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Posts Tagged ‘Intensive care unit’


Reporter: Aviva Lev-Ari, PhD, RN

Dr. Lev-Ari had 100 hours at the Coronary Care Unit at the Brigham and Women’s Hospital in Boston in 2006, and four month at the ICU at Faulkner Hospital, Boston in 2007.

A Randomized Trial of Nighttime Physician Staffing in an Intensive Care Unit

Meeta Prasad Kerlin, M.D., M.S.C.E., Dylan S. Small, Ph.D., Elizabeth Cooney, M.P.H., Barry D. Fuchs, M.D., Lisa M. Bellini, M.D., Mark E. Mikkelsen, M.D., M.S.C.E., William D. Schweickert, M.D., Rita N. Bakhru, M.D., Nicole B. Gabler, Ph.D., M.H.A., Michael O. Harhay, M.P.H., John Hansen-Flaschen, M.D., and Scott D. Halpern, M.D., Ph.D.

May 20, 2013DOI: 10.1056/NEJMoa1302854

BACKGROUND

Increasing numbers of intensive care units (ICUs) are adopting the practice of nighttime intensivist staffing despite the lack of experimental evidence of its effectiveness.

Full Text of Background…

METHODS

We conducted a 1-year randomized trial in an academic medical ICU of the effects of nighttime staffing with in-hospital intensivists (intervention) as compared with nighttime coverage by daytime intensivists who were available for consultation by telephone (control). We randomly assigned blocks of 7 consecutive nights to the intervention or the control strategy. The primary outcome was patients’ length of stay in the ICU. Secondary outcomes were patients’ length of stay in the hospital, ICU and in-hospital mortality, discharge disposition, and rates of readmission to the ICU. For length-of-stay outcomes, we performed time-to-event analyses, with data censored at the time of a patient’s death or transfer to another ICU.

Full Text of Methods…

RESULTS

A total of 1598 patients were included in the analyses. The median Acute Physiology and Chronic Health Evaluation (APACHE) III score (in which scores range from 0 to 299, with higher scores indicating more severe illness) was 67 (interquartile range, 47 to 91), the median length of stay in the ICU was 52.7 hours (interquartile range, 29.0 to 113.4), and mortality in the ICU was 18%. Patients who were admitted on intervention days were exposed to nighttime intensivists on more nights than were patients admitted on control days (median, 100% of nights [interquartile range, 67 to 100] vs. median, 0% [interquartile range, 0 to 33]; P<0.001). Nonetheless, intensivist staffing on the night of admission did not have a significant effect on the length of stay in the ICU (rate ratio for the time to ICU discharge, 0.98; 95% confidence interval [CI], 0.88 to 1.09; P=0.72), ICU mortality (relative risk, 1.07; 95% CI, 0.90 to 1.28), or any other end point. Analyses restricted to patients who were admitted at night showed similar results, as did sensitivity analyses that used different definitions of exposure and outcome. 

CONCLUSIONS

In an academic medical ICU in the United States, nighttime in-hospital intensivist staffing did not improve patient outcomes. (Funded by University of Pennsylvania Health System and others; ClinicalTrials.gov number, NCT01434823.)

RESULTS

The study period included 352 nights, 175 of which (50%) were randomly assigned to the intervention; nighttime intensivists staffed 166 (95%) of the intervention nights. A total of 1598 patients were included in the analyses (Figure 1), of whom 970 (61%) were admitted at night (Table 1TABLE 1Characteristics of the Study Population., and Table S1 in the Supplementary Appendix). The median APACHE III score (with scores ranging from 0 to 299 and higher scores indicating more severe illness) was 67 (interquartile range, 47 to 91), and the median length of stay in the ICU was 52.7 hours (interquartile range, 29.0 to 113.4). A total of 381 patients (24%) died in the hospital, including 293 (18%) who died in the ICU.

Nighttime intensivists were generally younger than the daytime intensivists (Table S2 in the Supplementary Appendix), although most (82%) also worked as daytime intensivists during the study period. Nighttime intensivists completed post-shift questionnaires on 116 intervention nights (66%) and reported evaluating a median of 4 (interquartile range, 3 to 5) new patients and 2 (interquartile range, 1 to 3) previously admitted patients per night (Table S3 in the Supplementary Appendix). During the control nights, the at-home intensivists received a median of 2 (interquartile range, 1 to 3) calls each night, and the critical care fellows received a median of 2 (interquartile range, 0 to 3) calls each night (Table S4 in the Supplementary Appendix).

Patients who were admitted on intervention days had greater cumulative exposure to nighttime intensivists than did patients who were admitted on control days (median, 100% of nights [interquartile range, 67 to 100] vs. median, 0% [interquartile range, 0 to 33]; P<0.001). Staffing with nighttime intensivists did not have a significant effect on the length of stay in the ICU (rate ratio for ICU discharge, 0.98; 95% confidence interval [CI], 0.88 to 1.09; P=0.72) (Figure 2AFIGURE 2Kaplan–Meier Curves for Time to Discharge from the ICU.). In this study, the rate ratio refers to the instantaneous rate of discharge from the ICU in the intervention group divided by the instantaneous rate of discharge from the ICU in the control group, such that a rate ratio greater than 1 would indicate that the intervention shortened the time to ICU discharge. The findings were similar in analyses that were restricted to patients admitted at night (hazard ratio, 0.98; 95% CI, 0.84 to 1.13; P=0.74) (Figure 2B), and in several sensitivity analyses (Table 2TABLE 2Primary, Restricted, and Sensitivity Analyses of the Effect of the Intervention.). The results were also similar in the rank-based analysis of length of stay in the ICU, in which deaths were coded as the longest possible length of stay (P=0.51).

Nighttime intensivist staffing also had no significant effect on the length of stay in the hospital (median, 174 hours [interquartile range, 91 to 361] in the intervention group vs. 166 hours [interquartile range, 84 to 328] in the control group; rate ratio, 0.91; 95% CI, 0.82 to 1.02; P=0.12) or on ICU mortality, hospital mortality, readmission to the ICU among ICU survivors, or discharge to home (Table 3TABLE 3Secondary Outcomes.). Analyses that were restricted to patients admitted at night also showed no significant effects of nighttime intensivist staffing.

The patients’ APACHE III score did not modify the effect of the intervention on the length of stay in the ICU (P=0.28 for interaction) (Table S5 in theSupplementary Appendix). The effects of the intervention on the length of stay in the ICU were also similar during periods in which residents were more experienced and those in which residents were less experienced (Table S6 in the Supplementary Appendix). There was significant heterogeneity in the effect of the intervention on readmission to the ICU during the two periods (P=0.03 for interaction). However, the intervention was not associated with significantly fewer readmissions during the inexperienced-resident period (relative risk for readmission, 0.58; 95% CI, 0.10 to 3.39), and the heterogeneity was due, in part, to a nonsignificantly higher readmission rate with the intervention during the experienced-resident period (relative risk for readmission, 1.94; 95% CI, 0.87 to 4.30).

The Web-based surveys were completed by 41 of 91 eligible residents (45%). A majority of residents reported that the presence of nighttime intensivists improved the quality of care as perceived by the resident, provided support to residents, permitted appropriate resident autonomy, and improved the educational experience (Table S7 in the Supplementary Appendix).

DISCUSSION

In this single-center randomized trial of in-hospital nighttime intensivist staffing in an academic medical center in the United States, we found no evidence that this staffing model, as compared with nighttime telephone availability of the daytime intensivist, had a significant effect on length of stay in the ICU or hospital, ICU or in-hospital mortality, readmission to the ICU, or the probability of discharge to home. We also observed no significant benefits of the intervention in subgroups of patients for whom we had hypothesized the greatest effects: patients admitted at night, those with the most severe illness at the time of ICU admission, and those admitted during the period when the residents were least experienced. These findings are consistent with a multicenter observational study that suggested that in hospitals with high-intensity daytime intensivist staffing, the presence of nighttime intensivists did not reduce mortality.14 The current trial extends this work by removing the potential for ICU-level and patient-level confounding and by documenting the lack of significant effects on a broad range of outcomes.

There are several possible explanations for the lack of significant benefit of nighttime intensivists in this study. First, there may be limited room for improvement in ICUs that have daytime intensivist staffing, particularly if the benefits of daytime intensivist staffing derive from better ICU-wide processes of care.9,28 Second, nighttime intensivist staffing may be associated with discontinuity of care for some patients, offsetting benefits for other patients. Third, in the staffing model and setting that we studied, bedside intensivists may not add to the quality of care provided by well-trained resident physicians who have telephone access to intensivists. Finally, nighttime intensivists may truly have an effect on mortality in a small number of patients, but such patients may be so few in number that detecting these benefits would require a much larger study. Future research that investigates these and other potential explanations could inform broader debates about the best ways to use a limited intensivist workforce.29,30

We also found that most residents believed that nighttime intensivists improved their educational experience and provided desirable support for decision making. These findings are tempered by the positive framing of the questions in our survey and the modest response rate. Nonetheless, academic centers may wish to consider residents’ perspectives in choosing to adopt or retain this staffing model.

A strength of this randomized trial is that it took place in an ICU in which 61% of admissions occurred at night. If nighttime intensivists were effective, it is likely that they would be particularly effective in an ICU with such a large nighttime workload. In addition, by randomly assigning weeks rather than individual nights, we ensured that our contrast would meaningfully represent the presence or absence of year-round nighttime intensivist staffing.

An important limitation of this study is that it was performed in a single, academic medical ICU in the United States that had round-the-clock coverage by reasonably well-trained residents. Our results may be generalizable to U.S. academic ICUs with high-intensity daytime staffing, which have been among the early adopters of nighttime intensivist staffing in the United States. However, our study does not address whether nighttime intensivist staffing may provide benefits in community ICUs, ICUs without high-intensity daytime staffing, ICUs with fewer or less well-trained residents, or ICUs in other countries.

Second, our nighttime workforce may differ with respect to age, frequency of shifts, or other characteristics from workforces that are employed or considered elsewhere. It is uncertain whether different nighttime staffing models would affect patient outcomes.

Third, although we evaluated several outcomes, the presence of nighttime intensivists may affect other outcomes such as physician burn-out, staff satisfaction, patient and family experiences, objectively measured educational outcomes, and the incidence of malpractice claims. In addition, outcomes external to the ICU were not measured, such as the possible role of nighttime intensivists in helping hospitals meet quality benchmarks.15

In summary, this randomized trial in an ICU with high-intensity staffing during the day failed to identify benefits to adding intensivists at night. The compelling face validity of nighttime intensivist staffing has probably spurred the widespread adoption of this staffing model.8,10 However, nighttime intensivist staffing may also be one of several expensive medical practices that have been adopted without a supportive evidence base.31 Because the adoption of nighttime intensivist staffing by hospitals with plentiful resources may siphon intensivists away from hospitals with fewer resources,17,18 rigorous evaluation of the model is needed in settings that were not evaluated in this study.

Supported by the University of Pennsylvania Health System and by pilot grants (to Dr. Halpern) from the Roybal Center for Behavioral Economics and Health, National Institute on Aging, National Institutes of Health (P30AG034546), and the Department of Medical Ethics and Health Policy, University of Pennsylvania.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

This article was published on May 20, 2013 at NEJM.org.

http://www.nejm.org/doi/full/10.1056/NEJMoa1302854?query=OF#t=articleDiscussion

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A Second Look at the Transthyretin Nutrition Inflammatory Conundrum

Subtitle: Transthyretin and the Systemic Inflammatory Response

 

Author and Curator: Larry H. Bernstein, MD, FACP, Clinical Pathologist, Biochemist, and Transfusion Physician

 

Brief introduction

Transthyretin  (also known as prealbumin) has been widely used as a biomarker for identifying protein-energy malnutrition (PEM) and for monitoring the improvement of nutritional status after implementing a nutritional intervention by enteral feeding or by parenteral infusion. This has occurred because transthyretin (TTR) has a rapid removal from the circulation in 48 hours and it is readily measured by immunometric assay. Nevertheless, concerns have been raised about the use of TTR in the ICU setting, which prompted a review of the  benefit of using this test in acute and chronic care. TTR is easily followed in the underweight and the high risk populations in an ambulatory setting, which has a significant background risk of chronic diseases. It is sensitive to the systemic inflammatory response syndrome (SIRS), and needs to be understood in the context of acute illness to be used effectively. There are a number of physiologic changes associated with SIRS and the injury/repair process that affect TTR. The most important point is that in the context of an ICU setting, the contribution of TTR is significant in a complex milieu.  A much better understanding of the significance of this program has emerged from studies of nitrogen and sulfur in health and disease.

