as

  • the area-weighted average drug concentration (AWAC)
  • in the distal segment of the stent is 12% higher than the proximal segment

Total drug uptake in the arterial wall denote as volume-weighted average concentration (VWAC) is highest in the middle segment of the stent and 5% higher than the proximal stent region

Increased mural drug deposition along the flow direction in a non-bifurcating arterial vessel.

Inset shows a high magnification image of drug pattern in the distal stent segment outlined by black dashed line.
The entire stent is divided into three equal sections denoted as proximal, middle and distal sections, respectively
and the same notation is followed for subsequent analyses.

http://dx.doi.org/10.1371/journal.pone.0008105.g002

These observations indicate that the flow-mediated effect induced by the presence of the stent in the artery

  • is maximal on the mural surface and
  • increases in the longitudinal flow direction.

Further, these results suggest that transmural diffusion-mediated transport sequesters drug from both

  • the proximal and distal portions of the stent
  • into the central segment of the arterial wall beneath the stent.

Predicted levels of average drug concentration varied exponentially

  • with linear increments of inlet flow rate

but maintained similar relationship between the inter-segment concentration levels within the stented region.

Stent position influences drug distribution in bifurcated beds

The location of the stent directly modulates

  • the extent to which drug is deposited on the arterial wall as well as
  • spatial gradients that are established in arterial drug distribution.

Similar to the non-bifurcating vessel case,

  • peaks in drug deposition occur directly beneath the stent struts regardless of the relative location of the SB with respect to the stent. However,
  • drug distribution and corresponding spatial heterogeneity within inter-strut regions depend on the stent location with respect to the flow divider.
  • Mural drug deposition is a function of relative stent position with respect to the side-branch and Reynolds number in arterial bifurcations.

Impact of flow on drug distribution in bifurcations

One can appreciate how blood flow and flow dividers affect arterial drug deposition, and especially on inter-strut drug deposition.

  • Drug deposition within the stented-region of MB  and the entire SB significantly decreases with flow acceleration regardless of stent placement.

Simulations predicted

Local endovascular drug delivery was long assumed to be governed by diffusion alone. The impact of flow was
thought to be restricted to systemic dilution.

  • 2D computational models suggested a complex interplay between the stent and blood flow
  1. Arterial drug deposition is a function of stent location.   http://dx.doi.org/10.1371/journal.pone.0008105.g005
  2. Arterial drug deposition is mediated by flow in bifurcated beds.
    http://dx.doi.org/10.1371/journal.pone.0008105.g006
  • extensive flow-mediated drug delivery in bifurcated vascular beds where the drug distribution patterns are heterogeneous and sensitive to relative stent position and luminal flow.

A single DES in the MB coupled with large retrograde luminal flow on the lateral wall of the side-branch (SB) can provide drug deposition on the SB lumen-wall interface, except

  • when the MB stent is downstream of the SB flow divider.
  • the presence of the SB affects drug distribution in the stented MB.

Fluid mechanic effects play an even greater role than in the SB

  • especially when the DES is across and downstream to the flow divider
  • and in a manner dependent upon

    the Reynolds number.

Summary

We presented the hemodynamic effects on drug distribution patterns using a

  • simplified uniform-cell stent design, though our methodology is adaptable to
    several types of stents with variable design features.

Variability in arterial drug distribution due to other geometric and morphologic aspects such as

  • bifurcation angle, arterial taper as well as presence of a trifurcation can also be understood using our computational framework.

Further, performance of a candidate DES using other commonly used stenting procedures for bifurcation lesions such as culotte and crush techniques can be quantified based on their resulting drug distribution patterns.

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http://pharmaceuticalintelligence.com/2012/10/30/cardiovascular-risk-inflammatory-marker-risk-assessment-for-coronary-heart-disease-and-ischemic-stroke-atherosclerosis/

To Stent or Not? A Critical Decision

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New Definition of MI Unveiled, Fractional Flow Reserve (FFR)CT for Tagging Ischemia

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http://pharmaceuticalintelligence.com/2012/08/27/new-definition-of-mi-unveiled-fractional-flow-reserve-ffrct-for-tagging-ischemia/

Ethical Considerations in Studying Drug Safety — The Institute of Medicine Report

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http://pharmaceuticalintelligence.com/2012/08/23/ethical-considerations-in-studying-drug-safety-the-institute-of-medicine-report/

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http://pharmaceuticalintelligence.com/2012/08/22/new-drug-eluting-stent-works-well-in-stemi/

Expected New Trends in Cardiology and Cardiovascular Medical Devices

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http://pharmaceuticalintelligence.com/2012/08/17/expected-new-trends-in-cardiology-and-cardiovascular-medical-devices/

Coronary Artery Disease – Medical Devices Solutions: From First-In-Man Stent Implantation, via Medical Ethical Dilemmas to Drug Eluting Stents

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http://pharmaceuticalintelligence.com/2012/08/13/coronary-artery-disease-medical-devices-solutions-from-first-in-man-stent-implantation-via-medical-ethical-dilemmas-to-drug-eluting-stents/

Percutaneous Endocardial Ablation of Scar-Related Ventricular Tachycardia

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http://pharmaceuticalintelligence.com/2012/07/18/percutaneous-endocardial-ablation-of-scar-related-ventricular-tachycardia/

Competition in the Ecosystem of Medical Devices in Cardiac and Vascular Repair: Heart Valves, Stents, Catheterization Tools and Kits for Open Heart and Minimally Invasive Surgery (MIS)

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Clinical Decision Support Systems for Management Decision Making of Cardiovascular Diseases

Author, and Content Consultant to e-SERIES A: Cardiovascular Diseases: Justin Pearlman, MD, PhD, FACC

and

Curator: Aviva Lev-Ari, PhD, RN

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Clinical Decision Support Systems (CDSS)

Clinical decision support system (CDSS) is an interactive decision support system (DSS). It generally relies on computer software designed to assist physicians and other health professionals with decision-making tasks, such as when to apply a particular diagnosis, further specific tests or treatments. A functional definition proposed by Robert Hayward of the Centre for Health Evidence defines CDSS as follows:  “Clinical Decision Support systems link health observations with health knowledge to influence health choices by clinicians for improved health care”. CDSS is a major topic in artificial intelligence in medicine.

Vinod Khosla of A Khosla Ventures investment, in a Fortune Magazine article, “Technology will replace 80% of what doctors do”, on December 4, 2012, wrote about CDSS as a harbinger of science in medicine.

Computer-assisted decision support is in its infancy, but we have already begun to see meaningful impact on healthcare. Meaningful use of computer systems is now rewarded under the Affordable Care Act.  Studies have demonstrated the ability of computerized clinical decision support systems to lower diagnostic errors of omission significantly, by directly countering cognitive bias.  Isabel is a differential diagnosis tool and, according to a Stony Book study, matched the diagnoses of experienced clinicians in 74% of complex cases. The system improved to a 95% match after a more rigorous entry of patient data. The IBM supercomputer, Watson, after beating all humans at the intelligence-based task of playing Jeopardy, is now turning its attention to medical diagnosis. It can process natural language questions and is fast at parsing high volumes of medical information, reading and understanding 200 million pages of text in 3 seconds. 

Examples of CDSS

  1. CADUCEUS
  2. DiagnosisPro
  3. Dxplain
  4. MYCIN
  5. RODIA

VIEW VIDEO

“When Should a Physician Deviate from the Diagnostic Decision Support Tool and What Are the Associated Risks?”

Introduction

Justin D. Pearlman, MD, PhD

A Decision Support System consists of one or more tools to help achieve good decisions. For example, decisions that can benefit from DSS include whether or not to undergo surgery, whether or not to undergo a stress test first, whether or not to have an annual mammogram starting at a particular age, or a computed tomography (CT) to screen for lung cancer, whether or not to utilize intensive care support such as a ventilator, chest shocks, chest compressions, forced feeding, strong antibiotics and so on versus care directed to comfort measures only without regard to longevity.

Any DSS can be viewed like a digestive tract, chewing on input, and producing output, and like the digestive tract, the output may only be valuable to a farmer. A well designed DSS is efficient in the input, timely in its processing and useful in the output. Mathematically, a DSS is a model with input parameters and an output variable or set of variables that can be used to determine an action. The input can be categorical (alive, dead), semi-quantitative (cold-warm-hot), or quantitative (temperature, systolic blood pressure, heart rate, oxygen saturation). The output can be binary (yes-no) or it can express probabilities or confidence intervals.

The process of defining specifications for a function and then deriving a useful function is called mathematical modeling. We will derive the function for “average” as an example. By way of specifications, we want to take a list of numbers as input, and come out with a single number that represents the middle of the pack or “central tendency.”   The order of the list should not matter, and if we change scales, the output should scale the same way. For example, if we use centimeters instead of inches, and we apply 2.54 centimeters to an inch, then the output should increase by the multiplier 2.54. If the list of numbers are all the same then the output should be the consistent value. Representing these specifications symbolically:

1. order doesn’t matter: f(a,b) = f(b,a), where “a” and “b” are input values, “f” is the function.

2. multipliers pass through (linearity):  f(ka,kb)=k f(a,b), where k is a scalar e.g. 2.54 cm/inch.

3. identity:  f(a,a,a,…) = a

Properties 1 and 2 lead us to consider linear functions consisting of sums and multipliers: f(a,b,c)=Aa+Bb+Cc …, where the capital letters are multipliers by “constants” – numbers that are independent of the list values a,b,c, and since the order should not matter, we simplify to f(a,b,c)=K (a+b+c+…) because a constant multiplier K makes order not matter. Property 3 forces us to pick K = 1/N where N is the length of the list. These properties lead us to the mathematical solution: average = sum of list of numbers divided by the length of the list.

A coin flip is a simple DSS: heads I do it, tails I don’t. The challenge of a good DSS is to perform better than random choice and also perform better (more accurately, more efficiently, more reliably, more timely and/or under more adverse conditions) than unassisted human decision making.

Therefore, I propose the following guiding principles for DSS design: choose inputs wisely (accessible, timely, efficient, relevant), determine to what you want output to be sensitive AND to what you want output to be insensitive, and be very clear about your measures of success.

For example, consider designing a DSS to determine whether a patient should receive the full range of support capabilities of an intensive care unit (ICU), or not. Politicians have cited the large bump in the cost of the last year of life as an opportunity to reduce costs of healthcare, and now pay primary care doctors to encourage patients to establish advanced directives not to use ICU services. From the DSS standpoint, the reasoning is flawed because the decision not to use ICU services should be sensitive to benefit as well as cost, commonly called cost-benefit analysis. If we measure success of ICU services by the benefit of quality life net gain (QLNG, “quailing”), measured in quality life-years (QuaLYs) and achieve 50% success with that, then the cost per QuaLY measures the cost-benefit of ICU services. In various cost-benefit decisions, the US Congress has decided to proceed if the cost is under $20-$100,000/QuaLY. If ICU services are achieving such a cost-benefit, then it is not logical to summarily block such services in advance. Rather, the ways to reduce those costs include improving the cost efficiency of ICU care, and improving the decision-making of who will benefit.

An example of a DSS is the prediction of plane failure from a thousand measurements of strain and function of various parts of an airplane. The desired output is probability of failure to complete the next flight safely. Cost-Benefit analysis then establishes what threshold or operating point merits grounding the plane for further inspection and preventative maintenance repairs. If a DSS reports probability of failure, then the decision (to ground the plane) needs to establish a threshold at which a certain probability triggers the decision to ground the plane.

The notion of an operating point brings up another important concept in decision support. At first blush, one might think the success of a DSS is determined by its ability to correctly identify a predicted outcome, such as futility of ICU care (when will the end result be no quality life net gain). The flaw in that measure of success is that it depends on prevalence in the study group. As an extreme example, if you study a group of patients with fatal gunshot wounds to the head, none will benefit and the DSS requirement is trivial and any DSS that says no for that group has performed well. At the other extreme, if all patients become healthy, the DSS requirement is also trivial, just say yes. Therefore the proper assessment of a DSS should pay attention to the prevalence and the operating point.

The impact of prevalence and operating point on decision-making is addressed by receiver-operator curves. Consider looking at the blood concentration of Troponin-I (TnI) as the sole determinant to decide who is having a heart attack.  If one plots a graph with horizontal axis troponin level and vertical axis ultimate proof of heart attack, the percentage of hits will generally be higher for higher values of TnI. To create such a graph, we compute a “truth table” which reports whether the test was above or below a decision threshold operating point, and whether or not the disease (heart attack) was in fact present:

TRUTH TABLE

              Disease            Not Disease
Test Positive

TP

FP

Test Negative

FN

TN

Total

TP+FN

FP+TN

The sensitivity to the disease is the true positive rate (TPR), the percentage of all disease cases that are ranked by the decision support as positive: TPR = TP/(TP+FN). 100% sensitivity can be achieved trivially by lowering the threshold for a positive test to zero, at a cost.  While sensitivity is necessary for success it is not sufficient. In addition to wanting sensitivity to disease, we want to avoid labeling non-disease as disease. That is often measured by specificity, the true negative rate (TNR), the percentage of those without disease who are correctly identified as not having disease: TNR = TN/(FP+TN). I propose also we define the complement to specificity, the anti-sensitivity, as the false positive rate (FPR), FPR = FP/(FP+TN) = 1 – TNR. Anti-sensitivity is a penalty cost of lowering the diagnostic threshold to boost sensitivity, as the concomitant rise in anti-sensitivity means a growing number of non-disease subjects are labeled as having disease. We want high sensitivity to true disease without high anti-sensitivity to false disease, and we want to be insensitive to common distractors. In these formulas, note that false negatives (FN) are True for disease, and false positives (FP) are False for disease, so the denominators add FN to TP for total True disease, and add FP to TN for total False for disease.

