Abstract
Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p < 0.01) and within 60 days (40% vs 15%, p = 0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p = 0.03) and an Integrated Discrimination Improvement index of 0.07 (p = 0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected > 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.
Highlights
Several clinical calculators predict intensive care unit (ICU) mortality, these are cumbersome and often require 24 h of data to calculate
The most widely known of these scoring systems are the Simplified Acute Physiology Score (SAPS) and the Acute Physiology and Chronic Health Evaluation (APACHE) s core[8,9,10]
We further looked at performance in predicting both 60-day mortality as well as in-hospital mortality in two pre-specified subgroups: (1) patients in shock, which was defined as requiring at least one vasopressor, and (2) patients whose primary driver of prognosis was multi-system organ dysfunction syndrome (MODS) or acute respiratory distress syndrome (ARDS)
Summary
Several clinical calculators predict intensive care unit (ICU) mortality, these are cumbersome and often require 24 h of data to calculate. We tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. The most widely known of these scoring systems are the Simplified Acute Physiology Score (SAPS) and the Acute Physiology and Chronic Health Evaluation (APACHE) s core[8,9,10] In addition to their limited predictive capacity, these tools are designed around ICU admission data, and cannot be used prospectively to risk-stratify patients at emergency department admission or to select patients for enrollment into clinical trials[3]. To address these shortcomings, there has been significant interest in developing molecular diagnostic assays to better risk stratify patients with critical illness[3,11,12,13]. We further examine the impact of timing of blood draw, patient comorbidities, and acuity of illness as a driver of prognosis on test performance
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