Transthyretin protein structure

Transthyretin protein structure (Photo credit: Wikipedia)

Age-standardised disability-adjusted life year...

Age-standardised disability-adjusted life year (DALY) rates from Protein-energy malnutrition by country (per 100,000 inhabitants). (Photo credit: Wikipedia)

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The systemic inflammatory response syndrome C-reactive protein and transthyretin conundrum.
Larry H Bernstein
Clin Chem Lab Med 2007; 45(11):0
ICID: 939932
Article type: Editorial

The Transthyretin Inflammatory State Conundrum
Larry H. Bernstein
Current Nutrition & Food Science, 2012, 8, 00-00

Keywords: Tranthyretin (TTR), systemic inflammatory response syndrome (SIRS), protein-energy malnutrition (PEM), C- reactive protein, cytokines, hypermetabolism, catabolism, repair.

Transthyretin has been widely used as a biomarker for identifying protein-energy malnutrition (PEM) and for monitoring the improvement of nutritional status after implementing a nutritional intervention by enteral feeding or by parenteral infusion. This has occurred because transthyretin (TTR) has a rapid removal from the circulation in 48 hours and it is readily measured by immunometric assay. Nevertheless, concerns have been raised about the use of TTR in the ICU setting, which prompts a review of the actual benefit of using this test in a number of settings. TTR is easily followed in the underweight and the high risk populations in an ambulatory setting, which has a significant background risk of chronic diseases. It is sensitive to the systemic inflammatory response syndrome (SIRS), and needs to be understood in the context of acute illness to be used effectively.

There are a number of physiologic changes associated with SIRS and the injury/repair process that affect TTR and  in the context of an ICU setting, the contribution of TTR is essential.  The only consideration is the timing of initiation since the metabolic burden is sufficiently high that a substantial elevation is expected in the first 3 days post admission, although the level of this biomarker is related to the severity of injury. Despite the complexity of the situation, TTR is not to be considered a test “for all seasons”. In the context of age, prolonged poor meal intake, chronic or acute illness, TTR needs to be viewed in a multivariable lens, along with estimated lean body mass, C-reactive protein, the absolute lymphocyte count, presence of neutrophilia, and perhaps procalcitonin if there is remaining uncertainty. Furthermore, the reduction of risk of associated complication requires a systematized approach to timely identification, communication, and implementation of a suitable treatment plan.

The most important point is that in the context of an ICU setting, the contribution of TTR is significant in a complex milieu.

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Title: The Automated Malnutrition Assessment
Accepted 29 April 2012. http://www.nutritionjrnl.com. Nutrition (2012), doi:10.1016/j.nut.2012.04.017.
Authors: Gil David, PhD; Larry Howard Bernstein, MD; Ronald R Coifman, PhD
Article Type: Original Article

Keywords: Network Algorithm; unsupervised classification; malnutrition screening; protein energy malnutrition (PEM); malnutrition risk; characteristic metric; characteristic profile; data characterization; non-linear differential diagnosis

We have proposed an automated nutritional assessment (ANA) algorithm that provides a method for malnutrition risk prediction with high accuracy and reliability.  The problem of rapidly identifying risk and severity of malnutrition is crucial for minimizing medical and surgical complications. These are not easily performed or adequately expedited. We characterized for each patient a unique profile and mapped similar patients into a classification. We also found that the laboratory parameters were sufficient for the automated risk prediction.

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Title: The Increasing Role for the Laboratory in Nutritional Assessment
Article Type: Editorial
Section/Category: Clinical Investigation
Accepted 22 May 2012. http://www.elsevier.com/locate/clinbiochem.
Clin Biochem (2012), doi:10.1016/j.clinbiochem.2012.05.024
Keywords: Protein Energy Malnutrition; Nutritional Screening; Laboratory Testing
Author: Dr. Larry Howard Bernstein, MD

The laboratory role in nutritional management of the patient has seen remarkable growth while there have been dramatic changes in technology over the last 25 years, and it is bound to be transformative in the near term. This editorial is an overview of the importance of the laboratory as an active participant in nutritional care.

The discipline emerged divergently along separate paths with unrelated knowledge domains in physiological chemistry, pathology, microbiology, immunology and blood cell recognition, and then cross-linked emerging into clinical biochemistry, hematology-oncology, infectious diseases, toxicology and therapeutics, genetics, pharmacogenomics, translational genomics and clinical diagnostics.

In reality, the more we learn about nutrition, the more we uncover of metabolic diversity of individuals, the family, and societies in adapting and living in many unique environments and the basic reactions, controls, and responses to illness. This course links metabolism to genomics and individual diversity through metabolomics, which will be enlightened by chemical and bioenergetic insights into biology and translated into laboratory profiling.

Vitamin deficiencies were discovered as clinical entities with observed features as a result of industrialization (rickets and vitamin D deficiency) and mercantile trade (scurvy and vitamin C)[2].  Advances in chemistry led to the isolation of each deficient “substance”.  In some cases, a deficiency of a vitamin and what is later known as an “endocrine hormone” later have confusing distinctions (vitamin D, and islet cell insulin).

The accurate measurement and roles of trace elements, enzymes, and pharmacologic agents was to follow within the next two decades with introduction of atomic absorption, kinetic spectrophotometers, column chromatography and gel electrophoresis.  We had fully automated laboratories by the late 1960s, and over the next ten years basic organ panels became routine.   This was a game changer.

Today child malnutrition prevalence is 7 percent of children under the age of 5 in China, 28 percent in sub-Saharan African, and 43 percent in India, while under-nutrition is found mostly in rural areas with 10 percent of villages and districts accounting for 27-28 percent of all Indian underweight children. This may not be surprising, but it is associated with stunting and wasting, and it has not receded with India’s economic growth. It might go unnoticed viewed alongside a growing concurrent problem of worldwide obesity.

The post WWII images of holocaust survivors awakened sensitivity to nutritional deprivation.

In the medical literature, Studley [HO Studley.  Percentage of weight loss. Basic Indicator of surgical risk in patients with chronic peptic ulcer.  JAMA 1936; 106(6):458-460.  doi:10.1001/jama.1936.02770060032009] reported the association between weight loss and poor surgical outcomes in 1936.  Ingenbleek et al [Y Ingenbleek, M De Vissher, PH De Nayer. Measurement of prealbumin as index of protein-calorie malnutrition. Lancet 1972; 300[7768]: 106-109] first reported that prealbumin (transthyretin, TTR) is a biomarker for malnutrition after finding very low TTR levels in African children with Kwashiorkor in 1972, which went unnoticed for years.  This coincided with the demonstration by Stanley Dudrick  [JA Sanchez, JM Daly. Stanley Dudrick, MD. A Paradigm ShiftArch Surg. 2010; 145(6):512-514] that beagle puppies fed totally through a catheter inserted into the superior vena cava grew, which method was then extended to feeding children with short gut.  Soon after Bistrian and Blackburn [BR Bistrian, GL Blackburn, E Hallowell, et al. Protein status of general surgical patients. JAMA 1974; 230:858; BR Bistrian, GL Blackburn, J Vitale, et al. Prevalence of malnutrition in general medicine patients, JAMA, 1976, 235:1567] showed that malnourished hospitalized medical and surgical patients have increased length of stay, increased morbidity, such as wound dehiscence and wound infection, and increased postoperative mortality, later supported by many studies.

Michael Meguid,MD, PhD, founding editor of Nutrition [Elsevier] held a nutrition conference “Skeleton in the Closet – 20 years later” in Los Angeles in 1995, at which a Beckman Prealbumin Roundtable was held, with Thomas Baumgartner and Michael M Meguid as key participants.  A key finding was that to realize the expected benefits of a nutritional screening and monitoring program requires laboratory support. A Ross Roundtable, chaired by Dr. Lawrence Kaplan, resulted in the first Standard of Laboratory Practice Document of the National Academy of Clinical Biochemists on the use of the clinical laboratory in nutritional support and monitoring. Mears then showed a real benefit to a laboratory interactive program in nutrition screening based on TTR [E Mears. Outcomes of continuous process improvement of a nutritional care program incorporating serum prealbumin measurements. Nutrition 1996; 12 (7/8): 479-484].

A later Ross Roundtable on Quality in Nutritional Care included a study of nutrition screening and time to dietitian intervention organized by Brugler and Di Prinzio that showed a decreased length of hospital stay with $1 million savings in the first year (which repeated), which included reduced cost for dietitian evaluations and lower complication rates.

Presentations were made at the 1st International Transthyretin Congress in Strasbourg, France by Mears [E Mears.  The role of visceral protein markers in protein calorie malnutrition. Clin Chem Lab Med 2002; 40:1360-1369] on the impact of TTR in screening for PEM in a public hospital in Louisiana, and by Potter [MA Potter, G Luxton. Prealbumin measurement as a screening tool for patients with protein calorie malnutrition in emergency hospital admissions: a pilot study.  Clin Invest Med. 1999; 22(2):44-52] that indicated a 17% in-hospital mortality rate in a Canadian hospital for patients with PCM compared with 4% without PCM (p < 0.02), while only 42% of patients with PCM received nutritional supplementation. Cost analysis of screening with prealbumin level projected a saving of $414 per patient screened.  Ingenbleek and Young [Y Ingenbleek, VR Young.  Significance of transthyretin in protein metabolism.  Clin Chem Lab Med. 2002; 40(12):1281–1291.  ISSN (Print) 1434-6621, DOI: 10.1515/ CCLM.2002.222, December 2002. published online: 01/06/2005] tied the TTR to basic effects reflected in protein metabolism.

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Transthyretin as a marker to predict outcome in critically ill patients.
Arun Devakonda, Liziamma George, Suhail Raoof, Adebayo Esan, Anthony Saleh, Larry H Bernstein
Clin Biochem 2008; 41(14-15):1126-1130
ICID: 939927
Article type: Original article

TTR levels correlate with patient outcomes and are an accurate predictor of patient recovery in non-critically ill patients, but it is uncertain whether or not TTR level correlates with level of nutrition support and outcome in critically ill patients. This issue has been addressed only in critically ill patients on total parenteral nutrition and there was no association reported with standard outcome measures. We revisit this in all patients admitted to a medical intensive care unit.

Serum TTR was measured on the day of admission, day 3 and day 7 of their ICU stay. APACHE II and SOFA score was assessed on the day of admission. A registered dietician for their entire ICU stay assessed the nutritional status and nutritional requirement. Patients were divided into three groups based on initial TTR level and the outcome analysis was performed for APACHE II score, SOFA score, ICU length of stay, hospital length of stay, and mortality.

TTR showed excellent concordance with the univariate or multivariate classification of patients with PEM or at high malnutrition risk, and followed for seven days in the ICU, it is a measure of the metabolic burden.  TTR levels decline from day 1 to day 7 in spite of providing nutritional support. Twenty-five patients had an initial TTR serum concentration more than 17 mg/dL (group 1), forty-eight patients had mild malnutrition with a concentration between 10 and 17 mg/dL (group 2), Forty-five patients had severe malnutrition with a concentration less than 10 mg/dL (group 3).  Initial TTR level had inverse correlation with ICU length of stay, hospital length of stay, and APACHE II score, SOFA score; and predicted mortality, especially in group 3.

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A simplified nutrition screen for hospitalized patients using readily available laboratory and patient
information.
Linda Brugler, Ana K Stankovic, Madeleine Schlefer, Larry Bernstein
Nutrition 2005; 21(6):650-658
ICID: 825623
Article type: Review article
The role of visceral protein markers in protein calorie malnutrition.
Linda Brugler, Ana Stankovic, Larry Bernstein, Frederick Scott, Julie O’Sullivan-Maillet
Clin Chem Lab Med 2002; 40(12):1360-1369
ICID: 636207
Article type: Original article

The Automated Nutrition Score is a data-driven extension of continuous quality improvement.