The graph in figure 1 justifies the definition of anti-sensitivity. It is an ROC or “Receiver-Operator Curve” which is a plot of sensitivity versus anti-sensitivity for different diagnostic thresholds of a test (operating points). Note, higher sensitivity comes at the cost of higher anti-sensitivity. Where to operate (what threshold to use for diagnosis) can be selected according to cost-benefit analysis of sensitivity versus anti-sensitivity (and specificity).

 untitled
FIgure 1 ROC (Receiver-Operator Curve): Graph of sensitivity (true positive rate) versus anti-sensitivity (false positive rate) computed by changing the operating point (threshold for declaring a test numeric value positive for disease). High area under the curve (AUC) is favorable because it means less anti-sensitivity for high sensitivity (upper left corner of shaded area more to the left, and higher). The dots on the curve are operating points. An inclusive operating point (high on the curve, high sensitivity) is used for screening tests, whereas an exclusive operating point (low on the curve, low anti-sensitivity) is used for definitive diagnosis.

Cost benefit analysis generally is based on a semi-lattice, or upside-down branching tree, which represents all choices and outcomes. It is important to include all branches down to final outcomes. For example, if the test is a mammogram to screen for breast cancer, the cost is not just the cost of the test, and the benefit “early diagnosis.” The cost-benefit calculation forces us to put a numerical value on the impact, such as a financial cost to an avoidable death, or we can get a numerical result in terms of quality life years expected. The cost, however, is not just the cost of the mammogram, but also of downstream events such as the cost of the needle biopsies for the suspicious “positives” and so on.

semilattice decision treeFigure 2 Semi-lattice Decision Tree: Starting from all patients, create a branch point for your test result, and add further branch points for any subsequent step-wise outcomes until you reach the “bottom line.” Assign a value to each, resulting in a numerical net cost and net benefit. If tests invoke risks (for example, needle biopsy of lung can collapse a lung and require hospitalization for a chest tube) then insert branch points for whether the complication occurs or not, as the treatment of a complication counts as part of the cost. The intermediary nodes can have probability of occurrence as their numeric factor, and the bottom line can apply the net probability of the path leading to a value as a multiplier to the dollar value (a 10% chance of costing $10,000 counts as an expectation cost of 0.1 x 10,000 = $1,000).

A third area of discussion is the statistical power of a DSS – how reliable is it in the application that you care about? Commonly DSS design is contrary to common statistical applications which address significance of a deviation in a small number of variables that have been measured many times in a large population. Instead, DSS often uses many variables to fully describe or characterize the status of a small population. For example, thousands of different measurements may be performed on a few dozen airplanes, aiming to predict when the plane should be grounded for repairs. A similar inversion of numbers – numerous variables, small number of cases – is common in genomics studies.

The success of a DDS is measured by its predictive value compared to outcomes or other measures of success. Thus measures of success include positive predictive value, negative predictive value, and confidence. A major problem with DDS is the inversion of the usually desired ratio of repetitions to measurement variables. When you get a single medical lab test, you have a single measurement value such as potassium level and a large number of normal subjects for comparison. If we knew the  mean μ and standard deviation σ that describes the distribution of normal values in the population at large, then we could compute the confidence in the decision to call our observed value abnormal based on the normal distribution:  , <br /><br /><br /><br /><br /><br /><br /><br /><br />
f(x) = \frac{1}{\sigma\sqrt{2\pi}} e^{ -\frac{(x-\mu)^2}{2\sigma^2} }.<br /><br /><br /><br /><br /><br /><br /><br /><br />

A value may be deemed distinctive based on a 95% confidence interval if it falls outside of the norm, say by more than twice the standard deviation σ, thereby establishing that it is unlikely to be random as the distance from the mean excludes 95% of the normal distribution.

The determination of confidence in an observed set of results stems from maximized likelihood estimates. Earlier in this article we described how to derive the the mean, or center, of a set of measurements. A similar analysis can derive the standard deviation (square root of variance) as a measure of spread around the mean, as well as other descriptive statistics based on sample values. These formulas describe the distribution of sample values about the mean. The calculation is based on a simple inversion. If we knew the mean and variance of a population of values for a measurement, we could calculate the likelihood of each new measurement falling a particular distance from the mean, and we could calculate the combined likelihood for a set of observed values. Maximized Likelihood Estimation (MLE) simply inverts the method of calculation. Instead of treating the mean and variance as known, we can treat the sample observations as the known data, to characterize a distribution for the observed data samples from an estimate of the spread about an unknown mean from a set of N normal samples x(one can apply calculus to compute the formulas below for the unknown mean and unknown variance, based simply on computing how to maximize the joint likelihood of the observations  xfrom the frequency distribution above, in order t0 derive the following formulas): 

\sigma = \sqrt{\frac{1}{N}\left[(x_1-\mu)^2 + (x_2-\mu)^2 + \cdots + (x_N - \mu)^2\right]}, {\rm \ \ where\ \ } \mu = \frac{1}{N} (x_1 + \cdots + x_N),

The frequency distribution (a function of mean and spread) reports the frequency of observing x if it is drawn from a population with the specified mean μ and standard deviation σ . We can invert that by treating the observations, x, as known and the mean μ and standard deviation σ unknown, then calculate the values μ and  σ that maximize the likelihood of our sample set as coming from the dynamically described population.

In DSS there is typically an inversion of the usually requisite large number of samples (small versus large) and number of variables (large versus small. This inversion has major consequences on data confidence. If you measure just 14 independent variables versus one variable, each at 95% confidence, the net confidence drops exponentially to less than 50%: 0.9514=49%. In the airplane grounding screen tests, 1000 independent variables, at 95% confidence each, yields a net confidence of only 5 x 10-23 which is 10 sextillion times less than 50% confidence. This same problem arises in genomics research, in which we have a large array of gene product measurements on a small number of patients. Standard statistical tools are problematic at high variable counts. One can turn to qualitative grouping tools such as exploratory factor analysis, or recover statistical robustness with HykGene, a combined cluster and ranking method devised by the author to improve dramatically the ability to identify distinctions with confidence when the number of variables is high.

Evolution of DSS

Aviva Lev-Ari, PhD, RN

The examples provided above refer to sets of binary models, one family of DSS. Another type of DSS is multivariate in nature, a corollary of multivariate scenarios constitute alternative choice options. Last decade development in the DSS field involved the design of Recommendation Engines given manifested preference functions that involved simultaneous trade-off functions against cost function. Game theoretical context is embedded into Recommendation Engines. The output mentioned above, is in fact an array of options with probabilities of saving reward assigned by the Recommendation Engine.

Underlining Computation Engines

Methodological Basis of Clinical DSS

There are many different methodologies that can be used by a CDSS in order to provide support to the health care professional.[7]

The basic components of a CDSS include a dynamic (medical) knowledge base and an inference mechanism (usually a set of rules derived from the experts and evidence-based medicine) and implemented through medical logic modules based on a language such as Arden syntax. It could be based on Expert systems or artificial neural networks or both (connectionist expert systems).

Bayesian Network

The Bayesian network is a knowledge-based graphical representation that shows a set of variables and their probabilistic relationships between diseases and symptoms. They are based on conditional probabilities, the probability of an event given the occurrence of another event, such as the interpretation of diagnostic tests. Bayes’ rule helps us compute the probability of an event with the help of some more readily available information and it consistently processes options as new evidence is presented. In the context of CDSS, the Bayesian network can be used to compute the probabilities of the presence of the possible diseases given their symptoms.

Some of the advantages of Bayesian Network include the knowledge and conclusions of experts in the form of probabilities, assistance in decision making as new information is available and are based on unbiased probabilities that are applicable to many models.

Some of the disadvantages of Bayesian Network include the difficulty to get the probability knowledge for possible diagnosis and not being practical for large complex systems given multiple symptoms. The Bayesian calculations on multiple simultaneous symptoms could be overwhelming for users.

Example of a Bayesian network in the CDSS context is the Iliad system which makes use of Bayesian reasoning to calculate posterior probabilities of possible diagnoses depending on the symptoms provided. The system now covers about 1500 diagnoses based on thousands of findings.

Another example is the DXplain system that uses a modified form of the Bayesian logic. This CDSS produces a list of ranked diagnoses associated with the symptoms.

A third example is SimulConsult, which began in the area of neurogenetics. By the end of 2010 it covered ~2,600 diseases in neurology and genetics, or roughly 25% of known diagnoses. It addresses the core issue of Bayesian systems, that of a scalable way to input data and calculate probabilities, by focusing specialty by specialty and achieving completeness. Such completeness allows the system to calculate the relative probabilities, rather than the person inputting the data. Using the peer-reviewed medical literature as its source, and applying two levels of peer-review to the data entries, SimulConsult can add a disease with less than a total of four hours of clinician time. It is widely used by pediatric neurologists today in the US and in 85 countries around the world.

Neural Network

Artificial Neural Networks (ANN) is a nonknowledge-based adaptive CDSS that uses a form of artificial intelligence, also known as machine learning, that allows the systems to learn from past experiences / examples and recognizes patterns in clinical information. It consists of nodes called neuron and weighted connections that transmit signals between the neurons in a forward or looped fashion. An ANN consists of 3 main layers: Input (data receiver or findings), Output (communicates results or possible diseases) and Hidden (processes data). The system becomes more efficient with known results for large amounts of data.

The advantages of ANN include the elimination of needing to program the systems and providing input from experts. The ANN CDSS can process incomplete data by making educated guesses about missing data and improves with every use due to its adaptive system learning. Additionally, ANN systems do not require large databases to store outcome data with its associated probabilities. Some of the disadvantages are that the training process may be time consuming leading users to not make use of the systems effectively. The ANN systems derive their own formulas for weighting and combining data based on the statistical recognition patterns over time which may be difficult to interpret and doubt the system’s reliability.

Examples include the diagnosis of appendicitis, back pain, myocardial infarction, psychiatric emergencies and skin disorders. The ANN’s diagnostic predictions of pulmonary embolisms were in some cases even better than physician’s predictions. Additionally, ANN based applications have been useful in the analysis of ECG (A.K.A. EKG) waveforms.

Genetic Algorithms

Genetic Algorithm (GA) is a nonknowledge-based method developed in the 1940s at the Massachusetts Institute of Technology based on Darwin’s evolutionary theories that dealt with the survival of the fittest. These algorithms rearrange to form different re-combinations that are better than the previous solutions. Similar to neural networks, the genetic algorithms derive their information from patient data.

An advantage of genetic algorithms is these systems go through an iterative process to produce an optimal solution. The fitness function determines the good solutions and the solutions that can be eliminated. A disadvantage is the lack of transparency in the reasoning involved for the decision support systems making it undesirable for physicians. The main challenge in using genetic algorithms is in defining the fitness criteria. In order to use a genetic algorithm, there must be many components such as multiple drugs, symptoms, treatment therapy and so on available in order to solve a problem. Genetic algorithms have proved to be useful in the diagnosis of female urinary incontinence.

Rule-Based System

A rule-based expert system attempts to capture knowledge of domain experts into expressions that can be evaluated known as rules; an example rule might read, “If the patient has high blood pressure, he or she is at risk for a stroke.” Once enough of these rules have been compiled into a rule base, the current working knowledge will be evaluated against the rule base by chaining rules together until a conclusion is reached. Some of the advantages of a rule-based expert system are the fact that it makes it easy to store a large amount of information, and coming up with the rules will help to clarify the logic used in the decision-making process. However, it can be difficult for an expert to transfer their knowledge into distinct rules, and many rules can be required for a system to be effective.

Rule-based systems can aid physicians in many different areas, including diagnosis and treatment. An example of a rule-based expert system in the clinical setting is MYCIN. Developed at Stanford University by Edward Shortliffe in the 1970s, MYCIN was based on around 600 rules and was used to help identify the type of bacteria causing an infection. While useful, MYCIN can help to demonstrate the magnitude of these types of systems by comparing the size of the rule base (600) to the narrow scope of the problem space.

The Stanford AI group subsequently developed ONCOCIN, another rules-based expert system coded in Lisp in the early 1980s.[8] The system was intended to reduce the number of clinical trial protocol violations, and reduce the time required to make decisions about the timing and dosing of chemotherapy in late phase clinical trials. As with MYCIN, the domain of medical knowledge addressed by ONCOCIN was limited in scope and consisted of a series of eligibility criteria, laboratory values, and diagnostic testing and chemotherapy treatment protocols that could be translated into unambiguous rules. Oncocin was put into production in the Stanford Oncology Clinic.

Logical Condition

The methodology behind logical condition is fairly simplistic; given a variable and a bound, check to see if the variable is within or outside of the bounds and take action based on the result. An example statement might be “Is the patient’s heart rate less than 50 BPM?” It is possible to link multiple statements together to form more complex conditions. Technology such as a decision table can be used to provide an easy to analyze representation of these statements.

