Development of an Algorithm to Predict Mortality in Patients With Sepsis and Coagulopathy

Clinical and Applied Thrombosis/hemostasis : Official Journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
Amanda WalbornDebra Hoppensteadt

Abstract

Sepsis is a systemic response to infection with a high rate of mortality and complex pathophysiology involving inflammation, infection response, hemostasis, endothelium, and platelets. The purpose of this study was to develop an equation incorporating biomarker levels at intensive care unit (ICU) admission to predict mortality in patients with sepsis, based on the hypothesis that a combination of biomarkers representative of multiple physiological systems would provide improved predictive value. Plasma samples and clinical data were collected from 103 adult patients with sepsis at the time of ICU admission. Biomarker levels were measured using commercially available methods. A 28-day mortality was used as the primary end point. Stepwise linear regression modeling was performed to generate a predictive equation for mortality. Differences in biomarker levels between survivors were quantified using the Mann-Whitney test and the area under the receiver operating curve (AUC) was used to describe predictive ability. Significant differences (P < .05) were observed between survivors and nonsurvivors for plasminogen activator inhibitor 1 (AUC = 0.70), procalcitonin (AUC = 0.77), high mobility group box 1 (AUC = 0.67), interleukin (IL) 6...Continue Reading

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Citations

Oct 30, 2020·Risk Management and Healthcare Policy·Xin LongMinghao Fang

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Methods Mentioned

BETA
enzyme-linked immunosorbent assays
Assay
chip

Software Mentioned

Excel
GraphPad Prism
MATLAB

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