Larry H Bernstein
Nutrition 2009; 25(3):316-317
ICID: 939934

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Transthyretin: its response to malnutrition and stress injury. clinical usefulness and economic implications.
LH Bernstein, Y Ingenbleek
Clin Chem Lab Med 2002; 40(12):1344-1348
ICID: 636205
Article type: Original article

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THE NUTRITIONALLY-DEPENDENT ADAPTIVE DICHOTOMY (NDAD) AND STRESS HYPERMETABOLISM
Yves Ingenbleek  MD  PhD  and  Larry Bernstein MD
J CLIN LIGAND ASSAY  (out of print)

The acute reaction to stress is characterized by major metabolic, endocrine and immune alterations. According to classical descriptions, these changes clinically present as a succession of 3 adaptive steps – ebb phase, catabolic flow phase, and anabolic flow phase. The ebb phase, shock and resuscitation, is immediate, lasts several hours, and is characterized by hypokinesis, hypothermia, hemodynamic instability and reduced basal metabolic rate. The catabolic flow phase, beginning within 24 hours and lasting several days, is characterized by catabolism with the flow of gluconeogenic substrates and ketone bodies in response to the acute injury. The magnitude of the response depends on the acuity and the severity of the stress. The last, a reparative anabolic flow phase, lasts weeks and is characterized by the accretion of amino acids (AAs) to rebuilding lean body mass.

The current opinion is that the body economy is reset during the course of stress at novel thresholds of metabolic priorities. This is exemplified mainly by proteolysis of muscle, by an effect on proliferating gut mucosa and lymphoid tissue as substrates are channeled to support wound healing, by altered syntheses of liver proteins with preferential production of acute phase proteins (APPs) and local repair in inflamed tissues (3). The first two stages demonstrate body protein breakdown exceeding the rate of protein synthesis, resulting in a negative nitrogen (N) balance, muscle wasting and weight loss. In contrast, the last stage displays reversed patterns, implying progressive recovery of endogenous N pools and body weight.

These adaptive alterations undergo continuing elucidation. The identification of cytokines, secreted by activated macrophages/monocytes or other reacting cells, has provided further insights into the molecular mechanisms controlling energy expenditure, redistribution of protein pools, reprioritization of syntheses and secretory processes.

The free fraction of hormones bound to specific binding-protein(s) [BP(s)] manifests biological activities, and any change in the BP blood level modifies the effect of the hormone on the end target organ.  The efficacy of these adaptive responses may be severely impaired in protein-energy malnourished (PEM) patients. This is especially critical with respect to changes of the circulating levels of transthyretin (TTR), retinol-binding protein (RBP) and corticosteroid-binding globulin (CBG) conveying thyroid hormones (TH), retinol and cortisol, respectively.  This reaction is characterized by cytokine mediated autocrine, paracrine and endocrine changes. Among the many inducing molecules identified, interleukins 1 and 6 (Il-1, Il-6) and tumor necrosis factor a (TNF) are associated with enhanced production of 3 counterregulatory hormonal families (cortisol, catecholamines and glucagon). Growth hormone (GH) and TH also have roles in these metabolic adjustments.

There is overproduction of cortisol mediated by several cytokines acting on both the adrenal cortex (10) and on the pituitary through hypothalamic CRH with loss of feedback regulation of ACTH production (11). Hypercortisolemia is a major finding observed after surgery (12), sepsis (13), and medical insults, usually correlated with severity of insult and of complications. Rising cortisol values parallel hyperglycemic trends, as an effect of both gluconeogenesis and insulin resistance. Working in concert with TNF, glucocorticoids govern the breakdown of muscle mass, which is regarded as the main factor responsible for the negative N balance.

Under normal conditions, GH exerts both lipolytic and anabolic influences in the whole body economy under the dual control of the hypothalamic hormones somatocrinin (GHRH) and somatostatin (SRIH). GH secretion is usually depressed by rising blood concentrations of glucose and free fatty acids (FFAs) but is paradoxicaly elevated despite hyperglycemia in stressed patients.

The oversecretion of counterregulatory hormones working in concert generates subtle equilibria between glycogenolytic/glycolytic/gluconeogenic adaptive processes. The net result is the neutralization of the main hypoglycemic and anabolic activities of insulin and the development of a persisting and controlled hyperglycemic tone in the stressed body. The molecular mechanisms whereby insulin resistance occurs in the course of stress refer to
cytokine-  and  hormone-induced  phosphorylation abnormalities affecting receptor signaling. The insulin-like anabolic processes of GH are mediated by IGF1 working as relay agent. The expected high IGF1 surge associated with GH oversecretion is not observed in severe stress as plasma values are usually found at the lower limit of normal or even in the subnormal range.  The end result of this dissociation between high GH and low IGF1 levels is to favor the proteolysis of muscle mass to release AAs for gluconeogenesis and the breakdown of adipose tissue to provide ketogenic substrates.

The acute stage of stress is associated with the onset of a low T3 syndrome typically delineated by the drop of both total (TT3) and free (FT3) triiodothyronine plasma levels in the subnormal range. In contrast, both total (TT4) and free (FT4) thyroxine values usually remain within normal ranges with declining trends observed for TT4 and rising tendencies for FT4 (44). This last free compound is regarded as the sensor reflecting the actual thyroid status and governing the release of TSH whereas FT3 works as the active hormonal mediator at nuclear receptor level. The maintenance of an euthyroid sick syndrome is compatible with the down-regulation of most metabolic and energetic processes in healthy tissues. These inhibitory effects , negatively affecting all functional steps of the hypothalamo-pituitary-thyroid axis concern TSH production, iodide uptake, transport and organification into iodotyrosyl residues, peroxidase coupling activity as well as thyroglobulin synthesis and TH leakage. Taken together, the above-mentioned data indicate that the development of hyperglycemia and of insulin-resistance in healthy tissues – mainly in the muscle mass – are hallmarks resulting from the coordinated activities of the counterregulatory hormones.

A growing body of recent data suggest that the stressed territory, whatever the causal agent – bacterial or viral sepsis, auto-immune disorder, traumatic or toxic shock, burns, cancer – manifest differentiated metabolic and immune reactions. The amplitude, duration and efficacy of these responses are reportedly impaired along several ways in PEM patients. These last detrimental effects are accompanied by a number of medical, social and economical consequences, such as extended length of hospital stay and increased complication / mortality rates. It is therefore mandatory to correctly identify and follow up the nutritional status of hospitalized patients. Such approaches are prerequisite to timely and scientifically grounded nutritional and pharmacological mediated interventions.

Contrary to the rest of the body, energy requirements of the inflamed territory are primarily fulfilled by anaerobic glycolysis, an effect triggered by the inhibition of key-enzymes of carbohydrate metabolism, notably pyruvate-dehydrogenase. This non-oxidative combustion of glucose reveals low conversion efficiency but offers the major advantage to maintain, in the context of hyperglycemia, fuel provision to poorly irrigated and/or edematous tissues. The depression of the 5’-monodeiodinating activity (5’-DA) plays a pivotal role in these adaptive changes, yielding inactive reverse T3 (rT3) as index of impaired T4 to T3 conversion rates, but at the same time there is an augmented supply of bioactive T3 molecules and local overstimulation of thyro-dependent processes characterized by thyroid down-regulation.  The same differentiated evolutionary pattern applies to IGF1. In spite of lowered plasma total concentrations, the proportion of IGF1 released in free form may be substantially increased owing to the proteolytic degradation of IGFBP-3 in the intravascular compartment. The digestion of  BP-3 results from the surge of several proteases occurring the course of stress, yielding biologically active IGF1 molecules available for the repair of damaged tissues. In contrast, healthy receptors oppose a strong resistance to IGF1 ligands freed in the general circulation, likely induced by an acquired phosphorylation defect very similar in nature to that for the insulin transduction pathway.

PEM is the generic denomination of a broad spectrum of nutritional disorders, commonly found in hospital settings, and whose extreme poles are identified as marasmus and kwashiorkor. The former condition is usually regarded as the result of long-lasting starvation leading to the loss of lean body mass and fat reserves but relatively well-preserved liver function and immune capacities. The latter condition is typically the consequence of (sub)acute deprivation predominantly affecting the protein content of staplefood, an imbalance causing hepatic steatosis, fall of visceral proteins, edema and increased vulnerability to most stressful factors. PEM may be hypometabolic or hypermetabolic, usually coexists with other diseased states and is frequently associated with complications. Identification of PEM calls upon a large set of clinical and analytical disciplines comprising anthropometry, immunology, hematology and biochemistry.

CBG, TTR and RBP share in common the transport of specific ligands exerting their metabolic effects at nuclear receptor level. Released from their specific BPs in free form, cortisol, FT4 and retinol immediately participe to the strenghtening of the positive and negative responses to stressful stimuli. CBG is a relatively weak responder to short-term nutritional influences (73)  although long-lasting PEM is reportedly capable of causing its significant diminution (74). The dramatic drop of CBG in the course of stress appears as the combined effect of Il-6-induced posttranscriptional blockade of its liver synthesis (75) and peripheral overconsumption by activated neutrophils (61). The divergent alterations outlined by CBG and total cortisolemia result in an increased disposal of free ligand reaching proportions considerably higher than the 4 % recorded under physiological conditions.

The appellation of negative APPs that was once given to the visceral group of carrier-proteins. The NDAD concept takes the opposite view, defending the opinion that their suppressed synthesis releases free ligands which positively contribute to strengthen all aspects of the stress reaction, justifying the ABR denomination. This implies that the role played by ABRs should no longer be interpreted in terms of concentrations but in terms of functionality.

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THE OXIDATIVE STRESS OF HYPERHOMOCYSTEINEMIA RESULTS FROM REDUCED BIOAVAILABILITY OF SULFUR-CONTAINING REDUCTANTS.
Yves Ingenbleek. The Open Clinical Chemistry Journal, 2011, 4, 34-44.

Vegetarian subjects consuming subnormal amounts of methionine (Met) are characterized by subclinical protein malnutrition causing reduction in size of their lean body mass (LBM) best identified by the serial measurement of plasma transthyretin (TTR). As a result, the transsulfuration pathway is depressed at cystathionine-β-synthase (CβS) level triggering the upstream sequestration of homocysteine (Hcy) in biological fluids and promoting its conversion to Met. Maintenance of beneficial Met homeostasis is counterpoised by the drop of cysteine (Cys) and glutathione (GSH) values downstream to CβS causing in turn declining generation of hydrogen sulfide (H2S) from enzymatic sources. The biogenesis of H2S via non-enzymatic reduction is further inhibited in areas where earth’s crust is depleted in elemental sulfur (S8) and sulfate oxyanions. Combination of subclinical malnutrition and S8-deficiency thus maximizes the defective production of Cys, GSH and H2S reductants, explaining persistence of unabated oxidative burden. The clinical entity increases the risk of developing cardiovascular diseases (CVD) and stroke in underprivileged plant-eating populations regardless of Framingham criteria and vitamin-B status. Although unrecognized up to now, the nutritional disorder is one of the commonest worldwide, reaching top prevalence in populated regions of Southeastern Asia. Increased risk of hyperhomocysteinemia and oxidative stress may also affect individuals suffering from intestinal malabsorption or westernized communities having adopted vegan dietary lifestyles.

Metabolic pathways: Met molecules supplied by dietary proteins are submitted to TM processes allowing to release Hcy which may in turn either undergo Hcy – Met RM pathways or be irreversibly committed into TS decay. Impairment of CbS activity, as described in protein malnutrition, entails supranormal accumulation of Hcy in body fluids, stimulation of activity and maintenance of Met homeostasis. This last beneficial effect is counteracted by decreased concentration of most components generated downstream to CbS, explaining the depressed CbS- and CbL-mediated enzymatic production of H2S along the TS cascade. The restricted dietary intake of elemental S further operates as a limiting factor for its non-enzymatic reduction to H2S which contributes to downsizing a common body pool. Combined protein- and S-deficiencies work in concert to deplete Cys, GSH and H2S from their body reserves, hence impeding these reducing molecules to properly face the oxidative stress imposed by hyperhomocysteinemia.

see also …

McCully, K.S. Vascular pathology of homocysteinemia: implications for the pathogenesis of arteriosclerosis. Am. J. Pathol., 1996, 56, 111-128.

Cheng, Z.; Yang, X.; Wang, H. Hyperhomocysteinemia and endothelial dysfunction. Curr. Hypertens. Rev., 2009, 5,158-165.

Loscalzo, J. The oxidant stress of hyperhomocyst(e)inemia. J. Clin.Invest., 1996, 98, 5-7.

Ingenbleek, Y.; Hardillier, E.; Jung, L. Subclinical protein malnutrition is a determinant of hyperhomocysteinemia. Nutrition, 2002, 18, 40-46.