In the clinical setting, logical conditions are primarily used to provide alerts and reminders to individuals across the care domain. For example, an alert may warn an anesthesiologist that their patient’s heart rate is too low; a reminder could tell a nurse to isolate a patient based on their health condition; finally, another reminder could tell a doctor to make sure he discusses smoking cessation with his patient. Alerts and reminders have been shown to help increase physician compliance with many different guidelines; however, the risk exists that creating too many alerts and reminders could overwhelm doctors, nurses, and other staff and cause them to ignore the alerts altogether.

Causal Probabilistic Network

The primary basis behind the causal network methodology is cause and effect. In a clinical causal probabilistic network, nodes are used to represent items such as symptoms, patient states or disease categories. Connections between nodes indicate a cause and effect relationship. A system based on this logic will attempt to trace a path from symptom nodes all the way to disease classification nodes, using probability to determine which path is the best fit. Some of the advantages of this approach are the fact that it helps to model the progression of a disease over time and the interaction between diseases; however, it is not always the case that medical knowledge knows exactly what causes certain symptoms, and it can be difficult to choose what level of detail to build the model to.

The first clinical decision support system to use a causal probabilistic network was CASNET, used to assist in the diagnosis of glaucoma. CASNET featured a hierarchical representation of knowledge, splitting all of its nodes into one of three separate tiers: symptoms, states and diseases.

  1. a b c d e “Decision support systems .” 26 July 2005. 17 Feb. 2009 <http://www.openclinical.org/dss.html>.
  2. 2^ a b c d e f g Berner, Eta S., ed. Clinical Decision Support Systems. New York, NY: Springer, 2007.
  3. 3^ Khosla, Vinod (December 4, 2012). “Technology will replace 80% of what doctors do”. Retrieved April 25, 2013.
  4. ^ Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J et al. (2005). “Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review.”JAMA 293 (10): 1223–38. doi:10.1001/jama.293.10.1223PMID 15755945.
  5. ^ Kensaku Kawamoto, Caitlin A Houlihan, E Andrew Balas, David F Lobach. (2005). “Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success.”BMJ 330 (7494): 765. doi:10.1136/bmj.38398.500764.8FPMC 555881PMID 15767266.
  6. ^ Gluud C, Nikolova D (2007). “Likely country of origin in publications on randomised controlled trials and controlled clinical trials during the last 60 years.”Trials 8: 7. doi:10.1186/1745-6215-8-7PMC 1808475PMID 17326823.
  7. ^ Wagholikar, K. “Modeling Paradigms for Medical Diagnostic Decision Support: A Survey and Future Directions”. Journal of Medical Systems. Retrieved 2012.
  8. ^ ONCOCIN: An expert system for oncology protocol management E. H. Shortliffe, A. C. Scott, M. B. Bischoff, A. B. Campbell, W. V. Melle, C. D. Jacobs Seventh International Joint Conference on Artificial Intelligence, Vancouver, B.C.. Published in 1981

SOURCE for Computation Engines Section and REFERENCES:

http://en.wikipedia.org/wiki/Clinical_decision_support_system

Cardiovascular Diseases: Decision Support Systems (DSS) for Disease Management Decision Making – DSS analyzes information from hospital cardiovascular patients in real time and compares it with a database of thousands of previous cases to predict the most likely outcome.

Can aviation technology reduce heart surgery complications?

Algorithm for real-time analysis of data holds promise for forecasting
August 13, 2012 | By 

British researchers are working to adapt technology from the aviation industry to help prevent complications among heart patients after surgery. Up to 1,000 sensors aboard aircraft help airlines determine when a plane requires maintenance, reports The Engineer, serving as a model for the British risk-prediction system.

The system analyzes information from hospital cardiovascular patients in real time and compares it with a database of thousands of previous cases to predict the most likely outcome.

“There are vast amounts of clinical data currently collected which is not analyzed in any meaningful way. This tool has the potential to identify subtle early signs of complications from real-time data,” Stuart Grant, a research fellow in surgery at University Hospital of South Manchester, says in a hospital statement. Grant is part of the Academic Surgery Unit working with Lancaster University on the project, which is still its early stages.

The software predicts the patient’s condition over a 24-hour period using four metrics: systolic blood pressure, heart rate, respiration rate and peripheral oxygen saturationexplains EE Times.

As a comparison tool, the researchers obtained a database of 30,000 patient records from the Massachusetts Institute of Technology and combined it with a smaller, more specialized database from Manchester.

In six months of testing, its accuracy is about 75 percent, The Engineer reports. More data and an improved algorithm could boost that rate to 85 percent, the researchers believe. Making the software web-based would allow physicians to access the data anywhere, even on tablets or phones, and could enable remote consultation with specialists.

In their next step, the researchers are applying for more funding and for ethical clearance for a large-scale trial.

U.S. researchers are working on a similar crystal ball, but one covering an array of conditions. Researchers from the University of Washington, MIT and Columbia University are using a statistical model that can predict future ailments based on a patient’s history–and that of thousands of others.

And the U.S. Department of Health & Human Services is using mathematical modeling to analyze effects of specific healthcare interventions.

Predictive modeling also holds promise to make clinical research easier by using algorithms examine multiple scenarios based on different kinds of patient populations, specified health conditions and various treatment regimens

To learn more:
– here’s the Engineer article
– check out the hospital report
– read the EE Times article

Related Articles:
Algorithm looks to past to predict future health conditions
HHS moves to mathematical modeling for research, intervention evaluation
Decision support, predictive modeling may speed clinical research

SOURCE:

Can aviation technology reduce heart surgery complications? – FierceHealthIT http://www.fiercehealthit.com/story/can-aviation-technology-reduce-heart-surgery-complications/2012-08-13#ixzz2SITHc61J

http://www.fiercehealthit.com/story/study-decision-support-systems-must-be-flexible-adaptable-transparent/2012-08-20

Medical Decision Making Tools: Overview of DSS available to date  

http://www.openclinical.org/dss.html

Clinical Decision Support Systems – used for Cardiovascular Medical Decisions

Stud Health Technol Inform. 2010;160(Pt 2):846-50.

AALIM: a cardiac clinical decision support system powered by advanced multi-modal analytics.

Amir A, Beymer D, Grace J, Greenspan H, Gruhl D, Hobbs A, Pohl K, Syeda-Mahmood T, Terdiman J, Wang F.

Source

IBM Almaden Research Center, San Jose, CA, USA.

Abstract

Modern Electronic Medical Record (EMR) systems often integrate large amounts of data from multiple disparate sources. To do so, EMR systems must align the data to create consistency between these sources. The data should also be presented in a manner that allows a clinician to quickly understand the complete condition and history of a patient’s health. We develop the AALIM system to address these issues using advanced multimodal analytics. First, it extracts and computes multiple features and cues from the patient records and medical tests. This additional metadata facilitates more accurate alignment of the various modalities, enables consistency check and empowers a clear, concise presentation of the patient’s complete health information. The system further provides a multimodal search for similar cases within the EMR system, and derives related conditions and drugs information from them. We applied our approach to cardiac data from a major medical care organization and found that it produced results with sufficient quality to assist the clinician making appropriate clinical decisions.

PMID: 20841805 [PubMed – indexed for MEDLINE]

DSS development for Enhancement of Heart Drug Compliance by Cardiac Patients 

A good example of a thorough and effective CDSS development process is an electronic checklist developed by Riggio et al. at Thomas Jefferson University Hospital (TJUH) [12]. TJUH had a computerized physician order-entry system in place. To meet congestive heart failure and acute myocardial infarction quality measures (e.g., use of aspirin, beta blockers, and angiotensin-converting enzyme (ACE) inhibitors), a multidisciplinary team including a focus group of residents developed a checklist, embedded in the computerized discharge instructions, that required resident physicians to prescribe the recommended medications or choose from a drop-down list of contraindications. The checklist was vetted by several committees, including the medical executive committee, and presented at resident conferences for feedback and suggestions. Implementation resulted in a dramatic improvement in compliance.

http://virtualmentor.ama-assn.org/2011/03/medu1-1103.html

Early DSS Development at Stanford Medical Center in the 70s

MYCIN (1976)     MYCIN was a rule-based expert system designed to diagnose and recommend treatment for certain blood infections (antimicrobial selection for patients with bacteremia or meningitis). It was later extended to handle other infectious diseases. Clinical knowledge in MYCIN is represented as a set of IF-THEN rules with certainty factors attached to diagnoses. It was a goal-directed system, using a basic backward chaining reasoning strategy (resulting in exhaustive depth-first search of the rules base for relevant rules though with additional heuristic support to control the search for a proposed solution). MYCIN was developed in the mid-1970s by Ted Shortliffe and colleagues at Stanford University. It is probably the most famous early expert system, described by Mark Musen as being “the first convincing demonstration of the power of the rule-based approach in the development of robust clinical decision-support systems” [Musen, 1999].

The EMYCIN (Essential MYCIN) expert system shell, employing MYCIN’s control structures was developed at Stanford in 1980. This domain-independent framework was used to build diagnostic rule-based expert systems such as PUFF, a system designed to interpret pulmonary function tests for patients with lung disease.

http://www.bmj.com/content/346/bmj.f657

ECG for Detection of MI: DSS use in Cardiovascualr Disease Management

http://faculty.ksu.edu.sa/AlBarrak/Documents/Clinical%20Decision%20Support%20Systems_Ch01.pdf

also showed that neural networks did a better job than two experienced cardiologists in detecting acute myocardial infarction in electrocardiograms with concomitant left bundle branch block.

Olsson SE, Ohlsson M, Ohlin H, Edenbrandt L. Neural networks—a diagnostic tool in acute myocardial infarction with concomitant left bundle branch block. Clin Physiol Funct Imaging 2002;22:295–299.

Sven-Erik Olsson, Hans Öhlin, Mattias Ohlsson and Lars Edenbrandt
Neural networks – a diagnostic tool in acute myocardial infarction with concomitant left bundle branch block
Clinical Physiology and Functional Imaging 22, 295-299 (2002) 

Abstract
The prognosis of acute myocardial infarction (AMI) improves by early revascularization. However the presence of left bundle branch block (LBBB) in the electrocardiogram (ECG) increases the difficulty in recognizing an AMI and different ECG criteria for the diagnosis of AMI have proved to be of limited value. The purpose of this study was to detect AMI in ECGs with LBBB using artificial neural networks and to compare the performance of the networks to that of six sets of conventional ECG criteria and two experienced cardiologists. A total of 518 ECGs, recorded at an emergency department, with a QRS duration > 120 ms and an LBBB configuration, were selected from the clinical ECG database. Of this sample 120 ECGs were recorded on patients with AMI, the remaining 398 ECGs being used as a control group. Artificial neural networks of feed-forward type were trained to classify the ECGs as AMI or not AMI. The neural network showed higher sensitivities than both the cardiologists and the criteria when compared at the same levels of specificity. The sensitivity of the neural network was 12% (P = 0.02) and 19% (P = 0.001) higher than that of the cardiologists. Artificial neural networks can be trained to detect AMI in ECGs with concomitant LBBB more effectively than conventional ECG criteria or experienced cardiologists.

http://home.thep.lu.se/~mattias/publications/papers/lu_tp_00_38_abs.html

Additional SOURCES:

http://www.implementationscience.com/content/6/1/92

http://www.fiercehealthit.com/story/study-decision-support-systems-must-be-flexible-adaptable-transparent/2012-08-20

 Comment of Note

During 1979-1983 Dr. Aviva Lev-Ari was part of Prof. Ronald A. Howard, Stanford University, Study Team, the consulting group to Stanford Medical Center during MYCIN feature enhancement development.

Professor Howard is one of the founders of the decision analysis discipline. His books on probabilistic modeling, decision analysis, dynamic programming, and Markov processes serve as major references for courses and research in these fields.

https://engineering.stanford.edu/profile/rhoward

It was Prof. Howard from EES, Prof. Amos Tversky of Behavior Science  (Advisor of Dr. Lev-Ari’s Masters Thesis at HUJ), and Prof. Kenneth Arrow, Economics, with 15 doctoral students in the early 80s, that formed the Interdisciplinary Decision Analysis Core Group at Stanford. Students of Prof. Howard, chiefly, James E. Matheson, started the Decision Analysis Practice at Stanford Research Institute (SRI, Int’l) in Menlo Park, CA.

http://www.sri.com/

Dr. Lev-Ari  was hired on 3/1985 to head SRI’s effort in algorithm-based DSS development. The models she developed were applied in problem solving for  SRI Clients, among them Pharmaceutical Manufacturers: Ciba Geigy, now NOVARTIS, DuPont, FMC, Rhone-Poulenc, now Sanofi-Aventis.

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Drug Eluting Stents: On MIT’s Edelman Lab’s Contributions to Vascular Biology and its Pioneering Research on DES

Drug Eluting Stents: On MIT‘s Edelman Lab’s Contributions to Vascular Biology and its Pioneering Research on DES

Author: Larry H Bernstein, MD, FACP

and 

Curator: Aviva Lev-Ari, PhD, RN
http://PharmaceuticalIntelligence.com/2013/04/25/Contributions
-to-vascular-biology/

This is the first of a three part series on the evolution of vascular biology and the studies of the effects of biomaterials in vascular reconstruction and on drug delivery, which has embraced a collaboration of cardiologists at Harvard Medical School , Affiliated Hospitals, and MIT,
requiring cardiovascular scientists at the PhD and MD level, physicists, and computational biologists working in concert, and
an exploration of the depth of the contributions by a distinguished physician, scientist, and thinker.

The first part – Vascular Biology and Disease – will cover the advances in the research on

  • vascular biology,
  • signaling pathways,
  • drug diffusion across the endothelium and
  • the interactions with the underlying muscularis (media),
  • with additional considerations for type 2 diabetes mellitus.

The second part – Stents and Drug Delivery – will cover the

  • purposes,
  • properties and
  • evolution of stent technology with
  • the acquired knowledge of the pharmacodynamics of drug interactions and drug distribution.

The third part – Problems and Promise of Biomaterials Technology – will cover the shortcomings of the cardiovascular devices, and opportunities for improvement

Vascular Biology and Cardiovascular Disease

Early work on endothelial injury and drug release principles

The insertion of a catheter for the administration of heparin is not an innocuous procedure. Heparin is infused to block coagulation, lowering the risk of a dangerous

  • clot formation and
  • dissemination.

It was shown experimentally that the continuous infusion of heparin

  • suppresses smooth muscle proliferation after endothelial injury. It may lead to
  • hemorrhage as a primary effect.

The anticoagulant property of heparin was removed by chemical modification without loss of the anti-proliferative effect.

In this study, MIT researches placed ethylene-vinyl acetate copolymer matrices containing standard and modified heparin adjacent to rat carotid arteries at the time of balloon deendothelialization.

Matrix delivery of both heparin compounds effectively diminished this proliferation in comparison to controls without producing systemic anticoagulation or side effects.

This mode of therapy appeared more effective than administering the agents by either

  • intravenous pumps or
  • heparin/polymer matrices placed in a subcutaneous site distant from the injured carotid artery

This indicated that the site of placement at the site of injury is a factor in the microenvironment, and is a preference for avoiding restenosis after angioplasty and other interventions.

This raised the question of why the proliferation of vascular muscle occurs in the first place.
 Edelman, Nugent and Karnovsky  (1) showed that the proliferation required first the denudation of vascular surface endothelium. This exposed the underlayer to the effect of basic fibroblast growth factor, which stimulates mitogenesis of the exposed cell, explained by the endothelium as a barrier from circulating bFGF.

To answer this question, they compared the effect of

  • 125I-labelled bFGF intravenously given with perivascular controlled bFGF release.
  • Polymeric controlled release devices delivered bFGF to the extravascular space without transendothelial transport. 
Deposition within the blood vessel wall was rapidly distributed circumferentially and was substantially greater than that observed following intravenous injection.

The amount of bFGF deposited in arteries adjacent to the release devices was 40 times that deposited in similar arteries in animals who received a single intravenous bolus of bFGF.

The presence of intimal hyperplasia increased deposition of perivascularly released bFGF 2.4-fold but decreased the deposition of intravenously injected bFGF by 67%.

  • bFGF was 5- to 30-fold more abundant in solid organs after intravenous injection than it was following perivascular release, and
  • bFGF deposition was greatest in the kidney, liver, and spleen and was substantially lower in the heart and lung.

This result indicated that vascular deposition of bFGF is independent of endothelium, and

  • bFGF delivery is effectively perivascular. (2)

Drug activity studies have to be done in well controlled and representative conditions.
 Edelsman’s Lab researchers studied the

  • dose response of injured arteries to exogenous heparin in vivo by providing steady and predictable arterial levels of drug.
  • Controlled-release devices were fabricated to direct heparin uniformly and at a steady rate to the adventitial surface of balloon-injured rat carotid arteries.

Researchers predicted the distribution of heparin throughout the arterial wall using computational simulations and correlated these concentrations with the biologic response of the tissues.

Researchers determined from this process that an in vivo arterial concentration of 0.3 mg/ml of heparin is required to maximallyinhibit intimal hyperplasia after injury.

This estimation of the required tissue concentration of a drug is

  • independent of the route of administration and
  • applies to all forms of drug release.

In this way the Team was able to

  • evaluate the potential of  widely disparate forms of drug release and, to finally
  • create some rigorous criteria by which to guide the development of particular delivery strategies for local diseases. (3)

Chiefly, the following three effects:

(1) Effect of controlled adventitial heparin delivery on smooth muscle cell proliferation following endothelial injury. ER Edelman, DH Adams, and MJ Karnovsky. PNAS May 1990; 87: 3773-3777.


(2) Perivascular and intravenous administration of basic fibroblast growth factor: Vascular and solid organ deposition. ER Edelman, MA Nugent, and MJ Karnovsky. PNAS Feb 1993; 90: 1513-1517.


(3) Tissue concentration of heparin, not administered dose, correlates with the biological response of injured arteries in vivo. MA Lovich and ER Edelman. PNAS Sep 1999; 96: 11111–11116.

Vascular Injury and Repair

Perlecan is a heparin-sulfate proteoglycan that might be critical for regulation of vascular repair by inhibiting the binding and mitogenic activity of basic fibroblast growth factor-2 (bFGF-2) in vascular smooth muscle cells .

The Team generated

  • Clones of endothelial cells expressing an antisense vector targeting domain III of perlecan. The transfected cells produced significantly less perlecan than parent cells, and they had reduced bFGF in vascular smooth muscle cells.
  • Endothelial cells were seeded onto three-dimensional polymeric matrices and implanted adjacent to porcine carotid arteries subjected to deep injury.
  • The parent endothelial cells prevented thrombosis, but perlecan deficient cells were ineffective.

The ability of endothelial cells to inhibit intimal hyperplasia, however, was only in part suppressed by perlecan. The differential regulation by perlecan of these aspects of vascular repair may clarify why control of clinical clot formation does not lead to full control of intimal hyperplasia.

The use of genetically modified tissue engineered cells provides a new approach for dissecting the role of specific factors within the blood vessel wall.(1) Successful implementation of local arterial drug delivery requires transmural distribution of drug. The physicochemical properties of the applied compound govern its transport and tissue binding.

  • Hydrophilic compounds are cleared rapidly.
  • Hydrophobic drugs bind to fixed tissue elements, potentially prolonging tissue residence and biological effect.

Local vascular drug delivery provides

  • elevated concentrations of drug in the target tissue while
  • minimizing systemic side effects.

To better characterize local pharmacokinetics the Team examined the arterial transport of locally applied dextran and dextran derivatives in vivo.

Using a two-compartment pharmacokinetic model to correct

  • The measured transmural flux of these compounds for systemic
  • Redistribution and elimination as delivered from a photo-polymerizable hydrogel.
  • The diffusivities and the transendothelial permeabilities were strongly dependent on molecular weight and charge
  • For neutral dextrans, the diffusive resistance increased with molecular weightapproximately 4.1-fold between the molecular weights of 10 and 282 kDa.
  • Endothelial resistance increased 28-fold over the same molecular weight range.
  • The effective medial diffusive resistance was unaffected by cationic charge as such molecules moved identically to neutral compounds, but increased approximately 40% when dextrans were negatively charged.

Transendothelial resistance was 20-fold lower for the cationic dextrans, and 11-fold higher for the anionic dextrans, when both were compared to neutral counterparts.

These results suggest that, while

  • low molecular weight drugs will rapidly traverse the arterial wall with the endothelium posing a minimal barrier,
  • the reverse is true for high molecular weight agents.

The deposition and distribution of locally released vascular therapeutic compounds might be predicted based upon chemical properties, such as molecular weight and charge. (2)

Paclitaxel is hydrophobic and has therapeutic potential against proliferative vascular disease.
 The favorable preclinical data with this compound may, in part, result from preferential tissue binding.
 The complexity of Paclitaxel pharmacokinetics required in-depth investigation if this drug is to reach its full clinical potential in proliferative vascular diseases.

Equilibrium distribution of Paclitaxel reveals partitioning above and beyond perfusate concentration and a spatial gradient of drug across the arterial wall.

The effective diffusivity (Deff) was estimated from the Paclitaxel distribution data to

  • facilitate comparison of transport of Paclitaxel through arterial parenchyma with that of other vasoactive agents and to
  • characterize the disparity between endovascular and perivascular application of drug.

This transport parameter described the motion of drug in tissues given an applied concentration gradient and includes, in addition to diffusion,

  • the impact of steric hindrance within the arterial interstitium;
  • nonspecific binding to arterial elements; and, in the preparation used here,
  • convective effects from the applied transmural pressure gradient.

At all times, the effective diffusivity for endovascular delivery exceeded that of perivascular delivery. The arterial transport of Paclitaxel was quantified through application ex vivo and measurement of the subsequent transmural distribution.

  • Arterial Paclitaxel deposition at equilibrium varied across the arterial wall.
  • Permeation into the wall increased with time, from 15 minutes to 4 hours, and
  • varied with the origin of delivery.

In contrast to hydrophilic compounds, the concentration in tissue exceeded the applied concentration and the rate of transport was markedly slower. Furthermore, endovascular and perivascular Paclitaxel application led to differences in deposition across the blood vessel wall.

This leads to a conclusion that Paclitaxel interacts with arterial tissue elements  as it moves under the forces of

  • diffusion and
  • convection and
  • can establish substantial partitioning and spatial gradients across the tissue. (3)

Endovascular drug-eluting stents have changed the practice of  cardiovascular vascularization, and yet it is unclear how they so dramatically reduce restenosis

We don’t know how to distinguish between the different formulations available.
 Researchers are now questioning whether individual properties of different drugs beyond lipid avidity effect arterial transport and distribution.

In bovine internal carotid segments, tissue-loading profiles for

  • Hydrophobic Paclitaxel and Rapamycin are indistinguishable, reaching load steady state after 2 days.
  • Hydrophilic dextran reaches equilibrium in hours.

Paclitaxel and Rapamycin bind to the artery at 30–40 times bulk concentration, and bind to specific tissue elements.

Transmural drug distribution profiles are markedly different for the two compounds.

  • Rapamycin binds specifically to FKBP12 binding protein and it distributes evenly through the artery,
  • Paclitaxel binds specifically to microtubules, and remains primarily in the subintimal space.

The binding of Rapamycin and Paclitaxel to specific intracellular proteins plays an essential role in

  • determining arterial transport and distribution and in
  • distinguishing one compound from another.

These results offer further insight into the

  • mechanism of local drug delivery and the
  • specific use of existing drug-eluting stent formulations. (4)

The Role of Amyloid beta (A) in Creation of Vascular Toxic Plaque

Amyloid beta (A) is a peptide family produced and deposited in neurons and endothelial cells (EC).
It is found at subnanomolar concentrations in the plasma of healthy individuals.
 Simple conformational changes produce a form of A-beta , A-beta 42, which creates toxic plaque in the brains of Alzheimer’s patients.

Oxidative stress induced blood brain barrier degeneration has been proposed as a key factor for A-beta 42 toxicity.

This cannot account for lack of injury from the same peptide in healthy tissues.
Researchers hypothesized that cell state mediates A-beta’s effect.
 They examined the viability in the presence of A-beta secreted from transfected
Chinese hamster ovary cells (CHO) of

  • aortic Endothelial Cells (EC),
  • vascular smooth muscle cells (SMC) and
  • epithelial cells (EPI) in different states

A-beta was more toxic to all cell types when they were subconfluent.
 Subconfluent EC sprouted and SMC and EPI were inhibited by A-beta.
Confluent EC were virtually resistant to A-beta and suppressed A-beta production by A-beta +CHO.

Products of subconfluent EC overcame this resistant state, stimulating the production and toxicity of A-beta 42. Confluent EC overgrew >35% beyond their quiescent state in the presence of A-beta conditioned in media from subconfluent EC.

These findings imply that A-beta 42 may well be even more cytotoxic to cells in injured or growth states and potentially explain the variable and potent effects of this protein.

One may now need to consider tissue and cell state in addition to local concentration of and exposure duration to A-beta.

The specific interactions of A-beta and EC in a state-dependent fashion may help understand further the common and divergent forms of vascular and cerebral toxicity of A-beta and the spectrum of AD. (5)

(1) Perlecan is required to inhibit thrombosis after deep vascular injury and contributes
to endothelial cell-mediated inhibition of intimal hyperplasia. MA Nugent, HM Nugent,
RV Iozzoi, K Sanchack, and ER Edelman. PNAS Jun 2000; 97(12): 6722-6727


(2) Correlation of transarterial transport of various dextrans with their physicochemical properties.
O Elmalak, MA Lovich, E Edelman. Biomaterials 2000; 21: 2263-2272


(3) Arterial Paclitaxel Distribution and Deposition. CJ Creel, MA Lovich, ER Edelman. Circ Res. 2000;86:879-884


(4) Specific binding to intracellular proteins determines arterial transport properties for rapamycin and Paclitaxel.
AD Levin, N Vukmirovic, Chao-Wei Hwang, and ER Edelman. PNAS Jun 2004; 101(25): 9463–9467.
www.pnas.org/cgi/doi/10.1073/pnas.0400918101

(5) Amyloid beta toxicity dependent upon endothelial cell state. M Balcells, JS Wallins, ER Edelman.
Neuroscience Letters 441 (2008) 319–322

Endothelial Damage as an Inflammatory State

Autoimmunity may drive vascular disease through anti-endothelial cell (EC) antibodies. This raises a question about whether an increased morbidity of cardiovascular diseases in concert with systemic illnesses may involve these antibodies.