Ingenbleek, Y.; Young, V.R. The essentiality of sulfur is closely related to nitrogen metabolism: a clue to hyperhomocysteinemia. Nutr. Res. Rev., 2004, 17, 135-153.

Hosoki, R.; Matsuki, N.; Kimura, H. The possible role of hydrogen sulfide as an endogenous smooth muscle relaxant in synergy with nitric oxide. Biochem. Biophys. Res. Commun., 1997, 237, 527-531.

Tang, B.; Mustafa, A.; Gupta, S.; Melnyk, S.; James S.J.; Kruger, W.D. Methionine-deficient diet induces post-transcriptional downregulation of cystathionine-􀀁-synthase. Nutrition, 2010, 26, 1170-1175.

Elshorbagy, A.K.; Valdivia-Garcia, M.; Refsum, H.; Smith, A.D.; Mattocks, D.A.; Perrone, C.E. Sulfur amino acids in methioninerestricted rats: Hyperhomocysteinemia. Nutrition, 2010, 26, 1201- 1204.

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Yves Ingenbleek. Plasma Transthyretin Reflects the Fluctuations of Lean Body Mass in Health and Disease. Chapter 20. In S.J. Richardson and V. Cody (eds.), Recent Advances in Transthyretin Evolution, Structure and Biological Functions, DOI: 10.1007/978‐3‐642‐00646‐3_20, # Springer‐Verlag Berlin Heidelberg 2009.

Transthyretin (TTR) is a 55-kDa protein secreted mainly by the choroid plexus and the liver. Whereas its intracerebral production appears as a stable secretory process allowing even distribution of intrathecal thyroid hormones, its hepatic synthesis is influenced by nutritional and inflammatory circumstances working concomitantly. Both morbid conditions are governed by distinct pathogenic mechanisms leading to the reduction in size of lean body mass (LBM). The liver production of TTR integrates the dietary and stressful components of any disease spectrum, explaining why it is the sole plasma protein whose evolutionary patterns closely follow the shape outlined by LBM fluctuations. Serial measurement of TTR therefore provides unequalled information on the alterations affecting overall protein nutritional status. Recent advances in TTR physiopathology emphasize the detecting power and preventive role played by the protein in hyperhomocysteinemic states, acquired metabolic disorders currently ascribed to dietary restriction in water-soluble vitamins. Sulfur (S)-deficiency is proposed as an additional causal factor in the sizeable proportion of hyperhomocysteinemic patients characterized by adequate vitamin intake but experiencing varying degrees of nitrogen (N)-depletion. Owing to the fact that N and S coexist in plant and animal tissues within tightly related concentrations, decreasing LBM as an effect of dietary shortage and/or excessive hypercatabolic losses induces proportionate S-losses. Regardless of water-soluble vitamin status, elevation of homocysteine plasma levels is negatively correlated with LBM reduction and declining TTR plasma levels. These findings occur as the result of impaired cystathionine-b-synthase activity, an enzyme initiating the transsulfuration pathway and whose suppression promotes the upstream accumulation and remethylation of homocysteine molecules. Under conditions of N- and S-deficiencies, the maintenance of methionine homeostasis indicates high metabolic priority.

Schematically, the human body may be divided into two major compartments, namely fat mass (FM) and FFM that is obtained by substracting
FM from body weight (BW). The fat cell mass sequesters about 80% of the total body lipids, is poorly hydrated and contains only small quantities of lean tissues and nonfat constituents. FFM comprises the sizeable part of lean tissues and minor mineral compounds among which are Ca, P, Na, and Cl pools totaling about 1.7 kg or 2.5% of BW in a healthy man weighing 70 kg. Subtraction of mineral mass from FFM provides LBM, a composite aggregation of organs and tissues with specific functional properties. LBM is thus nearly but not strictly equivalent to FFM. With extracellular mineral content subtracted, LBM accounts for most of total body proteins (TBP) and of TBN assuming a mean 6.25 ratio between protein and N content.

SM accounts for 45% of TBN whereas the remaining 55% is in nonmuscle lean tissues. The LBM of the reference man contains 98% of total
body potassium (TBK) and the bulk of total body sulfur (TBS). TBK and TBS reach equal intracellular amounts (140 g each) and share distribution patterns (half in SM and half in the rest of cell mass).  The body content of K and S largely exceeds that of magnesium (19 g), iron (4.2 g) and zinc (2.3 g). The average hydration level of LBM in healthy subjects of all age is 73% with the proportion of the intracellular/extracellular fluid spaces being 4:3. SM is of particular relevance in nutritional studies due to its capacity to serve as a major reservoir of amino acids (AAs) and as a dispenser of gluconeogenic substrates. An indirect estimate of SM size consists in the measurement of urinary creatinine, end-product of the nonenzymatic hydrolysis of phosphocreatine which is limited to muscle cells.

During ageing, all the protein components of the human body decrease regularly. This shrinking tendency is especially well documented for SM  whose absolute amount is preserved until the end of the fifth decade, consistent with studies showing unmodified muscle structure, intracellular K content and working capacit. TBN and TBK are highly correlated in healthy subjects and both parameters manifest an age-dependent curvilinear decline
with an accelerated decrease after 65 years.  The trend toward sarcopenia is more marked and rapid in elderly men than in elderly women decreasing strength and functional capacity. The downward SM slope may be somewhat prevented by physical training or accelerated by supranormal cytokine status as reported in apparently healthy aged persons suffering low-grade inflammation. 2002) or in critically ill patients whose muscle mass undergoes proteolysis and contractile dysfunction.

The serial measurement of plasma TTR in healthy children shows that BP values are low in the neonatal period and rise linearly with superimposable concentrations in both sexes during infant growth consistent with superimposable N accretion and protein synthesis rates. Starting from the sixties, TTR values progressively decline showing steeper slopes in elderly males. The lowering trend seems to be initiated by the attenuation of androgen influences and trophic stimuli with increasing age. The normal human TTR trajectory from birth to death has been well documented by scientists belonging to the Foundation for Blood Research. TTR is the first plasma protein to decline in response to marginal protein restricion, thus working as an early signal warning that adaptive mechanisms maintaining homeostasis are undergoing decompensation.

TTR was proposed as a marker of protein nutritional status following a clinical investigation undertaken in 1972 on protein-energy malnourished (PEM) Senegalese children (Ingenbleek et al. 1972). By comparison with ALB and transferrin (TF) plasma values, TTR revealed a much higher degree of sensitivity to changes in protein status that has been attributed to its shorter biological half-life (2 days) and to its unusual Trp richness (Ingenbleek et al. 1972, 1975a). Transcription of the TTR gene in the liver is directed by CCAAT/enhancer binding protein (C/EBP) bound to hepatocyte nuclear factor 1 (HNF1) under the control of several other HNFs. The mechanism responsible for the suppressed TTR synthesis in PEM-states is a restricted AA and energy supply working as limiting factors (Ingenbleek and Young 2002). The rapidly turning over TTR protein is highly responsive to any change in protein flux and energy supply, being clearly situated on the cutting edge of the equipoise.

LBM shrinking may be the consequence of either dietary restriction reducing protein syntheses to levels compatible with survival or that of cytokine-induced tissue proteolysis exceeding protein synthesis and resulting in a net body negative N balance. The size of LBM in turn determines plasma TTR concentrations whose liver production similarly depends on both dietary provision and inflammatory conditions. In animal cancer models, reduced TBN pools were correlated with decreasing plasma TTR values and provided the same predictive ability. In kidney patients, LBM is proposed as an excellent predictor of outcome working in the same direction as TTR plasma levels.  High N intake, supposed to preserve LBM reserves, reduces significantly the mortality rate of kidney patients and is positively correlated with the alterations of TTR plasma concentrations appearing as the sole predictor of final outcome. It is noteworthy that most SELDI or MALDI workers interested in defining protein nutritional status have chosen TTR as a biomarker, showing that there exists a large consensus considering the BP as the most reliable indicator of protein depletion in most morbid circumstances.

Total homocysteine (tHcy) is a S-containing AA not found in customary diets but endogenously produced in the body of mammals by the enzymatic transmethylation of methionine (Met), one of the eight IAAs supplied by staplefoods. tHcy may either serve as precursor substrate for the synthesis of new Met molecules along the remethylation (RM) pathway or undergo irreversible kidney leakage through a cascade of derivatives defining the transsulfuration (TS) pathway. Hcy is thus situated at the crossroad of RM and TS pathways that are regulated by three water-soluble vitamins (pyridoxine, B6; folates, B9; cobalamins, B12).

Significant positive correlations are found between tHcy and plasma urea and plasma creatinine, indicating that both visceral and muscular tissues undergo proteolytic degradation throughout the course of rampant inflammatory burden. In healthy individuals, tHcy plasma concentrations maintain positive correlations with LBM and TTR from birth until the end of adulthood. Starting from the onset of normal old age, tHcy values become disconnected from LBM control and reveal diverging trends with TTR values. Of utmost importance is the finding that, contrary to all protein
components which are downregulated in protein-depleted states, tHcy values are upregulated.  Hyperhomocysteinemia is an acquired clinical entity characterized by mild or moderate elevation in tHcy blood values found in apparently healthy individuals (McCully 1969). This distinct morbid condition appears as a public health problem of increasing importance in the general population, being regarded as an independent and graded risk factor for vascular pathogenesis unrelated to hypercholesterolemia, arterial hypertension, diabetes and smoking.

Studies grounded on stepwise multiple regression analysis have concluded that the two main watersoluble vitamins account for only 28% of tHcy variance whereas vitamins B6, B9, and B12, taken together, did not account for more than 30–40% of variance. Moreover, a number of hyperhomocysteinemic conditions are not responsive to folate and pyridoxine supplementation. This situation prompted us to search for other causal factors which might fill the gap between the public health data and the vitamin triad deficiencies currently incriminated. We suggest that S – the forgotten element – plays central roles in nutritional epidemiology (Ingenbleek and Young 2004).

Aminoacidemia studies performed in PEM children, adult patients and elderly subjects have reported that the concentrations of plasma IAAs invariably display lowering trends as the morbid condition worsens. The depressed tendency is especially pronounced in the case of tryptophan and for the so-called branched-chain AAs (BCAAs, isoleucine, leucine, valine) the decreases in which are regarded as a salient PEM feature following the direction outlined by TTR (Ingenbleek et al. 1986). Met constitutes a notable exception to the above described evolutionary profiles, showing unusual stability in chronically protein depleted states.

Maintenance of normal methioninemia is associated with supranormal tHcy blood values in PEMadults (Ingenbleek et al. 1986) and increased tHcy leakage in the urinary output of PEM children. In contrast, most plasma and urinary S-containing compounds produced along the TS pathway downstream to CbSconverting step (Fig. 20.1) display significantly diminished values. This is notably the case for cystathionine (Ingenbleek et al. 1986), glutathione, taurine, and sulfaturia. Such distorted patterns are reminiscent of abnormalities defining homocystinuria, an inborn disease of Met metabolism characterized by CbS refractoriness to pyridoxine stimuli, thereby promoting the upstream retention of tHcy in biological fluids. It
was hypothesized more than 20 years ago (Ingenbleek et al. 1986) that PEM is apparently able to similarly depress CbS activity, suggesting that the enzyme is a N-status sensitive step working as a bidirectional lockgate, overstimulated by high Met intake (Finkelstein and Martin 1986) and downregulated under N-deprivation conditions (Ingenbleek et al. 2002). Confirmation that N dietary deprivation may inhibit CbS activity has recently provided. The tHcy precursor pool is enlarged in biological fluids, boosting Met remethylation processes along the RM pathway, consistent with studies showing overstimulation of Met-synthase activity in conditions of protein restriction. In other words, high tHcy plasma concentrations observed in PEM states are the dark side of adaptive mechanisms for maintaining Met homeostasis. This is consistent with the unique role played by Met in the preservation of N body stores.

The classical interpretation that strict vegans, who consume plenty of folates in their diet and manifest nevertheless higher tHcy plasma concentrations than omnivorous counterparts, needs to be revisited. On the basis of hematological and biochemical criteria, cobalamin deficiency is one of the most prevalent vitamin-deficiencies wordwide, being often incriminated as deficient in vegan subjects. It seems, however, likely that its true causal impact on rising tHcy values is substantially overestimated in most studies owing to the modest contribution played by cobalamins on tHcy
variance analyses. In contrast, there exists a growing body of converging data indicating that the role played by the protein component is largely underscored in vegan studies. It is worth recalling that S is the main intracellular anion coexisting with N within a constant mean S:N ratio (1:14.5) in animal tissues and dietary products of animal origin (Ingenbleek 2006). The mean S:N ratio found in plant items ranges from 1:20 to 1:35, a proportion that does not optimally meet human tissue requirements (Ingenbleek 2006), paving the way for borderline S and N deficiencies.