Matrix-embedded ECs act as powerful regulators of vascular repair accompanied by significant reduction in expected systemic and local inflammation.

The Lab researchers compared the immune response against free and matrix-embedded ECs in naive mice and mice with heightened EC immune reactivity. Mice were presensitized to EC with repeated subcutaneous injections of saline-suspended porcine EC (PAE) (5*10^5 cells).

On day 42, both naive mice (controls) and mice with heightened EC immune reactivity received 5*10^5 matrix-embedded or free PAEs. Circulating PAE-specific antibodies and effector T-cells were analyzed 90 days after implantation for –

  • PAE-specific antibody-titers,
  • frequency of CD4+-effector cells, and
  • xenoreactive splenocytes

These were 2- to 4-fold lower (P<0.0001) when naıve mice were injected with matrix-embedded instead of saline-suspended PAEs.

Though basal levels of circulating antibodies were significantly elevated after serial PAE injections (2210+341 mean fluorescence intensity, day 42) and almost doubled again 90 days after injection of a fourth set of free PAEs, antibody levels declined by half in recipients of matrix-embedded PAEs at day 42 (P<0.0001), as did levels of CD4+-effector cells and xenoreactive splenocytes.

A significant immune response to implantation of free PAE is elicited in naıve mice, that is even more pronounced in mice with pre-developed anti-endothelial immunity.

Matrix-embedding protects xenogeneic ECs against immune reaction in naive mice and in mice with heightened immune reactivity.

Matrix-embedded EC might offer a promising approach for treatment of advanced cardiovascular disease. (1)

Researchers examined the molecular mechanisms through which

mechanical force and hypertension modulate

endothelial cell regulation of vascular homeostasis.

Exposure to mechanical strain increased the paracrine inhibition of vascular smooth muscle cells (VSMCs) by endothelial cells.

Mechanical strain stimulated the production by endothelial cells of perlecan and heparan-sulfate glycosaminoglycans. By inhibiting the expression of perlecan with an antisense vector researchers demonstrated that perlecan was essential to the strain-mediated effects on endothelial cell growth control.

Mechanical regulation of perlecan expression in endothelial cells was

  • governed by a mechano-transduction pathway
  • requiring transforming growth factor (TGF-β) signaling and
  • intracellular signaling through the ERK pathway.

Immunohistochemical staining of the aortae of spontaneously hypertensive rats
demonstrated strong correlations between

  • endothelial TGF-β,
  • phosphorylated signaling intermediates, and
  • arterial thickening.

Studies on ex vivo arteries exposed to varying levels of pressure demonstrated that

ERK and TGF-beta signaling were required for pressure-induced upregulation of endothelial HSPG.

The Team’s findings suggest a novel feedback control mechanism in which

  • net arterial remodeling to hemodynamic forces is controlled by a dynamic interplay between growth stimulatory signals from vSMCs and
  • growth inhibitory signals from endothelial cells. (2)

Heparan-sulfate proteoglycans (HSPGs) are potent regulators of vascular remodeling and repair.
 The major enzyme capable of degrading HSPGs is heparanase, which led us to examine
the role of heparanase in controlling

  • arterial structure,
  • mechanics, and
  • remodeling.

In vitro studies suggested heparanase expression in endothelial cells serves as a negative regulator of endothelial inhibition of vascular smooth muscle cell (vSMC) proliferation.

ECs inhibit vSMC proliferation through the interplay between

  • growth stimulatory signals from vSMCs and
  • growth inhibitory signals from ECs.

This would be expected if ECs had HSPGs that are degraded by heparanase.
Arterial structure and remodeling to injury is modified by heparanase expression.
Transgenic mice overexpressing heparanase had

  • increased arterial thickness,
  • cellular density, and
  • mechanical compliance.

Endovascular stenting studies in Zucker rats demonstrated increased heparanase expression in the neointima of obese, hyperlipidemic rats in comparison to lean rats.

The extent of heparanase expression within the neointima strongly correlated with the neointimal thickness following injury. To test the effects of heparanase overexpression on arterial repair, researchers developed a novel murine model of stent injury using small diameter self-expanding stents.

Using this model, researchers found that increased

  • neointimal formation and
  • macrophage recruitment occurs in transgenic mice overexpressing heparanase.
  • Taken together, these results support a role for heparanase in the regulation of arterial structure, mechanics, and repair. (3)

The first host–donor reaction in transplantation occurs at the blood–tissue interface.
When the primary component of the implant (donor) is the endothelial cells, it incites an immunologic reaction. Injections of free endothelial cell implants elicit a profound major histocompatibility complex (MHC) II dominated immune response.

Endothelial cells embedded within three-dimensional matrices behave like quiescent endothelial cells.

Perivascular implants of such embedded ECs cells are the most potent inhibitor of intimal hyperplasia and thrombosis following controlled vascular injury, but without any immune reactivity.

Allo- and even exenogenic endothelial cells evoke no significant humoral or
cellular immune response in immune-competent hosts when embedded within matrices.
 Moreover,  endothelial implants are immune-modulatory, reducing the extent of the memory response to previous free cell implants.

Attenuated immunogenicity results in muted activation of adaptive and innate immune cells. These findings point toward a pivotal role of matrix–cell-interconnectivity for

  • the cellular immune phenotype and might therefore assist in the design  of
  • extracellular matrix components for successful tissue engineering. (4)

Because changes in subendothelial matrix composition are associated with alterations of the endothelial immune phenotype, researchers sought to understand if

  • cytokine-induced NF-κB activity and
  • downstream effects depend on substrate adherence of endothelial cells (EC).

The team compared the upstream

  • phosphorylation cascade,
  • activation of NF-ĸβ, and
  • expression/secretion

of downstream effects of EC grown on tissue culture polystyrene plates (TCPS) with EC embedded within collagen-based matrices (MEEC).

Adhesion of natural killer (NK) cells was quantified in vitro and in vivo.

  • NF-κβ subunit p65 nuclear levels were significantly lower and
  • p50 significantly higher in cytokine-stimulated MEEC than in EC-TCPS.

Despite similar surface expression of TNF-α receptors, MEEC had significantly decreased secretion and expression of IL-6, IL-8, MCP-1, VCAM-1, and ICAM-1.

Attenuated fractalkine expression and secretion in MEEC (two to threefold lower than in EC-TCPS; p < 0.0002) correlated with 3.7-fold lower NK cell adhesion to EC (6,335 ± 420 vs. 1,735 ± 135 cpm; p < 0.0002).

Furthermore, NK cell infiltration into sites of EC implantation in vivo was significantly reduced when EC were embedded within matrix.

Matrix embedding enables control of EC substratum interaction.

This in turn regulates chemokine and surface molecule expression and secretion, in particular – of those compounds within NF-κβ pathways,

  • chemoattraction of NK cells,
  • local inflammation, and
  • tissue repair. (5)

Monocyte recruitment and interaction with the endothelium is imperative to vascular recovery.

Tie2 plays a key role in endothelial health and vascular remodeling.
Researchers studied monocyte-mediated Tie2/angiopoietin signaling following interaction of primary monocytes with endothelial cells and its role in endothelial cell survival.

The direct interaction of primary monocytes with subconfluent endothelial cells

resulted in transient secretion of angiopoietin-1 from monocytes and

the activation of endothelial Tie2. This effect was abolished by preactivation of monocytes with tumor necrosis factor-α (TNFα).

Although primary monocytes contained high levels of

  • both angiopoietin 1 and 2,
  • endothelial cells contained primarily angiopoietin 2.

Seeding of monocytes on serum-starved endothelial cells reduced caspase-3 activity by 46+5.1%, and 52+5.8% after TNFα treatment, and it decreased single-stranded DNA levels by 41+4.2% and 40+ 3.5%, respectively.

This protective effect of monocytes on endothelial cells was reversed by Tie2 silencing with specific short interfering RNA.

The antiapoptotic effect of monocytes was further supported by the

  • activation of cell survival signaling pathways involving phosphatidylinositol 3-kinase,
  • STAT3, and
  • AKT.

Monocytes and endothelial cells form a unique Tie2/angiopoietin-1 signaling system that affects endothelial cell survival and may play critical a role in vascular remodeling and homeostasis. (6)

(1) Cell–Matrix Contact Prevents Recognition and Damage of Endothelial Cells in States of Heightened Immunity.
H Methe, ER Edelman. Circulation. 2006;114[suppl I]:I-233–I-238.
http://www.circulationaha.org/DOI/10.1161/CIRCULATIONAHA.105.000687

(2) Endothelial Cells Provide Feedback Control for Vascular Remodeling Through a Mechanosensitive Autocrine
TGFβ Signaling Pathway. AB Baker, DS Ettenson, M Jonas, MA Nugent, RV Iozzo, ER Edelman.
Circ. Res. 2008;103;289-297   http://dx.doi.org/10.1161/CIRCRESAHA.108.179465http://circres.ahajournals.org/cgi/content/full/103/3/289

(3) Heparanase Alters Arterial Structure, Mechanics, and Repair Following Endovascular Stenting in Mice.
AB Baker, A Groothuis, M Jonas, DS Ettenson…ER Edelman.   Circ. Res. 2009;104;380-387;
http://dx.doi.org/10.1161/CIRCRESAHA.108.180695  http://circres.ahajournals.org/cgi/content/full/104/3/380

(4) The effect of three-dimensional matrix-embedding of endothelial cells on the humoral and cellular immune response.
H Methe, S Hess, ER Edelman. Seminars in Immunology 20 (2008) 117–122. http://dx.doi.org/10.1016/j.smim.2007.12.005

(5) NF-kB Activity in Endothelial Cells Is Modulated by Cell Substratum Inter-actions and Influences Chemokine-Mediated
Adhesion of Natural Killer Cells.  S Hess, H Methe, Jong-Oh Kim, ER Edelman.
Cell Transplantation 2009; 18: 261–273


(6) Primary Monocytes Regulate Endothelial Cell Survival Through Secretion of Angiopoietin-1 and Activation of Endothelial Tie2.
SY Schubert, A Benarroch, J Monter-Solans and ER Edelman. Arterioscler Thromb Vasc Biol 2011;31;870-875
http://dx.doi.org/10.1161/ATVBAHA.110.218255

Neointimal Formation, Shear Stress, and Remodelling with Reference to Diabetes

Innate immunity is of major importance in vascular repair. The present study evaluated whether

  • systemic and transient depletion of monocytes and macrophages with
  • liposome-encapsulated bisphosphonates inhibits experimental in-stent neointimal formation.

The Experiment

Rabbits fed on a hypercholesterolemic diet underwent bilateral iliac artery balloon denudation and stent deployment.

Liposomal alendronate (3 or 6 mg/kg) was given concurrently with stenting.

  • Monocyte counts were reduced by 90% 24 to 48 hours aftera single injection of liposomal alendronate, returning to basal levels at 6 days.

This treatment significantly reduced

  • intimal area at 28 days, from 3.88+0.93 to 2.08+0.58 and 2.16 +0.62 mm2.
  • Lumen area was increased from 2.87+0.44 to 3.57­+0.65 and 3.45+0.58 mm2, and
  • arterial stenosis was reduced from 58 11% to 37 8% and 38 7% in controls, in rabbits treated with 3 mg/kg, and with 6 mg/kg, respectively (mean+SD, n=8 rabbits/group, P< 0.01 for all 3 parameters).

No drug-related adverse effects were observed.
Reduction in neointimal formation was associated with

  • reduced arterial macrophage infiltration and proliferation at 6 days and with an
  • equal reduction in intimal macrophage and smooth muscle cell content at 28 days after injury.

Conversely, drug regimens ineffective in reducing monocyte levels did not inhibit neointimal formation.
Researchers have shown that a

  • single liposomal bisphosphonates injection concurrent with injury reduces in-stent neointimal formation and
  • arterial stenosis in hypercholesterolemic rabbits, accompanied by systemic transient depletion of monocytes and macrophages. (1)

Diabetes and insulin resistance are associated with increased disease risk and poor outcomes from cardiovascular interventions.

Even drug-eluting stents exhibit reduced efficacy in patients with diabetes.
Researchers reported the first study of vascular response to stent injury in insulin-resistant and diabetic animal models.

Endovascular stents were expanded in the aortae of

  • obese insulin-resistant and
  • type 2 diabetic Zucker rats,
  • in streptozotocin-induced type 1 diabetic Sprague-Dawley rats, and
  • in matched controls.

Insulin-resistant rats developed thicker neointima (0.46+0.08 versus 0.37+0.06 mm2, P 0.05), with  decreased lumen area (2.95+0.26 versus 3.29+0.15 mm2, P 0.03) 14 days after stenting compared with controls, but without increased vascular inflammation (tissue macrophages).

Insulin-resistant and diabetic rat vessels did exhibit markedly altered signaling pathway activation 1 and 2 weeks after stenting, with up to a 98% increase in p-ERK (anti-phospho ERK) and a 54% reduction in p-Akt (anti-phospho Akt) stained cells. Western blotting confirmed a profound effect of insulin resistance and diabetes on Akt and ERK signaling in stented segments. p-ERK/p-Akt ratio in stented segments uniquely correlated with neointimal response (R2 = 0.888, P< 0.04) , but not in lean controls.