A recent Taiwanese investigation on hyperhomocysteinemic nuns consuming traditional vegetarian regimens consisting of mainly rice, soy products,
vegetables and fruits with few or no dairy items illustrates such clinical misinterpretation (Hung et al. 2002). The authors reported that folates and cobalamins, taken together, accounted for only 28.6% of tHcy variance in the vegetarian cohort whereas pyridoxine was inoperative (Hung et al. 2002). The daily vegetable N and Met intakes were situated highly significantly (p < 0.001) below the recommended allowances for humans (FAO/WHO/United Nations University 1985), causing a stage of unrecognized PEM documented by significantly depressed BCAA plasma
concentrations. Met levels escaped the overall decline in IAAs levels, emphasizing that efficient homeostatic mechanisms operate at the expense of an acquired hyperhomocysteinemic state. The diagnosis of subclinical PEM was missed because the authors ignored the exquisitely sensitive TTR detecting power. A proper PEM identification would have allowed the authors to confirm the previously described TTR–tHcy relationship that was established in Western Africa from comparable field studies involving country dwellers living on plant products.

The concept that acute or chronic stressful conditions may exert similar inhibitory effects on CbS activity and thereby promote hyperhomocysteinemic states is founded on previous studies showing that hypercatabolic states are characterized by increased urinary N and S losses maintaining tightly correlated depletion rates (Cuthbertson 1931; Ingenbleek and Young 2004; Sherman and Hawk 1900) which reflect the S:N ratio found in tissues undergoing cytokine induced proteolysis. This has been documented in coronary infarction and in acute pancreatitis where tHcy elevation evolves too rapidly to allow for a nutritional vitamin B-deficit explanation.  tHcy is considered stable in plasma and the two investigations report unaltered folate and cobalamin plasma concentrations.

The clinical usefulness of TTR as a nutritional biomarker, described in the early seventies (Ingenbleek et al. 1972) has been substantially disregarded by the scientific community for nearly four decades. This long-lasting reluctance expressed by many investigators is largely due to the fact that protein malnutrition and stressful disorders of various causes have combined inhibitory effects on hepatic TTR synthesis. Declining TTR plasma concentrations may result from either dietary protein and energy restrictions or from cytokine-induced transcriptional blockade (Murakami et al. 1988) of its hepatic synthesis. The proposed marker was therefore seen as having high sensitivity but poor specificity. Recent advances in protein metabolism settle the controversy by throwing further light on the relationships between TTR and the N-components of body composition.

The developmental patterns of LBM and TTR exhibit striking similarities. Both parameters rise from birth to puberty, manifest gender dimorphism during full sexual maturity then decrease during ageing. Uncomplicated PEM primarily affects both visceral and structural pools of LBM with distinct kinetics, reducing protein synthesis to levels compatible with prolonged survival. In acute or chronic stressful disorders, LBM undergoes muscle proteolysis exceeding the upregulation of protein syntheses in liver and injured areas, yielding a net body negative N balance. These adaptive responses are well identified by the measurement of TTR plasma concentrations which therefore appear as a plasma marker for LBM fluctuations.
Attenuation of stress and/or introduction of nutritional rehabilitation restores both LBM and TTR to normal values following parallel slopes. TTR fulfills, therefore, a unique position in assessing actual protein nutritional status, monitoring the efficacy of dietetic support and predicting the patient’s outcome (Bernstein and Pleban 1996).

see also…

Acosta PB, Yannicelli S, Ryan AS, Arnold G, Marriage BJ, Plewinska M, Bernstein L, Fox J, Lewis V, Miller M, Velazquez A (2005) Nutritional therapy improves growth and protein status of children with a urea cycle enzyme defect. Mol Genet Metab 86:448–455.

Arroyave G, Wilson D, Be´har M, Scrimshaw NS (1961) Serum and urinary creatinine in children with severe protein malnutrition. Am J Clin Nutr 9:176–179.

Bates CJ, Mansoor MA, van der Pols J, Prentice A, Cole TJ, Finch S (1997) Plasma total homocysteine in a representative sample of 972 British men and women aged 65 and over. Eur J Clin Nutr 51:691–697.

Battezzatti A, Bertoli S, San Romerio A, Testolin G (2007) Body composition: An important determinant of homocysteine and methionine concentrations in healthy individuals. Nutr Metab Cardiovasc Dis 17:525–534.

Bernstein LH, Bachman TE, Meguid M, Ament M, Baumgartner T, Kinosian B, Martindale R, Spiekerman M (1995) Prealbumin in nutritional care Consensus Group. Measurement of visceral protein status in assessing protein and energy malnutrition: Standard of care. Nutrition 11:169–171

Bernstein LH, Ingenbleek Y (2002) Transthyretin: Its response to malnutrition and stress injury. Clinical usefulness and economical implications. Clin Chem Lab Med 40:1344–1348.

Boorsook H, Dubnoff JW (1947) The hydrolysis of phosphocreatine and the origin of creatinine. J Biol Chem 168:493–510.

Briend A, Garenne M, Maire B, Fontaine O, Dieng F (1989) Nutritional status, age and survival: The muscle mass hypothesis. Eur J Clin Nutr 43:715–726

Brouillette J, Quirion R (2007) Transthyretin: A key gene involved in the maintenance of memory capacities during aging. Neurobiol Aging 29:1721–1732

Chertow GM, Goldstein-Fuchs DJ, Lazarus JM, Kaysen GA (2005) Prealbumin, mortality, and cause-specific hospitalization in hemodialysis patients. Kidney Int 68:2794–2800

Cohn SH, Gartenhaus W, Sawitsky A, Rai K, Zanzi I, Vaswani A, Ellis KJ, Yasumura S, Cortes E, Vartsky D (1981) Compartmental body composition of cancer patients by measurement of total body nitrogen, potassium and water. Metabolism 30:222–229

Cuthbertson DP (1931) The distribution of nitrogen and sulphur in the urine during conditions of increased catabolism. Biochem J 25:236–244

Devakonda A, George L, Raoof S, Esan A, Saleh A, Bernstein LH (2008) Transthyretin as a marker to predict outcome in critically ill patients. Clin Biochem 41:1126–1130

Ellis KJ, Yasumura S, Vartsky D, Vaswani AN, Cohn SH (1982) Total body nitrogen in health and disease: Effects of age, weight, height, and sex. J Lab Clin Med 99:917–926

Etchamendy N, Enderlin V, Marighetto A, Vouimba RM, Pallet V, Jaffard R, Higueret P (2001) Alleviation of a selective age-related relational memory deficit in mice by pharmacologically induced normalization of brain retinoid signaling. J Neurosci 21:6423–6429

Evans WJ (1991) Reversing sarcopenia: How weight training can build strength and vitality. Geriatrics 51:46–53

Evans WJ, Campbell WW (1993) Sarcopenia and age-related changes in body composition and functional capacity. J Nutr 123:465–468

Finkelstein JD, Martin JJ (1984) Methionine metabolism in mammals. Distribution of methionine between competing pathways. J Biol Chem 259:9508–9513

Garg UC, Zheng ZJ, Folsom AR, Moyer YS, Tsai MY, McGovern P, Eckfeldt JH (1997) Short-term and long-term variability of plasma homocysteine measurement. Clin Chem 43:141–145

Goodman AB, Pardee AB (2003) Evidence for defective retinoid transport and function in late onset Alzheimer’s disease. Proc Natl Acad Sci USA 100:2901–2905

Gray GE, Landel AM, Meguid MM (1994) Taurine-supplemented total parenteral nutrition and taurine status of malnourished cancer patients. Nutrition 10:11–15

Heymsfield SB, McManus C, Stevens V, Smith J (1982) Muscle mass: Reliable indicator of protein-energy malnutrition and outcome. Am J Clin Nutr 35:1192–1199

Ingenbleek Y (2006) The nutritional relationship linking sulfur to nitrogen in living organisms. J Nutr 136:S1641–S1651
Ingenbleek Y (2008) Plasma transthyretin indicates the direction of both nitrogen balance and retinoid status in health and disease. Open Clin Chem J 1:1–12
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The role of biomarkers in the diagnosis of sepsis and patient management

Author: L. H. Bernstein, MD, FCAP

Key words: Systemic Inflammatory Response Syndrome (SIRS), sepsis, septic shock, mean arterial blood pressure (MAP), procalcitonin, combinatorial analysis, effect size

Highlights:
1.   The systemic inflammatory response syndrome (SIRS) is an acute response to trauma, burn, or infectious injury characterized by fever, hemodynamic and respiratory changes, and metabolic changes, not all of which are consistently present.

2.   The SIRS reaction involves hormonally driven changes in liver glycogen reserves, triggering of  lipolysis, lean body proteolysis, and reprioritization of hepatic protein synthesis with up-regulation of synthesis of acute phase proteins and down-regulation of albumin and important circulating transport proteins.

3.   Understanding of the processes leads to the identification of biomarkers for identification of sepsis and severe, moderate or early SIRS, which also can hasten treatment and recovery.

4.   The SIRS reaction unabated leads to a recurring cycle with hemodynamic collapse from septic shock, indistinguishable from cardiogenic shock, and death.

Abbreviations: Systemic Inflammatory Response Syndrome (SIRS), procalcitonin (PCT), C-reactive protein (CRP), mean arterial blood pressure (MAP), Intensive care unit (ICU), total white blood cell count (WBC), transthyretin(TTR)

Summary
By focusing on early and accurate diagnosis of infection in patients suspected of SIRS antibiotic overuse and its associated morbidity and mortality may be avoided, and therapeutic targets may be identified. This discussion investigates the performance of diagnostic algorithms and biomarkers for sepsis in patients presenting with leukocytosis and other findings. Suspected patients are usually identified by WBC above 12,000/mL  PCT level , SIRS and other criteria, such as serum biomarkers of sepsis. In this writer’s study of 435 patients, procalcitonin alone was a superior marker for sepsis. In patients with sepsis there was a marked increase in PCT (p = 0.0001). PCT was increased in patients requiring ICU admission, heart rate and blood pressure monitoring, and assisted ventilation.(p = 0.0001). Means for SIRS/non-SIRS were: CRP 802/404 mg/L; PCT 20.6/7.5 ng/mL; TTR 87.8/125 mg/L. A comprehensive overview of at least a decade of work is provided.

Introduction

Sepsis is a costly diagnosis in hospitalized patients and carries a high financial risk as a comorbidity and a payment penalty for failure to diagnose in a timely manner (1-4) under the severity of illness CMS reimbursement guidelines as a patient safety hazard, with pneumonia and sepsis among the ten most costly among hospital admissions. A polypeptide identical to a prohormone of calcitonin, procalcitonin, was initially described as a potential marker of bacterial disease by Assicot et al.(5). Procalcitonin is almost undetectable under physiological conditions (pg/ml range), but rises to very high values in response to bacteraemia or fungaemia, and appears to be related to the severity of infection.(6)  Sequential measurements in patients with bacteraemia have shown a rapid fall within 48 hours of antibiotic administration.

Is it an unlikely candidate sepsis biomarker? It is a precursor of calcitonin, and under ordinary circumstances can be accounted for by its production in the thyroid. It is widely produced extrathyroidally with sepsis. The main reason for such interest is the response seems to be uncoupled to the systemic inflammatory response, as CRP is.  What is it a response to? What is the role it has in primary cellular immune response? There is no question that it is found in very low level without serious infection, so that a low level would remove the necessity for a blood culture. In other words it predicts absence of sepsis. Is it fortuitous or serendipity?

On the other hand, we now refer to bacterial and abacterial sepsis. So there are a significant proportion of sepsis diagnoses for which cultures are negative. You might decide that the method of taking cultures x3 at different times and from different sites (not universally practiced) might account for the negative cultures. It was reported in the New York Times a week ago that a child came to the emergency room in a NY hospital with a simple sports injury abrasing the skin surface, was sent home, returned, and died in 24 hours. It’s not such an easy call, despite the result.