Transfemoral aortic stenting in rats provides insight into vascular responses in insulin resistance and diabetes.

Shifts in ERK and Akt signaling related to insulin resistance may reflect altered tissue repair in diabetes accompanied by a

  • shift in metabolic : proliferative balance.

These findings may help explain the increased vascular morbidity in diabetes and suggest specific therapies for patients with insulin resistance and diabetes. (2)

Researchers investigated the role of Valsartan (V) alone or in combination with Simvastatin (S) on coronary atherosclerosis and vascular remodeling, and tested the hypothesis that V or V/S attenuate the pro-inflammatory effect of low endothelial shear stress (ESS).

Twenty-four diabetic, hyperlipidemic swine were allocated into Early (n = 12) and Late (n=12) groups.
Diabetic swine in each group were treated with Placebo (n=4), V (n = 4) and V/S (n = 4) and  followed for 8 weeks in the Early group and 30 weeks in the Late group.

Blood pressure, serum cholesterol and glucose were similar across the treatment subgroups.
ESS was calculated in plaque-free subsegments of interest (n = 109) in the Late group at week 23.
Coronary arteries of this group were harvested at week 30, and the subsegments of interest were identified, and analyzed histopathologically.

Intravascular geometrically correct 3-dimensional reconstruction of the coronary arteries of 12 swine was performed 23 weeks after initiation of diabetes mellitus and a hyperlipidemic diet. Local endothelial shear stress was calculated

  • in plaque-free subsegments of interest (n=142) with computational fluid dynamics, and
  • the coronary arteries (n=31) were harvested and the same subsegments were identified at 30 weeks.

V alone or with S

  • reduced the severity of inflammation in high-risk plaques.
Both regimens attenuated the severity of enzymatic degradation of the arterial wall, reducing the severity of expansive remodeling.
  • attenuated the pro-inflammatory effect of low ESS.
V alone or with S
  • exerts a beneficial effect of reducing and stabilizing high-risk plaque characteristics independent of a blood pressure- and lipid-lowering effect. (3)

This study tested the hypothesis that low endothelial shear stress  augments the

  • expression of matrix-degrading proteases, promoting the
  • formation of thin-capped atheromata.

Researchers assessed the messenger RNA and protein expression, and elastolytic activity of selected elastases and their endogenous inhibitors.

Subsegments with low endothelial shear stress at week 23 showed

  • reduced endothelial coverage,
  • enhanced lipid accumulation, and
  • intense infiltration of activated inflammatory cells at week 30.

These lesions showed increased expression of messenger RNAs encoding

  • matrix metalloproteinase-2, -9, and -12, and cathepsins K and S
  • relative to their endogenous inhibitors and
  • increased elastolytic activity.

Expression of these enzymes correlated positively with the severity of internal elastic lamina fragmentation.

Thin-capped atheromata in regions with

  • lower preceding endothelial shear stress had
  • reduced endothelial coverage,
  • intense lipid and inflammatory cell accumulation,
  • enhanced messenger RNA expression and
  • elastolytic activity of MMPs and cathepsins with
  • severe internal elastic lamina fragmentation.

Low endothelial shear stress induces endothelial discontinuity and

  • accumulation of activated inflammatory cells, thereby
  • augmenting the expression and activity of elastases in the intima and
  • shifting the balance with their inhibitors toward matrix breakdown.

Team’s results provide new insight into the mechanisms of regional formation of plaques with thin fibrous caps. (4)

Elevated CRP levels predict increased incidence of cardiovascular events and poor outcomes following interventions. There is the suggestion that CRP is also a mediator of vascular injury.

Transgenic mice carrying the human CRP gene (CRPtg) are predisposed to arterial thrombosis post-injury.

Researchers examined whether CRP similarly modulates the proliferative and hyperplastic phases of vascular repair in CRPtg when thrombosis is controlled with daily aspirin and heparin at the time of trans-femoral arterial wire-injury.

Complete thrombotic arterial occlusion at 28 days was comparable for wild-type and CRPtg mice (14 and 19%, respectively). Neointimal area at 28d was 2.5 fold lower in CRPtg (4190±3134 m2, n = 12) compared to wild-types (10,157±8890 m2, n = 11, p < 0.05).

Likewise, neointimal/media area ratio was 1.10±0.87 in wild-types and 0.45±0.24 in CRPtg (p < 0.05).

  • Seven days post-injury, cellular proliferation and apoptotic cell number in the intima were both less pronounced in CRPtg than wild-type.
  • No differences were seen in leukocyte infiltration or endothelial coverage.
CRPtg mice had significantly reduced p38 MAPK signaling pathway activation following injury.

The pro-thrombotic phenotype of CRPtg mice was suppressed by aspirin/heparin, revealing CRP’s influence on neointimal growth after trans-femoral arterial wire-injury.

  • Signaling pathway activation,
  • cellular proliferation, and
  • neointimal formation

were all reduced in CRPtg following vascular injury.
 Increasingly the Team was aware of CRP multipotent effects.
 Once considered only a risk factor, and recently a harmful agent, CRP is a far more complex regulator of vascular biology. (5)

(1) Liposomal Alendronate Inhibits Systemic Innate Immunity and Reduces In-Stent Neointimal
Hyperplasia in Rabbits. HD Danenberg, G Golomb, A Groothuis, J Gao…, ER Edelman.
Circulation. 2003;108:2798-2804


(2) Vascular Neointimal Formation and Signaling Pathway Activation in Response to Stent Injury
in Insulin-Resistant and Diabetic Animals. M Jonas, ER Edelman, A Groothuis, AB Baker, P Seifert, C Rogers.
Circ. Res. 2005;97;725-733.        http://dx.doi.org/10.1161/01.RES.0000183730.52908.C6
http://circres.ahajournals.org/cgi/content/full/97/7/725

(3) Attenuation of inflammation and expansive remodeling by Valsartan alone or in combination with
Simvastatin in high-risk coronary atherosclerotic plaques. YS Chatzizisis, M Jonas, R Beigel, AU Coskun…
ER Edelman, CL Feldman, PH Stone.  Atherosclerosis 203 (2009) 387–394


(4) Augmented Expression and Activity of Extracellular Matrix-Degrading Enzymes in Regions of Low
Endothelial Shear Stress Colocalize With Coronary Atheromata With Thin Fibrous Caps in Pigs.
YS Chatzizisis, AB Baker, GK Sukhova,…P Libby, CL Feldman, ER Edelman, PH Stone
Circulation 2011;123;621-630     http://dx.doi.org/10.1161/CIRCULATIONAHA.110.970038
http://circ.ahajournals.org/cgi/content/full/123/6/621


(5) Neointimal formation is reduced after arterial injury in human crp transgenic mice
HD Danenberg, E Grad, RV Swaminathan, Z Chenc,…ER Edelman
Atherosclerosis 201 (2008) 85–91

A Rattle Bag of Science and the Art of Translation

Science Translational Medicine – A rattle bag of science and the art of translation
E. R. Edelman, G. A. FitzGerald.
Sci.Transl. Med. 3, 104ed3 (2011). http://dx.doi.org/10.1126/scitranslmed.3002131

Elazer R. Edelman is the Thomas D. and Virginia W. Cabot Professor of Health Sciences and Technology at MIT,
Professor of Medicine at Harvard Medical School, a coronary care unit cardiologist at the Brigham and Women’s
Hospital, and Director of the Harvard-MIT Biomedical Engineering Center. E-mail: ere@mit.edu

Garret A. FitzGerald is the McNeil Professor in Translational Medicine and Therapeutics, Chair of the Department of
Pharmacology, and Director of the Institute for Translational Medicine & Therapeutics, University of Pennsylvania.
E-mail: garret@upenn.edu

In 2011, the American Association for the Advancement of Science (AAAS)  founded Science Translational Medicine (STM)
to disseminate interdisciplinary science integrating basic and clinical research that defines and fosters new therapeutics, devices, and diagnostics.

Conceived and nourished under the creative vision of Elias Zerhouni and Katrina Kelner, the journal has attracted widespread attention.
Now, as we assume the mantle of co-chief scientific advisors, we look back on the journal’s early accomplishments, restate our mission, and make clear the kinds of manuscripts we seek and accept for publication.

STM’s mission, as articulated by Elias and Katrina, was to

“promote human health by providing a forum for communication and cross-fertilization among basic, translational, and clinical research practitioners and trainees from all relevant established and emerging disciplines.”

This statement remains relevant and accurate today.
 With this mission on our masthead, STM now receives ~25 manuscripts (full-length research articles) per week and publishes ~10% of them. Roughly half of the submissions are deemed inappropriate for the journal and are returned without review within 8 to 10 days of receipt.

Of those papers that undergo full peer review,

decisions to reject are made within 48 days and

the mean time to acceptance (including the revision period) is 125 days.

There is now an average wait of only 24 days between acceptance and publication.

Defining TRANSLATIONAL Medicine

In accord with the journal’s broad readership, the ideal manuscript meets five criteria: It
(i) reports a discovery of translational relevance with high-impact potential;
(ii) has a conceptual focus with interdisciplinary appeal;
(iii) elucidates a biological mechanism;
(iv) is innovative and novel; and
(v) is presented in clear, broadly accessible language.
 STM seeks to publish research that describes

  • how innovative concepts drive the creative biomedical science
  • that ultimately improves the quality of people’s lives—

This is the broadest of our journal’s criteria but is the one that sets us apart as well.
Translational relevance does not require demonstration of benefit in humans but does require the evident potential to advance clinical medicine, thus impacting the direction of our culture and the welfare of our communities. Conceptual focus and mechanistic emphasis discriminate our papers from those that contain observational descriptions of technical findings for which value is restricted to a specific discipline.

However, innovation and novelty may apply to a fundamental scientific discovery or to the nature of its application and relevance to the translational process. Criteria enable the journal to consider versatile technological advances that apply new and creative thinking but may not necessarily offer fresh insights into biological mechanisms. Finally, while the subsequent additional efforts of the STM editorial staff are not to be discounted, the clarity of writing and coherence of argument presented within a submitted manuscript are likely to facilitate its progress through the challenge of peer review.

On Causes – Hippocrates, Aristotle, Robert Koch, and the Dread Pirate Roberts

Elazer R. Edelman
Circulation 2001;104:2509-2512

The idea of risk factors for vascular disease has evolved

  • from a dichotomous to continuous hazard analysis and
  • from the consideration of a few factors to
  • mechanistic investigation of many interrelated risks.

However, confusion still abounds regarding issues of association and causation. Originally, the simple presence of

  • tobacco abuse, hypertension, and/or hypercholesterolemia were tallied, and
  • the cumulative score was predictive of subsequent coronary artery disease.

Since then, dose responses have been defined for these and other factors and it has been suggested that almost 300 factors place patients at risk; these factors include elevations in plasma homocysteine.
 Recent studies shed interesting light on the mechanism of this potentially causal relationship, which was first noted in 1969.

Aside from putative effects on vessel wall dynamics, there is now direct evidence that homocysteine is atherogenic. Twenty-fold increases in plasma homocysteine achieved by dietary manipulation of apoE–/– mice increased aortic root lesion size 2-fold and produced a prolonged chronic inflammatory mural response accompanied by elevations in vascular cell adhesion molecule-1 (VCAM) and tumor necrosis factor-a (TNF-a).

In long term followup, homocysteine levels elevated by

  • dietary supplementation with methionine or homocysteine
  • promoted lesion size and plaque fibrosis in these
  • atherosclerosis-prone mice early in life, but without influencing ultimate plaque burden as the animals aged.

A number of mechanisms were proposed by which homocysteine achieved this effect, including

  • promotion of inflammation,
  • regulation of lipoprotein metabolism, and
  • modification of critical biochemical pathways and
  • metabolites including nitric oxide (NO).

See p 2569
In the present issue of Circulation,

Stühlinger et al 7 advance these mechanistic insights one critical step further by defining homocysteine’s effects at an enzymatic level.

The group led by Lentz published an association between levels of the

  • endogenous inhibitor of Nirtic Oxide synthase,
  • asymmetric dimethyl arginine (ADMA), and
  • homocysteine in cultured endothelial cells and in the serum of cynomolgus monkeys.

Such an association is interesting because the L-arginine–NO synthase pathway seems to be a critical component in the full range of endothelial cell biology and vascular dysfunction.

Stühlinger et al 7  now show that increased cultured endothelial cell elaboration of ADMA by homocysteine and its precursor L-methionine is associated with a dose-dependent impairment of the activity of endothelial dimethylarginine dimethylaminohydrolase (DDAH), the enzyme that degrades ADMA. Homocysteine directly inhibited DDAH activity in a cell-free system by targeting a critical sulfhydryl group on this enzyme.

Thus, one could envision that the balance of cardiovascular health and disease could well be determined by the ability of an intact Nirtic Oxide synthase system to overcome environmental, dietary, and even genetic factors.

In patients with altered enzymatic defense systems,

  • elevated homocysteine,
  • oxidized lipoproteins,
  • inflammation, and other
  • vasotoxins

may dominate even the most potent defense mechanisms.
These studies raise a number of issues.
Do we need to add to our list of established cardiovascular risk factors to accommodate new findings and associations?
Is there a final common pathway for all risk factors or perhaps even a unified factor theory into which all potential risks can be grouped?
And, as always, should we consider Nirtic Oxide at the core of this universality?
Finally, should we change our focus altogether and speak not of risk factors but of

  • genetic predisposition,
  • extent of biochemical aberration, and
  • degree of physical damage?