There have been numerous studies of the early recognition of sepsis and related diseases in patients related to admission and intensive care. The consensus  guideline has used a SIRS criteria (7, 8).  The SIRS criteria (7,8)  include temperature o C. >= 38o C., heart rate > 90 beats per minute, respiratory rate >20 breaths per minute or PaCO  < 32 mm of Hg, WBC > 12,000/mL or < 4,000/mL, or > 10% band forms. For the diagnosis of sepsis (2 or more SIRS criteria and confirmed or suspected infection) the SIRS criteria are insufficient with a very high false positive rate, so that there are medical institutions that require three.  The observation of fever, tachypnea, and tachycardia may well not be present early, and the observation of leukocytosis with or without band neutrophilia are unreliable.  The use of a plasma lactic acid measurement has been added, but it is basically a reflection of decreased splanchnic circulation to the superior mesenteric artery and liver bed.  A better case has been made for absolute neutophilia (9), with an adjustment for high lymphocyte counts in children in the first six months, and for the identification of increased immature myeloid precursors (myelocytes and metamyelocytes). The C-reactive protein, a long established acute phase protein, is not predictive at levels under 520 mg/L because it is elevated in a variety of chronic inflammatory conditions.  Moreover, it is infrequently used in adult medical practice for that reason, except for the high sensitivity CRP, which has been shown to be relevant to treatment of coronary heart disease by the Jupiter study (10), but also has raised the question of overuse of the statins with the undesirable side effect of skeletal muscle loss.  We can explore the validity of over ten years of studies in Europe and US, showing a debated benefit from using the procalcitonin biomarker (PCT, Brahms)(11-28).

The question arises whether there is a difference in PCT response between Gm- and Gm+, and there is, but it doesn’t matter. We can’t be certain that this reaction is  produced by vascular endothelium. I could identify at least one case where I knew the patient had no culture taken and died in cardiovascular shock. At that stage of decompensation what would make one think that it was other than pump failure? But in the evolution of cardiogenic shock, the perfusion of the superior mesentery artery could well be decompensated with the release of bacteria of intestinal organs. Quite a bit of work has been done in surgical research that indicates that there is bacterial migration to regional nodes, but it isn’t problematic unless there is a systemic insult.

Then there needs to be an explanation of events related to gene regulation and cell signaling, that is a blank screen. The cost of the test has been a factor limiting the use, which I think is not the key issue.

Results

A multivariable study with 435 patients to determine whether procalcitonin alone is a superior marker for sepsis established a difference between patients with and without sepsis , as the increase in PCT with sepsis was significant at p = 0.0001.  The PCT was also increased in patients who were admitted to the ICU, requiring assisted ventilation and monitoring of heart rate and blood pressure, significant at p = 0.0001.  The highest values occur in septic shock, even though mild elevations are seen with localized infection.  A PCT level distinguishes between four subgroups of the population: no infection, local infection, sepsis, and severe sepsis and septic shock. The PCT is very low with no infection and rises to levels above 5 with moderate to severe sepsis.  Table 1 compares the selected biomarker results for patients in ICU and not in ICU by the t test with adjustment for unequal variances.  The salient points are noted. PCT, not CRP, is significant for a difference between SIRS positive and SIRS negative patients in ICU (p=0.0001 vs 0.166), with a mean CRP of 495 mg/L in non ICU patients.  The result is expected because the CRP is elevated in other conditions without sepsis, and the patients in the ICU and outside the ICU may have a variety of inflammatory conditions.  There is a difference in PCT between ICU and non-ICU patients without SIRS (p = 0.0001), indicating that PCT is identifying infection, if not sepsis, in this cohort of patients.  Patients in the ICU with SIRS (vs without) have a mean PCT of 35.2 vs 3.7 ng/ml, a clinically as well as statistically significant increase in PCT (Mann-Whitney, p = 0.0001). On the other hand, patients without SIRS in the ICU also have higher CRP [1] and PCT [2] than those not in ICU (1, p = 0.032; 2, p = 0.004), but the CRP difference just reaches statistical significance while the unexpected PCT increase is a big effect.  The means obtained for SIRS/non-SIRS are: CRP [1] 802/404 mg/L; PCT [2] 20.6/7.5 ng/ml; TTR [3] 87.8/125 mg/L. So we see an increase of CRP and PCT with SIRS, as expected, and a decrease in TTR to below 100 mg/L as an obligatory response in relationship to the severity of the inflammatory state. The patients with SIRS and those with sepsis, respectively, had significant elevations of CRP [1] and PCT[2], and decrease of TTR[3] by Mann-Whitney test      (SIRS, p = 0.006, CRP [1]; 0.0001, PCT [2]; 0.0001 TTR[3]; sepsis, p = 0.010, CRP [1]; 0.014, PCT [2]; 0.004, TTR [3]).

Finally, we are particularly interested in combinations of variables for predicting infection and the stage of infection using PCT, MAP (mean arterial blood pressure), WBC.  The model fit looks good based on the chi-squared statistics.   The relationship between the predictor variables and SIRS or ICU is consistent with the large increases of PCT described.  In exploring this strong association between the chosen predictors for SIRS and ICU – PCT, WBC, MAP and TTR (CRP not used) demonstrated that each can be used in a classification matrix. (Table 2)   One might create a 4-letter code using M (MAP)_T (TTR)_W (WBC)_S (SIRS) to test for PCT effectiveness in the same way that one would test PCT against the clinical diagnosis of sepsis, but excluding the variable that we are interested in proving.  PCT can then be added as the fifth variable. The data was classified according to mean arterial blood pressure (MAP), TTR, white cell count (WBC), and SIRS as described and the PCT was kept out of the classification.  The PCT, MAP and SIRS differences were all significant at 0.0001, and the TTR had a p = 0.021 in the Kruskall Wallis analysis by ranks. A similar, but simpler classification did not include either PCT or MAP, resulting in three classes. The PCT increased within the subgroups of WTSIRS (2.5, 25, 50, 75 and 97.5 percentiles. Further, the subgroup of patients classified by MAP, TTR, WBC and SIRS, had a dramatic decline in the MAP by subclass, the last of which is comparable to septic shock.   We constructed a latent class model using the ordinals of PCT, MAP and WBC scaled to intervals. The combinatorial classes formed by the predictors have a defined contribution (percent) of each predictor.  The R2, L2 and C2 are shown.

Degrees of freedom (df)            282                  p-value

L-squared (L²)                         217.6904         1.00

X-squared                                235.4391         0.98

Cressie-Read                           209.1484         1.00

aBIC (based on LL)                  634.1041

bAIC (based on LL)                 494.7921

aBayes Information Criterion, bAkaike’s Information Criterion

Model for Dependent

Class1             0.7961

Class2             0.9136

Class3             0.9782

Class4             0.6410

Overall            0.9319

The chi-squared with a p-value close to 1 indicates that the partitioning of the combinatorial groups is excellent, and the model is not underfit or overfit.   A second cluster LCA model using SIRS as covariate also gives a good fit. The p-values are acceptable.

Chi-squared Statistics

Degrees of freedom (df)                        258                  p-value

L-squared (L²)                                     248.9633         0.65

X-squared                                            230.6279         0.89

Cressie-Read                                       222.0675         0.95

BIC (based on L²)                                -1238.4560

AIC (based on L²)                                -267.0367

Even though CRP has validity for identifying SIRS in our exploratory study, the specificity and its usefulness at a cutoff at 52 mg/dL raised significant concerns with respect to with respect to distinguishing SIRS with and without infection.  Keep in mind that large variances in CRP exist between the subgroups, which is problematic because of the CRP elevation in patients with metabolic syndrome and with chronic inflammatory diseases, but not necessarily sepsis. TTR is also decreased, as CRP is elevated, in patients with inflammatory conditions without sepsis.

The data demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. We also showed the elevation of PCT in concert with severity of infection, as determined by medical record review.  Patients with sepsis are transferred to the ICU for management. These patients are on antibiotics and they are monitored for drop in mean arterial blood pressure over the first 72 hours, as a drop in MAP below 72 indicates septic shock. The progression from SIRS to septic shock goes from single organ (lung, kidney) to double organ, to multiple organ dysfunction syndrome is accompanied by increased lactic acid, tachycardia, decreased MAP, and finally, increase in serum bilirubin.  We would expect and find elevations of PCT with pneumonia, deep wounds, and pyelonephritis as well as sepsis, but these patients would be expected to meet the SIRS criteria.  Our study was not designed to demonstrate how PCT might detect sepsis in older patients with negative SIRS criteria in the ICU who are on ventilator assistance and who may not develop a febrile response. One has to consider that this is related to PCT elevation being partly independent of the SIRS response.

We then showed the same relationship to biomarker combinations that classify the data in accordance with the severity of infection. The WBC count is the weakest classification variable, but it is in the SIRS criteria and it is of greatest value with a finding of immature neutrophils. However, the band count is now considered part of the mature neutrophil count so that the absolute neutrophil count and the immature granulocytes measured by flow cytometry (myelocytes and metamyelocytes) are superior to the tWBC and bands (  ).  The MAP is valuable for identifying the patients at highest risk of circulatory collapse with a drop in the MAP and transfer to ICU (on pressors). The drop in MAP within 72 hours is important for making decisions about Activated protein C (Xygris), which is a critical decision.  APC has been removed from the market.  We included the TTR, which decreases in patients with SIRS in proportion to the severity of illness.  If we compare these predictors in patients with a diagnosis of sepsis, CRP, PCT (and TTR) all have significant differences between ICU and not ICU admission at p < 0.05. The elevation of white cell count and percent neutrophils, unexpectedly has no separatory power. This would not be the case for a postoperative patient who had an increase in WBC that was previously not elevated, or a failure to drop the WBC given antibiotics. On the other hand, for the combination of SIRS and elevated white cell count, the CRP, PCT and TTR all give good separation between ICU and non-ICU patients, an improvement over SIRS positive status alone. This reflects the non specificity with a high false positive rate of the SIRS criteria when neither of the two predictors is granulocytosis.  We asked whether we can combine the key predictor variable into combinatorial classes that would improve the accuracy of identification. CRP was not of interest with respect to this analysis as the poor specificity could only confound matters, and the test offers no additional information than PCT provides.   A more formal classification can then be designed using existing multivariate protocols, but keeping in mind that a mixed model or one using a log-linear model is preferred.

Our study is unique in at least two respects: It is the first to clearly demonstrate a graded response of PCT to severity of infectious challenge.  It is also a rare study to use a classification method to study the effect of combinations of variables associated with SIRS and infection on PCT elevation (11-13). We have created a graded classification by using feature extraction and forming an N-length class based on established information principles (Kullback entropy and Akaike Information Criteria).  The features used to classify the data were PCT, MAP, TTR, WBC and a SIRS score of at least two. The data was also classified without using PCT in order to establish validity for PCT independently of a classification using the feature being evaluated.The classifications have been extensively examined using one-way ANOVA, Kruskal Wallis analysis by ranks,  and latent class analyses. The Kruskal-Wallis analysis by ranks is a powerful tool for comparing the PCT levels within and across feature classes when the variance of PCT values across groups does not have the same distribution and the assumption of normal distribution doesn’t hold. Latent class analysis is a group of methods that can be used to classify data when the data is converted to ordinal classes under the assumption that there is a hidden or “latent” underlying classification. In defining latent classes we assume the criterion of “conditional independence,” so that, each variable is statistically independent of every other variable within each latent class, In our case, latent classes correspond to probabilities for and against the presence of a distinct medical syndrome. In this case we call attention to the classes representing no infection, soft tissue infection, sepsis, and severe sepsis or septic shock.  In reality, the variables used to form the classes are not independent, but they are used as ordinal variables and can be ranked in order of importance in forming a classification. There is a paper of some interest with regard to classification and prediction of severe sepsis that finds PCT, lactic acid and aminoterminal pro B-type natriuretic peptide correlating with sepsis severity scores (12) and another using PCT in combination with waveform analysis (13).  Classification and prediction has been of particular interest to the corresponding investigator for laboratory procedure validation for more than 10 years (20-22).  We provide valuable references to this approach (23-27).

In all respects, we find agreement with a large number of studies, including those recently cited (5-19). PCT has been shown to be useful for discriminating systemic inflammatory response, infection and sepsis (5,6) and identifying a high mortality subgroup with sepsis (15), for identifying sepsis at the onset with either gram negative or gram positive bacteremia (10), for evaluating time to treatment effectiveness (16), and for identifying sepsis in the febrile neutropenic patient (18).

What is it in our findings that makes the results compelling?  CRP has been used for many years, although more widely in European countries than in US until the high sensitivity assay association with risk of coronary artery disease generated a new interest in this test.  CRP increase is associated with SIRS and its production is driven by the cytokines TNFa and Il6.  The liver reprioritises the production of acute phase reactants (CRP, a1 acid glycoprotein [orosomucoid], a1 antitrypsin and transferrin with down-regulation of production of albumin, TTR, transcortin, and other serum transport proteins. However, if this happens in the extreme condition, it also is the case in the more chronic conditions, such as, rheumatoid arthritis and autoimmune diseases, and is a feature of the metabolic syndrome, characterized by type 2 diabetes, obesity, and insulin resistance with or without dyslipidemia. Consequently, CRP is quite high associated with a variety of non-septic conditions.  The emergence of PCT as a sepsis biomarker is somewhat serendipidous.  The protein is the precursor of the peptide calcitonin, produced in the thyroid.  Sepsis appears to upregulate the extrathyroidal production of procalcitonin by vascular endothelium by a mechanism not understood.  PCT can be elevated with non-septic shock, such a cardiogenic shock, but it is easy to comprehend that secondary sepsis could occur by loss of gut integrity and bacterial translocation in such a state.

The importance of pneumonia and pyelonephritis as a precursor of sepsis, and the rapid progression of sepsis in the hospitalised ICU patient can’t be taken lightly.  The identification of sepsis in the emergency room is problematic because the clinical presentation is variable and not so specific.  The SIRS criteria – tachycardia, tachypnea, fever, and leukocytosis – are all common presentations in patients without sepsis.   On the one hand, more accurate identification of the patients with sepsis should eliminate many patients who are screened for sepsis and subsequently have negative culture, and should identify patients who require prompt antimicrobial treatment at an early stage.

The progression from SIRS to sepsis to organ failure and septic shock should also be monitored effectively, which depends on the level of PCT reflecting the level of systemic disorder.  This would permit the best identification of patients who are improving and those who might require activated protein C intervention.  The progression from SIRS to sepsis and beyond is a complex process involving repeated events in the course of the acute illness.  This gives even more justification for combining PCT with other measures to manage the septic state.

Conclusion

We have demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient.  In addition, we have shown the strength of classifying these patients using PCT in combination with MAP, TTR, WBC and SIRS.

References

1. Martin MS, Mannino DM, et al. The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med. 2003; 348:1546-1554.

2. NationalCenter for Health Statistics. National vital statistics reports. 2004; 53:9.

3. Angus DC, Linde-Zwirble WT, et al. Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med. 2001; 29:1303-1310.

4.  Smith BS, Schroeder WS; Tataronis GR.Hospital reimbursement for adult Patients with severe sepsis treated with drotrecogin alfa (activated). Hospital pharmacy 2005; 40:146-153.

5.  Assicot M, Gendrel D, Cersin H, Raymond J, et al. High serum procalcitonin concentrations in patients withsepsis and infection.  Lancet 1993: 341: 515-18.

6.  Delveraux I, Andre M, Columbier M, Albuisson E, et al. Can procalcitonin measurement help in differentiating between bacterial and other kinds of inflammatory processes?  Ann Rheum Dis 2003; 62: 337-40.

7. Bone R, Balk R, Cerra F, Dellinger R, Fein W, et. Definitions of sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. Amer Coll of Chest Physicians/Soc of Critical Care Med. Chest 1992; 101(6): 1644-655.

8.Dellinger R, Phillip R, Levy MM, Carlet JM, et al. Surviving Sepsis Campaign: Internatl Guidelines for Management of Severe Sepsis and Septic Shock:2008. Crit Care Med 2008; 36(1): 296-377.

9. Bernstein LH and Rucinski R. The relationship between granulocyte maturation and the septic state measurement of granulocyte maturation may improve the early diagnosis of the septic state.  Clin Chem Lab Med 2011;         DOI 10.1515/CCLM.2011.xxx

10. Ridker PM, Danielson E, Fonseca FAH, Genest J, Gotto AM, et al.  Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein.  NEJM 2008; 359: 2195-2207.

11. Jensen JU, Heslet L,; Jensen TH, Espersen K, et al. Procalcitonin increase in early identification of critically ill patients at high risk of mortality. Crit Care Med 2006; 34(10):1-7.

12.  Luzzani A, Polati E, Dorizzi R, Rungatscher A, et al.  Comparison of procalcitonin and C-reactive protein as markers of sepsis. Critical Care Medicine 2003:31(6):1737-1741.

13.  Reith HB, Mittelkotter U, Wagner R, Thiede A. Procalcitonin (PCT) in patients with abdominal sepsis. Intensive Care Med 2000; 26 suppl2: S165-9.

14.  Rau B, Steinbach G, Baumgart K, Gansauge F, et al. The clinical value of procalcitonin in the prediction of infected necrosis in acute pancreatitis. Intensive Care Med 2000; 26, suppl2. S159-64.

15.  Cheval C, Timsit JF, Garrouste-Orgeas M, Assicot M, et al. Procalcitonin (PCT) is useful in predicting the bacterial origin of an acute circulatory failure in critically ill patients. Intensive Care Med 2000; 26, suppl2 S153-8.

16.  Brunkhorst FM, Wegscheider K, Forycki ZF, Brunkhorst R. Procalcitonin for early diagnosis and differentiation of SIRS, sepsis, severe sepsis and septic shock. Intensive Care Med 2000; 26, suppl2 S148-52.

17.  Becker KL, Snider R, Nylen ES. Procalcitonin assay in systemic inflammation, infection, and sepsis: clinical utility and limitations. Crit Care Med 2008; 36(3): 941-52.

18.  Charles PE, Ladoire S, Aho S, Quenot JP, Doise JM, et al. Serum procalcitonin elevation in critically ill patients at the onset of bacteremia caused by either Gram negative or Gram positive bacteria. BMC Infectious Diseases 2008, 8:38 (http://www.biomedcentral.com/1471-2334/8/38)

19.  Wanner GA, Keel M, Steckholzer U, Beier W, Stocker R, Ertel W.  Relationship between procalcitonin plasma levels and severity of injury, sepsis, organ failure, and mortality in injured patients. Critical Care Medicine. 2000; 28(4): 950-957.

20.   Harbath S, Holeckova K, Froidevaux C, Pittet D, et al. Diagnostic Value of Procalcitonin, Interleukin-6, and Interleukin-8 in Critically Ill Patients Admitted with Suspected Sepsis. Amer J Respir Crit Care Med 2001;164: 396-402.

21.   Simon L, Gauvin F, 2 Devendra K. Amre DK,Saint-Louis P, Lacroix J. Serum Procalcitonin and C-Reactive Protein Levels as Markers of Bacterial Infection: A Systematic Review and Meta-analysis. CID 2004: 39:206-217.

22.   Selberg O, Hecker H, Martin M, Klos A Bautsch, et al.  Discrimination of sepsis and systemic inflammatory response syndrome by determination of circulating plasma concentrations of procalcitonin, protein complement 3a, and interleukin-6. Critical Care Medicine. 2000; 28(8): 2793-2798.

23.   Phua J, Koay ES, Lee KH. Lactate, procalcitonin, and amino-terminal pro-B-type natriuretic peptide versus cytokine measurements and clinical severity scores for prognostication in septic shock. Shock 2008; 29(3):328-33.

24.   Zakariah AN ; Cozzi SM ; Van Nuffelen M ; Clausi CM ; Pradier O ; Vincent JL. Combination of biphasic transmittance waveform with blood procalcitonin levels for diagnosis of sepsis in acutely ill patients. Crit Care Med.  2008; 36(5): 1507-12

25.   Viallon A, Guyomarch S, Marjollet O, Berger C, et al. Can Emergency physicians identify a high mortality subgroup of patients with sepsis: role of procalcitonin? Eur J Emerg Med 2008; 15(1):26-33.

26.   Bobre V, Harbarth S, Graf JD, Rohner P, Pugin J. Use of procalcitonin to shorten antibiotic treatment duration in septic patients: a randomized trial. Am J Respir Crit Care Med 2008;177 (5):498-505.

27.   Indino P, Lemarchand P, Bady P, de Torrente A, et al. Prospective study on procalcitonin and other systemic infection markers in patients with leukocytosis. Int J Infect Dis 2008;12 (3):319-24.

The role of biomarkers in the diagnosis of sepsis and patient management
Author: L. H. Bernstein, MD
Key words: Systemic Inflammatory Response Syndrome (SIRS), sepsis, septic shock, mean arterial blood pressure (MAP), procalcitonin, combinatorial analysis, effect size
Highlights:
1. The systemic inflammatory response syndrome (SIRS) is an acute response to trauma, burn, or infectious injury characterized by fever, hemodynamic and respiratory changes, and metabolic changes, not all of which are consistently present.
2. The SIRS reaction involves hormonally driven changes in liver glycogen reserves, triggering of lipolysis, lean body proteolysis, and reprioritization of hepatic protein synthesis with up-regulation of synthesis of acute phase proteins and down-regulation of albumin and important circulating transport proteins.
3. Understanding of the processes leads to the identification of biomarkers for identification of sepsis and severe, moderate or early SIRS, which also can hasten treatment and recovery.
4. The SIRS reaction unabated leads to a recurring cycle with hemodynamic collapse from septic shock, indistinguishable from cardiogenic shock, and death.

Abbreviations: Systemic Inflammatory Response Syndrome (SIRS), procalcitonin (PCT), C-reactive protein (CRP), mean arterial blood pressure (MAP), Intensive care unit (ICU), total white blood cell count (WBC), transthyretin(TTR)

Summary
By focusing on early and accurate diagnosis of infection in patients suspected of SIRS antibiotic overuse and its associated morbidity and mortality may be avoided, and therapeutic targets may be identified. This discussion investigates the performance of diagnostic algorithms and biomarkers for sepsis in patients presenting with leukocytosis and other findings. Suspected patients are usually identified by WBC above 12,000/L PCT level , SIRS and other criteria, such as serum biomarkers of sepsis. In this writer’s study of 435 patients, procalcitonin alone was a superior marker for sepsis. In patients with sepsis there was a marked increase in PCT (p = 0.0001). PCT was increased in patients requiring ICU admission, heart rate and blood pressure monitoring, and assisted ventilation.(p = 0.0001). Means for SIRS/non-SIRS were: CRP 802/404 mg/L; PCT 20.6/7.5 ng/mL; TTR 87.8/125 mg/L. A comprehensive overview of at least a decade of work is provided.