Some would view these remarkable success stories and the repeated association of hyperhomocyst(e)inemia with coronary, cerebral, and peripheral vascular disease and simply advocate for increased folic acid intake for all.

Indeed, this intervention of negligible cost and

  • insignificant side effect is already partially in place;
  • many foods are fortified with folate to prevent congenital neural tube defects.

This reader considers the seminal work by Vernon Young and Yves Ingenbleek on the relationship between

  • S8 and regions distant from lava flows in Asia and Indian subcontinents,
  • where they have determined hyperhomocysteinemia and the consequence associated with:
  • veganism (not voluntary)
  • impaired methyl donor reactions and transsulfuration pathways (not corrected by B12, folate)
  • loss of lean body mass due to the constant relationship of S:N (insufficient from plant sources)

What happens, when we fail to continue to pursue causality,

  • the linkage of biological significance or scientific plausibility with
  • epidemiologically or statistically significant association?

In medicine, risk becomes the likelihood that people without a disease will acquire the disease through contact with factors thought to increase disease risk.

All of these risk factors are then, by nature, imprecise and nonspecific.
 They are stochastic measures of what will happen to normal people who fall into particular measures of these parameters.

The daring may be willing to accept these risks, citing friend and foe who live well beyond or for far lesser times than anticipated by risk alone. Such concerns may well become moot if we can simultaneously identify patients at risk

  • by linking phenotype with genotype,
  • gene expression with protein elaboration, and
  • environmental exposures with the biochemical consequences and
  • direct anatomic aberrations they induce.

This kind of characterization may well replace a family history of arterial disease as a rough estimate of

  • genotype,
  • serum cholesterol as an indirect measure of the health of lipoprotein metabolism,
  • serum glucose as a crude determinant of the ravages of diabetes mellitus,
  • blood pressure measurement as a marker of long-standing endogenous exposure to altered flow, and
  • tobacco abuse as a maker of long-standing exposure to exogenous toxins.

Rather than identifying patients on the basis of their serum cholesterol, we will have a direct measure of their

  • LDL receptor number,
  • internalization rate,
  • macrophage content in the blood vessel wall,
  • metalloproteinase activity, etc.
  • insulin receptor metabolism,
  • oxidative state, and
  • glycated burden.
  • Serum glucose will similarly give way to these tests

Evaluating a new way to open clogged arteries: Computational model offers insight into mechanisms of drug-coated balloons.

A new study from MIT analyzes the potential usefulness of a new treatment that combines the benefits of angioplasty balloons and drug-releasing stents, but may pose fewer risks. With this new approach, a balloon is inflated in the artery for only a brief period, during which it releases a drug that prevents cells from accumulating and clogging the arteries over time.
While approved for limited use in Europe, these drug-coated balloons are still in development in the United States and have not received FDA approval. The MIT study, which models the behavior of the balloons, should help scientists optimize their performance and aid regulators in evaluating their effectiveness and safety.
“Until now, people who evaluate such technology could not distinguish hype from promise,” says Elazer Edelman, the Thomas D. and Virginia W. Cabot Professor of Health Sciences and Technology and senior author of the paper describing the study, which appeared online recently in the journal Circulation.
Lead author of the paper is Vijaya Kolachalama, a former MIT postdoc who is now a principal member of the technical staff at the Charles Stark Draper Laboratory.
Edelman’s lab is investigating a possible alternative to the current treatments: drug-coated balloons. “We’re trying to understand how and when this therapy could work and identify the conditions in which it may not,” Kolachalama says. “It has its merits; it has some disadvantages.”

Modeling drug release

The drug-coated balloons are delivered by a catheter and inflated at the narrowed artery for about 30 seconds, sometimes longer. During that time, the balloon coating, containing a drug such as Zotarolimus, is released from the balloon. The properties of the coating allow the drug to be absorbed in the body’s tissues. Once the drug is released, the balloon is removed.
In their new study, Kolachalama, Edelman and colleagues set out to rigorously characterize the properties of the drug-coated balloons. After performing experiments in tissue grown in the lab and in pigs, they developed a computer model that explains the dynamics of drug release and distribution. They found that factors such as the size of the balloon, the duration of delivery time, and the composition of the drug coating all influence how long the drug stays at the injury site and how effectively it clears the arteries.
One significant finding is that when the drug is released, some of it sticks to the lining of the blood vessels. Over time, that drug is slowly released back into the tissue, which explains why the drug’s effects last much longer than the initial 30-second release period.
“This is the first time we can explain the reasons why drug-coated balloons can work,” Kolachalama says. “The study also offers areas where people can consider thinking about optimizing drug transfer and delivery.”

http://circ.ahajournals.org/content/127/20/2047.short  
http://www.mit.edu/people/vbk/Circulation_2013.pdf 
http://www.sciencedaily.com/…13/05/130521121513.ht…    
Circulation, 2013; 127 (20): 2047 – 2055
http://dx.doi.org/10.1161/CIRCULATIONAHA.113.002051;

 

Conclusion

MIT’s Edelman’s Lab conducted the pioneering work in Vascular biology, animal models of drug eluting stents and was at the forefront of Empirical Molecular Cardiology in its studies in vascular physiology, biology and biomaterials for medical devices.

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The Heart Revolution By Kilmer McCully, Martha McCully

HarperCollinsPublishers, 1969

http://books.google.com/books?id=iYLbuZFxEt8C&pg=PR20&dq=New+York+Times+homocysteine+and+Cholesterol&hl=en&sa=X&ei=_0F7UfDRA8zB4APozIHQAQ&ved=0CEMQ6AEwAg

 

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Inhibition of ET-1, ETA and ETA-ETB, Induction of NO production, stimulation of eNOS and Treatment Regime with PPAR-gamma agonists (TZD): cEPCs Endogenous Augmentation for Cardiovascular Risk Reduction – A Bibliography

Aviva Lev-Ari, PhD, RN 10/4/2012

http://pharmaceuticalintelligence.com/2012/10/04/inhibition-of-et-1-eta-and-eta-etb-induction-of-no-production-and-stimulation-of-enos-and-treatment-regime-with-ppar-gamma-agonists-tzd-cepcs-endogenous-augmentation-for-cardiovascular-risk-reduc/

Positioning a Therapeutic Concept for Endogenous Augmentation of cEPCs — Therapeutic Indications for Macrovascular Disease: Coronary, Cerebrovascular and Peripheral

Aviva Lev-Ari, PhD, RN 8/29/2012

http://pharmaceuticalintelligence.com/2012/08/29/positioning-a-therapeutic-concept-for-endogenous-augmentation-of-cepcs-therapeutic-indications-for-macrovascular-disease-coronary-cerebrovascular-and-peripheral/

Cardiovascular Outcomes: Function of circulating Endothelial Progenitor Cells (cEPCs): Exploring Pharmaco-therapy targeted at Endogenous Augmentation of cEPCs

Aviva Lev-Ari, PhD, RN 8/28/2012

http://pharmaceuticalintelligence.com/2012/08/28/cardiovascular-outcomes-function-of-circulating-endothelial-progenitor-cells-cepcs-exploring-pharmaco-therapy-targeted-at-endogenous-augmentation-of-cepcs/

Endothelial Dysfunction, Diminished Availability of cEPCs, Increasing CVD Risk for Macrovascular Disease – Therapeutic Potential of cEPCs

Aviva Lev-Ari, PhD, R N 8/27/2012

http://pharmaceuticalintelligence.com/2012/08/27/endothelial-dysfunction-diminished-availability-of-cepcs-increasing-cvd-risk-for-macrovascular-disease-therapeutic-potential-of-cepcs/

Vascular Medicine and Biology: CLASSIFICATION OF FAST ACTING THERAPY FOR PATIENTS AT HIGH RISK FOR MACROVASCULAR EVENTS Macrovascular Disease – Therapeutic Potential of cEPCs

Aviva Lev-Ari, PhD, RN 8/24/2012

http://pharmaceuticalintelligence.com/2012/08/24/vascular-medicine-and-biology-classification-of-fast-acting-therapy-for-patients-at-high-risk-for-macrovascular-events-macrovascular-disease-therapeutic-potential-of-cepcs/

Cardiovascular Disease (CVD) and the Role of agent alternatives in endothelial Nitric Oxide Synthase (eNOS) Activation and Nitric Oxide Production

Aviva Lev-Ari, PhD, RN 7/19/2012

http://pharmaceuticalintelligence.com/2012/07/19/cardiovascular-disease-cvd-and-the-role-of-agent-alternatives-in-endothelial-nitric-oxide-synthase-enos-activation-and-nitric-oxide-production/

Resident-cell-based Therapy in Human Ischaemic Heart Disease: Evolution in the PROMISE of Thymosin beta4 for Cardiac Repair

Aviva Lev-Ari, PhD, RN 4/30/2012

http://pharmaceuticalintelligence.com/2012/04/30/93/

Triple Antihypertensive Combination Therapy Significantly Lowers Blood Pressure in Hard-to-Treat Patients with Hypertension and Diabetes

Aviva Lev-Ari, PhD, RN 5/29/2012

http://pharmaceuticalintelligence.com/2012/05/29/445/

Macrovascular Disease – Therapeutic Potential of cEPCs: Reduction Methods for CV Risk

Aviva Lev-Ari, PhD, RN 7/2/2012

http://pharmaceuticalintelligence.com/2012/07/02/macrovascular-disease-therapeutic-potential-of-cepcs-reduction-methods-for-cv-risk/

Mitochondria Dysfunction and Cardiovascular Disease – Mitochondria: More than just the “powerhouse of the cell”

Aviva Lev-Ari, PhD, RN 7/9/2012

http://pharmaceuticalintelligence.com/2012/07/09/mitochondria-more-than-just-the-powerhouse-of-the-cell/

Bystolic’s generic Nebivolol – positive effect on circulating Endothelial Proginetor Cells endogenous augmentation

Aviva Lev-Ari, PhD, RN 7/16/2012

http://pharmaceuticalintelligence.com/2012/07/16/bystolics-generic-nebivolol-positive-effect-on-circulating-endothilial-progrnetor-cells-endogenous-augmentation/

Arteriogenesis and Cardiac Repair: Two Biomaterials – Injectable Thymosin beta4 and Myocardial Matrix Hydrogel

Aviva Lev-Ari, PhD, RN 2/27/2013

http://pharmaceuticalintelligence.com/2013/02/27/arteriogenesis-and-cardiac-repair-two-biomaterials-injectable-thymosin-beta4-and-myocardial-matrix-hydrogel/

Cardiac Surgery Theatre in China vs. in the US: Cardiac Repair Procedures, Medical Devices in Use, Technology in Hospitals, Surgeons’ Training and Cardiac Disease Severity”

Aviva Lev-Ari, PhD, RN 1/8/2013

http://pharmaceuticalintelligence.com/2013/01/08/cardiac-surgery-theatre-in-china-vs-in-the-us-cardiac-repair-procedures-medical-devices-in-use-technology-in-hospitals-surgeons-training-and-cardiac-disease-severity/

Heart Remodeling by Design – Implantable Synchronized Cardiac Assist Device: Abiomed’s Symphony

Aviva Lev-Ari, PhD, RN 7/23/2012

http://pharmaceuticalintelligence.com/2012/07/23/heart-remodeling-by-design-implantable-synchronized-cardiac-assist-device-abiomeds-symphony/

Acute Chest Pain/ER Admission: Three Emerging Alternatives to Angiography and PCI

Aviva Lev-Ari, PhD, RN 3/10/2013

http://pharmaceuticalintelligence.com/2013/03/10/acute-chest-painer-admission-three-emerging-alternatives-to-angiography-and-pci/

Dilated Cardiomyopathy: Decisions on implantable cardioverter-defibrillators (ICDs) using left ventricular ejection fraction (LVEF) and Midwall Fibrosis: Decisions on Replacement using late gadolinium enhancement cardiovascular MR (LGE-CMR)

Aviva Lev-Ari, PhD, RN 3/10/2013
http://pharmaceuticalintelligence.com/2013/03/10/dilated-cardiomyopathy-decisions-on-implantable-cardioverter-defibrillators-icds-using-left-ventricular-ejection-fraction-lvef-and-midwall-fibrosis-decisions-on-replacement-using-late-gadolinium/

The Heart: Vasculature Protection – A Concept-based Pharmacological Therapy including THYMOSIN

Aviva Lev-Ari, PhD, RN 2/28/2013
http://pharmaceuticalintelligence.com/2013/02/28/the-heart-vasculature-protection-a-concept-based-pharmacological-therapy-including-thymosin/

FDA Pending 510(k) for The Latest Cardiovascular Imaging Technology

Aviva Lev-Ari, PhD, RN 1/28/2013
http://pharmaceuticalintelligence.com/2013/01/28/fda-pending-510k-for-the-latest-cardiovascular-imaging-technology/

PCI Outcomes, Increased Ischemic Risk associated with Elevated Plasma Fibrinogen not Platelet Reactivity

Aviva Lev-Ari, PhD, RN 1/10/2013
http://pharmaceuticalintelligence.com/2013/01/10/pci-outcomes-increased-ischemic-risk-associated-with-elevated-plasma-fibrinogen-not-platelet-reactivity/

The ACUITY-PCI score: Will it Replace Four Established Risk Scores — TIMI, GRACE, SYNTAX, and Clinical SYNTAX

Aviva Lev-Ari, PhD, RN
http://pharmaceuticalintelligence.com/2013/01/03/the-acuity-pci-score-will-it-replace-four-established-risk-scores-timi-grace-syntax-and-clinical-syntax/

Coronary artery disease in symptomatic patients referred for coronary angiography: Predicted by Serum Protein Profiles

Aviva Lev-Ari, PhD, RN
http://pharmaceuticalintelligence.com/2012/12/29/coronary-artery-disease-in-symptomatic-patients-referred-for-coronary-angiography-predicted-by-serum-protein-profiles/

Heart Renewal by pre-existing Cardiomyocytes: Source of New Heart Cell Growth Discovered

Aviva Lev-Ari, PhD, RN 12/23/2012
http://pharmaceuticalintelligence.com/2012/12/23/heart-renewal-by-pre-existing-cardiomyocytes-source-of-new-heart-cell-growth-discovered/

Cardiovascular Risk Inflammatory Marker: Risk Assessment for Coronary Heart Disease and Ischemic Stroke – Atherosclerosis.