Introduction
Sepsis is a costly diagnosis in hospitalized patients and carries a high financial risk as a comorbidity and a payment penalty for failure to diagnose in a timely manner (1-4) under the severity of illness CMS reimbursement guidelines as a patient safety hazard, with pneumonia and sepsis among the ten most costly among hospital admissions. A polypeptide identical to a prohormone of calcitonin, procalcitonin, was initially described as a potential marker of bacterial disease by Assicot et al.(5). Procalcitonin is almost undetectable under physiological conditions (pg/ml range), but rises to very high values in response to bacteraemia or fungaemia, and appears to be related to the severity of infection.(6) Sequential measurements in patients with bacteraemia have shown a rapid fall within 48 hours of antibiotic administration. There have been numerous studies of the early recognition of sepsis and related diseases in patients related to admission and intensive care. The consensus
guideline has used a SIRS criteria (7, 8). The SIRS criteria (7,8) include temperature </= 36o C. >= 38o C., heart rate > 90 beats per minute, respiratory rate >20 breaths per minute or PaCO2 < 32 mm of Hg, WBC > 12,000/L or < 4,000/L, or > 10% band forms. For the diagnosis of sepsis (2 or more SIRS criteria and confirmed or suspected infection) the SIRS criteria are insufficient with a very high false positive rate, so that there are medical institutions that require three. The observation of fever, tachypnea, and tachycardia may well not be present early, and the observation of leukocytosis with or without band neutrophilia are unreliable. The use of a plasma lactic acid measurement has been added, but it is basically a reflection of decreased splanchnic circulation to the superior mesenteric artery and liver bed. A better case has been made for absolute neutophilia (9), with an adjustment for high lymphocyte counts in children in the first six months, and for the identification of increased immature myeloid precursors (myelocytes and metamyelocytes). The C-reactive protein, a long established acute phase protein, is not predictive at levels under 520 mg/L because it is elevated in a variety of chronic inflammatory conditions. Moreover, it is infrequently used in adult medical practice for that reason, except for the high sensitivity CRP, which has been shown to be relevant to treatment of coronary heart disease by the Jupiter study (10), but also has raised the question of overuse of the statins with the undesirable side effect of skeletal muscle loss. We can explore the validity of over ten years of studies in Europe and US, showing a debated benefit from using the procalcitonin biomarker (PCT, Brahms)(11-28).
Results
A multivariable study with 435 patients to determine whether procalcitonin alone is a superior marker for sepsis established a difference between patients with and without sepsis , as the increase in PCT with sepsis was significant at p = 0.0001. The PCT was also increased in patients who were admitted to the ICU, requiring assisted ventilation and monitoring of heart rate and blood pressure, significant at p = 0.0001. The highest values occur in septic shock, even though mild elevations are seen with localized infection. A PCT level distinguishes between four subgroups of the population: no infection, local infection, sepsis, and severe sepsis and septic shock. The PCT is very low with no infection and rises to levels above 5 with moderate to severe sepsis. Patients in the ICU with SIRS (vs without) have a mean PCT of 35.2 vs 3.7 ng/ml, a clinically as well as statistically significant increase in PCT (Mann-Whitney, p = 0.0001). On the other hand, patients without SIRS in the ICU also have higher CRP [1] and PCT [2] than those not in ICU (1, p = 0.032; 2, p = 0.004), but the CRP difference just reaches statistical significance while the unexpected PCT increase is a big effect. The means obtained for SIRS/non-SIRS are: CRP [1] 802/404 mg/L; PCT [2] 20.6/7.5 ng/ml; TTR [3] 87.8/125 mg/L. So we see an increase of CRP and PCT with SIRS, as expected, and a decrease in TTR to below 100 mg/L as an obligatory response in relationship to the severity of the inflammatory state. The patients with SIRS and those with sepsis, respectively, had significant elevations of CRP [1] and PCT[2], and decrease of TTR[3] by Mann-Whitney test (SIRS, p = 0.006, CRP [1]; 0.0001, PCT [2]; 0.0001 TTR[3]; sepsis, p = 0.010, CRP [1]; 0.014, PCT [2]; 0.004, TTR [3]).
Finally, we are particularly interested in combinations of variables for predicting infection and the stage of infection using PCT, MAP (mean arterial blood pressure), WBC. The model fit looks good based on the chi-squared statistics.

Degrees of freedom (df) 282 p-value
L-squared (L²)       217.69       1.00
X-squared                235.44       0.98
Cressie-Read           209.15       1.00

aBIC (based on LL)      634
bAIC (based on LL)     495
aBayes Information Criterion, bAkaike’s Information Criterion

Model for Dependent
Class1    Class2       Class3    Class4     Overall
R² 0.7961    0.9136    0.9782   0.6410   0.9319

The chi-squared with a p-value close to 1 indicates that the partitioning of the combinatorial groups is excellent, and the model is not underfit or overfit. A second cluster LCA model using SIRS as covariate also gives a good fit. The p-values are acceptable.
Chi-squared Statistics
Degrees of freedom (df) 258      p-value
L-squared (L²)              248.96      0.65
X-squared                       230.62      0.89
Cressie-Read                  222.07     0.95
BIC (based on L²)       -1238.46
AIC (based on L²)        -267.04
Even though CRP has validity for identifying SIRS in our exploratory study, the specificity and its usefulness at a cutoff at 52 mg/dL raised significant concerns with respect to with respect to distinguishing SIRS with and without infection. Keep in mind that large variances in CRP exist between the subgroups, which is problematic because of the CRP elevation in patients with metabolic syndrome and with chronic inflammatory diseases, but not necessarily sepsis. TTR is also decreased, as CRP is elevated, in patients with inflammatory conditions without sepsis.
The data demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. We also showed the elevation of PCT in concert with severity of infection, as determined by medical record review PWe would expect and find elevations of PCT with pneumonia, deep wounds, and pyelonephritis as well as sepsis, but these patients would be expected to meet the SIRS criteria. Our study was not designed to demonstrate how PCT might detect sepsis in older patients with negative SIRS criteria in the ICU who are on ventilator assistance and who may not develop a febrile response. One has to consider that this is related to PCT elevation being partly independent of the SIRS response.
We then showed the same relationship to biomarker combinations that classify the data in accordance with the severity of infection. The WBC count is the weakest classification variable, but it is in the SIRS criteria and it is of greatest value with a finding of immature neutrophils. However, the band count is now considered part of the mature neutrophil count so that the absolute neutrophil count and the immature granulocytes measured by flow cytometry (myelocytes and metamyelocytes) are superior to the tWBC and bands ( ). The MAP is valuable for identifying the patients at highest risk of circulatory collapse with a drop in the MAP and transfer to ICU (on pressors). The drop in MAP within 72 hours is important for making decisions about Activated protein C (Xygris), which is a critical decision. APC has been removed from the market. We included the TTR, which decreases in patients with SIRS in proportion to the severity of illness. We asked whether we can combine the key predictor variable into combinatorial classes that would improve the accuracy of identification. CRP was not of interest with respect to this analysis as the poor specificity could only confound matters, and the test offers no additional information than PCT provides.
Our study is unique in at least two respects: It is the first to clearly demonstrate a graded response of PCT to severity of infectious challenge. It is also a rare study to use a classification method to study the effect of combinations of variables associated with SIRS and infection on PCT elevation (11-13). We have created a graded classification by using feature extraction and forming an N-length class based on established information principles (Kullback entropy and Akaike Information Criteria). The features used to classify the data were PCT, MAP, TTR, WBC and a SIRS score of at least two. The data was also classified without using PCT in order to establish validity for PCT independently of a classification using the feature being evaluated.The classifications have been extensively examined using one-way ANOVA, Kruskal Wallis analysis by ranks, and latent class analyses. The Kruskal-Wallis analysis by ranks is a powerful tool for comparing the PCT levels within and across feature classes when the variance of PCT values across groups does not have the same distribution and the assumption of normal distribution doesn’t hold. Latent class analysis is a group of methods that can be used to classify data when the data is converted to ordinal classes under the assumption that there is a hidden or “latent” underlying classification. In defining latent classes we assume the criterion of “conditional independence,” so that, each variable is statistically independent of every other variable within each latent class, In our case, latent classes correspond to probabilities for and against the presence of a distinct medical syndrome. In this case we call attention to the classes representing no infection, soft tissue infection, sepsis, and severe sepsis or septic shock. In reality, the variables used to form the classes are not independent, but they are used as ordinal variables and can be ranked in order of importance in forming a classification. There is a paper of some interest with regard to classification and prediction of severe sepsis that finds PCT, lactic acid and aminoterminal pro B-type natriuretic peptide correlating with sepsis severity scores (12) and another using PCT in combination with waveform analysis (13). Classification and prediction has been of particular interest to the corresponding investigator for laboratory procedure validation for more than 10 years (20-22). We provide valuable references to this approach (23-27).
In all respects, we find agreement with a large number of studies, including those recently cited (5-19). PCT has been shown to be useful for discriminating systemic inflammatory response, infection and sepsis (5,6) and identifying a high mortality subgroup with sepsis (15), for identifying sepsis at the onset with either gram negative or gram positive bacteremia (10), for evaluating time to treatment effectiveness (16), and for identifying sepsis in the febrile neutropenic patient (18).
We have demonstrated a clear relationship between high PCT and both SIRS and the ICU placement of the patient. In addition, we have shown the strength of classifying these patients using PCT in combination with MAP, TTR, WBC and SIRS.

References

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Table 1. Comparison of key sepsis biomarkers by means between ICU and non-ICU, SIRS positive status, and sepsis status.

Marker

Mean

p

SIRS Positive

ICU vs not

CRP (mg/L) 780 495 0.166
PCT (ng/ml) 35.2 3.7 0.0001

SIRS negative

ICU vs not

PCT (ng/ml) 0.0001

Sepsis Diagnosis

ICU vs not

CRP (mg/L) 817 521 0.010
PCT (ng/ml) 0.014
WBC 0.921
% neutrophils 0.452

SIRS with WBC

ICU vs not

CRP (mg/L) 802 404 0.006
PCT (ng/ml) 20.6 7.5 0.0001

Table 2. Comparison of PCT, MAP, TTR and WBC means and variation in SIRS and ICU placement.

variable-by-variablea

Fisher’s Exact testb

t-testc

PCT*SIRS

0.0001

0.0210

PCT*ICU

0.0001

0.0001

MAP*SIRS

0.0130

MAP*ICU

0.0001

0.0001

WBC*SIRS

0.0001

0.0001

WBC*ICU

NS

TTR*SIRS

0.0001

0.0001

TTR*ICU

0.0001

atwo variables, b,cp-value

Archival Table

Table 3.  Classes and 4-variable contributions for 4-class LCA cluster model.

Cluster Size

0.3646             0.2738             0.2209             0.1408

Indicators

PCT0425         (PCT: < 0.4, 0.41-2.5, > 2.5)

0          0.6393             0.8894             0.1278             0.0000

1          0.3190             0.1076             0.3752             0.0013

2          0.0355             0.0029             0.2459             0.0285

3          0.0062             0.0001             0.2511             0.9702

MAP758088    (MAP: > 88, 81-87, 75-80, < 80)

0          0.5234             0.6186             0.3709             0.4228

1          0.1861             0.1794             0.1771             0.1828

2          0.1065             0.0838             0.1361             0.1272

3          0.1841             0.1181             0.3160             0.2673

WBC1217       (WBC: < 12, 12-17, > 17)

0          0.3325             0.1772             0.0002             0.3084

1          0.4152             0.3948             0.0216             0.4171

2          0.2523             0.4280             0.9782             0.2745

TTR7105         (TTR: > 10.5, 7.0-10.5, < 7)

0          0.2457             0.9805             0.2159             0.3920

1          0.3352             0.0192             0.3279             0.3391

2          0.4191             0.0003             0.4562             0.2688

            Table 1. Comparison of key sepsis biomarkers by means between ICU and non-ICU, SIRS positive status, and sepsis status.

Marker

Mean

p

SIRS Positive

ICU vs not

CRP (mg/L) 780 495 0.166
PCT (ng/ml) 35.2 3.7 0.0001

SIRS negative

ICU vs not

PCT (ng/ml) 0.0001

Sepsis Diagnosis

ICU vs not

CRP (mg/L) 817 521 0.010
PCT (ng/ml) 0.014
WBC 0.921
% neutrophils 0.452

SIRS with WBC

ICU vs not

CRP (mg/L) 802 404 0.006
PCT (ng/ml) 20.6 7.5 0.0001

Table 2. Comparison of PCT, MAP, TTR and WBC means and variation in SIRS and ICU placement.

variable-by-variablea

Fisher’s Exact testb

t-testc

PCT*SIRS

0.0001

0.0210

PCT*ICU

0.0001

0.0001

MAP*SIRS

0.0130

MAP*ICU

0.0001

0.0001

WBC*SIRS

0.0001

0.0001

WBC*ICU

NS

TTR*SIRS

0.0001

0.0001

TTR*ICU

0.0001

atwo variables, b,cp-value

Archival Table

Table 3.  Classes and 4-variable contributions for 4-class LCA cluster model.

Cluster Size

0.3646             0.2738             0.2209             0.1408

Indicators

PCT0425         (PCT: < 0.4, 0.41-2.5, > 2.5)

0          0.6393             0.8894             0.1278             0.0000

1          0.3190             0.1076             0.3752             0.0013

2          0.0355             0.0029             0.2459             0.0285

3          0.0062             0.0001             0.2511             0.9702

MAP758088    (MAP: > 88, 81-87, 75-80, < 80)

0          0.5234             0.6186             0.3709             0.4228

1          0.1861             0.1794             0.1771             0.1828

2          0.1065             0.0838             0.1361             0.1272

3          0.1841             0.1181             0.3160             0.2673

WBC1217       (WBC: < 12, 12-17, > 17)

0          0.3325             0.1772             0.0002             0.3084

1          0.4152             0.3948             0.0216             0.4171

2          0.2523             0.4280             0.9782             0.2745

TTR7105         (TTR: > 10.5, 7.0-10.5, < 7)

0          0.2457             0.9805             0.2159             0.3920

1          0.3352             0.0192             0.3279             0.3391

2          0.4191             0.0003             0.4562             0.2688

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