Aviva Lev-Ari, PhD, RN 10/30/2012
http://pharmaceuticalintelligence.com/2012/10/30/cardiovascular-risk-inflammatory-marker-risk-assessment-for-coronary-heart-disease-and-ischemic-stroke-atherosclerosis/

To Stent or Not? A Critical Decision

Aviva Lev-Ari, PhD, RN 10/23/2012
http://pharmaceuticalintelligence.com/2012/10/23/to-stent-or-not-a-critical-decision/

New Definition of MI Unveiled, Fractional Flow Reserve (FFR)CT for Tagging Ischemia

Aviva Lev-Ari, PhD, RN 8/27/2012
http://pharmaceuticalintelligence.com/2012/08/27/new-definition-of-mi-unveiled-fractional-flow-reserve-ffrct-for-tagging-ischemia/

Ethical Considerations in Studying Drug Safety — The Institute of Medicine Report

Aviva Lev-Ari, PhD, RN 8/23/2012
http://pharmaceuticalintelligence.com/2012/08/23/ethical-considerations-in-studying-drug-safety-the-institute-of-medicine-report/

New Drug-Eluting Stent Works Well in STEMI

Aviva Lev-Ari, PhD, RN 8/22/2012
http://pharmaceuticalintelligence.com/2012/08/22/new-drug-eluting-stent-works-well-in-stemi/

Expected New Trends in Cardiology and Cardiovascular Medical Devices

Aviva Lev-Ari, PhD, RN 8/17/2012
http://pharmaceuticalintelligence.com/2012/08/17/expected-new-trends-in-cardiology-and-cardiovascular-medical-devices/

Coronary Artery Disease – Medical Devices Solutions: From First-In-Man Stent Implantation, via Medical Ethical Dilemmas to Drug Eluting Stents

Aviva Lev-Ari, PhD, RN 8/13/2012

http://pharmaceuticalintelligence.com/2012/08/13/coronary-artery-disease-medical-devices-solutions-from-first-in-man-stent-implantation-via-medical-ethical-dilemmas-to-drug-eluting-stents/

Percutaneous Endocardial Ablation of Scar-Related Ventricular Tachycardia

Aviva Lev-Ari, PhD, RN 7/18/2012

http://pharmaceuticalintelligence.com/2012/07/18/percutaneous-endocardial-ablation-of-scar-related-ventricular-tachycardia/

Competition in the Ecosystem of Medical Devices in Cardiac and Vascular Repair: Heart Valves, Stents, Catheterization Tools and Kits for Open Heart and Minimally Invasive Surgery (MIS)

Aviva Lev-Ari, PhD, RN 6/22/2012

http://pharmaceuticalintelligence.com/2012/06/22/competition-in-the-ecosystem-of-medical-devices-in-cardiac-and-vascular-repair-heart-valves-stents-catheterization-tools-and-kits-for-open-heart-and-minimally-invasive-surgery-mis/

Global Supplier Strategy for Market Penetration & Partnership Options (Niche Suppliers vs. National Leaders) in the Massachusetts Cardiology & Vascular Surgery Tools and Devices Market for Cardiac Operating Rooms and Angioplasty Suites

Aviva Lev-Ari, PhD, RN 6/22/2012

http://pharmaceuticalintelligence.com/2012/06/22/global-supplier-strategy-for-market-penetration-partnership-options-niche-suppliers-vs-national-leaders-in-the-massachusetts-cardiology-vascular-surgery-tools-and-devices-market-for-car/

Blood_Vessels

Blood_Vessels (Photo credit: shoebappa)

Visceral Myopathy in Statins

Visceral Myopathy in Statins (Photo credit: Snipergirl)

Medical science has advanced significantly sin...

Medical science has advanced significantly since 1507, when Leonardo da Vinci drew this diagram of the internal organs and vascular systems of a woman. (Photo credit: Wikipedia)

English: Lee Hood, MD, PhD, President and Co-f...

English: Lee Hood, MD, PhD, President and Co-found of the Institute for Systems Biology (Photo credit: Wikipedia)

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Economic Toll of Heart Failure in the US: Forecasting the Impact of Heart Failure in the United States – A Policy Statement From the American Heart Association

Reporter: Aviva Lev-Ari, PhD, RN

 

  • AHA Policy Statement

Forecasting the Impact of Heart Failure in the United States

A Policy Statement From the American Heart Association

  1. Paul A. Heidenreich, MD, MS, FAHA, Chair,

  2. Nancy M. Albert, PhD, RN, FAHA,
  3. Larry A. Allen, MD, MHS,
  4. David A. Bluemke, MD, PhD, FAHA,
  5. Javed Butler, MD, MPH, FAHA,
  6. Gregg C. Fonarow, MD, FAHA,
  7. John S. Ikonomidis, MD, PhD, FRCS(C), FAHA,
  8. Olga Khavjou, MA,
  9. Marvin A. Konstam, MD,
  10. Thomas M. Maddox, MD, MSc,
  11. Graham Nichol, MD, MPH, FRCP(C), FAHA,
  12. Michael Pham, MD, MPH,
  13. Ileana L. Piña, MD, MPH, FAHA,
  14. Justin G. Trogdon, PhD and
  15. on behalf of the American Heart Association Advocacy Coordinating Committee:
  • Council on Arteriosclerosis,
  • Thrombosis and Vascular Biology,
  • Council on Cardiovascular Radiology and Intervention,
  • Council on Clinical Cardiology,
  • Council on Epidemiology and Prevention, and
  • Stroke Council

Abstract

Background—Heart failure (HF) is an important contributor to both the burden and cost of national healthcare expenditures, with more older Americans hospitalized for HF than for any other medical condition. With the aging of the population, the impact of HF is expected to increase substantially.

Methods and Results—We estimated future costs of HF by adapting a methodology developed by the American Heart Association to project the epidemiology and future costs of HF from 2012 to 2030 without double counting the costs attributed to comorbid conditions. The model assumes that HF prevalence will remain constant by age, sex, and race/ethnicity and that rising costs and technological innovation will continue at the same rate.

By 2030,

  • >8 million people in the United States (1 in every 33) will have HF.
  • Between 2012 and 2030, real (2010$) total direct medical costs of HF are projected to increase from $21 billion to $53 billion.
  • Total costs, including indirect costs for HF, are estimated to increase from $31 billion in 2012 to $70 billion in 2030.
  • If one assumes all costs of cardiac care for HF patients are attributable to HF (no cost attribution to comorbid conditions), the 2030 projected cost estimates of treating patients with HF will be 3-fold higher ($160 billion in direct costs).

Conclusions—The estimated prevalence and cost of care for HF will increase markedly because of aging of the population. Strategies to prevent HF and improve the efficiency of care are needed.

Key Words:

http://circheartfailure.ahajournals.org/content/early/2013/04/24/HHF.0b013e318291329a.abstract

15 page PDF, at the below link

http://circheartfailure.ahajournals.org/content/early/2013/04/24/HHF.0b013e318291329a.full.pdf+html?sid=ad1efd74-a4e1-45b0-8a47-350e85435487

REFERENCE

Four Policy Statement From the American Heart Association

  1. AHA Policy StatementForecasting the Impact of Heart Failure in the United States: A Policy Statement From the American Heart Association

    • Paul A. Heidenreich,
    • Nancy M. Albert,
    • Larry A. Allen,
    • David A. Bluemke,
    • Javed Butler,
    • Gregg C. Fonarow,
    • John S. Ikonomidis,
    • Olga Khavjou,
    • Marvin A. Konstam,
    • Thomas M. Maddox,
    • Graham Nichol,
    • Michael Pham,
    • Ileana L. Piña,
    • and Justin G. Trogdon

    Circ Heart Fail. 2013;published online before print April 24 2013,doi:10.1161/HHF.0b013e318291329a

    …American Heart Association. Expert peer review of AHA Scientific Statements is conducted by the AHA Office of Science Operations…and improve the efficiency of care are needed. AHA Scientific Statements|heart failure|
  2. Select this article

    Special ReportStatement Regarding the Pre and Post Market Assessment of Durable, Implantable Ventricular Assist Devices in the United States

    • Michael A. Acker,
    • Francis D. Pagani,
    • Wendy Gattis Stough,
    • Douglas L. Mann,
    • Mariell Jessup,
    • Robert Kormos,
    • Mark S. Slaughter,
    • Timothy Baldwin,
    • Lynne Stevenson,
    • Keith D. Aaronson,
    • Leslie Miller,
    • David Naftel,
    • Clyde Yancy,
    • Joseph Rogers,
    • Jeffrey Teuteberg,
    • Randall C. Starling,
    • Bartley Griffith,
    • Steven Boyce,
    • Stephen Westaby,
    • Elizabeth Blume,
    • Peter Wearden,
    • Robert Higgins,
    • and Michael Mack

    Circ Heart Fail. 2013;6:e1-e11, published online before print November 12 2012,doi:10.1161/HHF.0b013e318279f6b5

    …wolterskluwer.com . Expert peer review of AHA Scientific Statements is conducted by the AHA Office of Science Operations…of Mechanically Assisted Circulatory Support.AHA Scientific Statements|heart-assist device|heart failure|BTC…
  3. Select this article

    Special ReportStatement Regarding the Pre and Post Market Assessment of Durable, Implantable Ventricular Assist Devices in the United States: Executive Summary

    • Michael A. Acker,
    • Francis D. Pagani,
    • Wendy Gattis Stough,
    • Douglas L. Mann,
    • Mariell Jessup,
    • Robert Kormos,
    • Mark S. Slaughter,
    • Timothy Baldwin,
    • Lynne Stevenson,
    • Keith D. Aaronson,
    • Leslie Miller,
    • David Naftel,
    • Clyde Yancy,
    • Joseph Rogers,
    • Jeffrey Teuteberg,
    • Randall C. Starling,
    • Bartley Griffith,
    • Steven Boyce,
    • Stephen Westaby,
    • Elizabeth Blume,
    • Peter Wearden,
    • Robert Higgins,
    • and Michael Mack

    Circ Heart Fail. 2013;6:145-150, published online before print November 12 2012,doi:10.1161/HHF.0b013e318279f55d

    …wolterskluwer.com . Expert peer review of AHA Scientific Statements is conducted by the AHA Office of Science Operations…of Mechanically Assisted Circulatory Support.AHA Scientific Statements|heart-assist device|heart failure| Background…
  4. Select this article

    ACCF/AHA/HFSA Data and Survey ReportACCF/AHA/HFSA 2011 Survey Results: Current Staffing Profile of Heart Failure Programs, Including Programs That Perform Heart Transplant and Mechanical Circulatory Support Device Implantation: A Report of the ACCF Heart Failure and Transplant Committee, AHA Heart Failure and Transplantation Committee, and Heart Failure Society of America

    • Mariell Jessup,
    • Nancy M. Albert,
    • David E. Lanfear,
    • JoAnn Lindenfeld,
    • Barry M. Massie,
    • Mary Norine Walsh,
    • and Mark J. Zucker

    Circ Heart Fail. 2011;4:378-387, published online before print April 4 2011,doi:10.1161/HHF.0b013e3182186210

    …hired for a given practice volume. These survey results are an initial step in developing such standards. AHA Scientific Statements|heart failure|heart transplant|mechanical circulatory support device|staffing profile| 1. Introduction…

http://circheartfailure.ahajournals.org/search?fulltext=AHA+Scientific+Statements&sortspec=date&submit=Submit&andorexactfulltext=phrase

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Reporter: Aviva Lev-Ari, PhD, RN

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Reporter: Aviva Lev-Ari, PhD, RN

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Genotype-based Analysis for Cancer Therapy using Large-scale Data Modeling: Nayoung Kim, PhD(c)

Reporter: Aviva Lev-Ari, PhD, RN

Systems Pharmacology – Pathways to Patient Response @ BioIT World, April 9-11, 2013, World Trade Center, Boston, MA

 

Nayoung Kim, PhD(c)’s presentation at the conference is to be viewed at the link, below

http://www.chiresource.com/BIT-05-23/Presentations/NPC/Kim_Nayoung.pdf

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