A Transcriptomic Severity Metric That Predicts Clinical Outcomes in Critically Ill Surgical Sepsis Patients

Abstract

OBJECTIVES: Clinically deployable methods for the rapid and accurate prediction of sepsis severity that could elicit a meaningful change in clinical practice are currently lacking. We evaluated a whole-blood, multiplex host-messenger RNA expression metric, Inflammatix-Severity-2, for identifying septic, hospitalized patients' likelihood of 30-day mortality, development of chronic critical illness, discharge disposition, and/or secondary infections. DESIGN: Retrospective, validation cohort analysis. SETTING: Single, academic health center ICU. PATIENTS: Three hundred thirty-five critically ill adult surgical patients with sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Whole blood was collected in PAXgene Blood RNA collection tubes at 24 hours after sepsis diagnosis and analyzed using a custom 29-messenger RNA classifier (Inflammatix-Severity-2) in a Clinical Laboratory Improvement Amendments certified diagnostic laboratory using the NanoString FLEX platform. Among patients meeting Sepsis-3 criteria, the Inflammatix-Severity-2 severity score was significantly better (p < 0.05) at predicting secondary infections (area under the receiver operating curve 0.71) and adverse clinical outcomes (area under the receiver operating curve 0.75) than C-reactive protein, absolute lymphocyte counts, total WBC count, age, and Charlson comorbidity index (and better, albeit nonsignificantly, than interleukin-6 and Acute Physiology and Chronic Health Evaluation II). Using multivariate logistic regression analysis, only combining the Charlson comorbidity index (area under the receiver operating curve 0.80) or Acute Physiology and Chronic Health Evaluation II (area under the receiver operating curve 0.81) with Inflammatix-Severity-2 significantly improved prediction of adverse clinical outcomes, and combining with the Charlson comorbidity index for predicting 30-day mortality (area under the receiver operating curve 0.79). CONCLUSIONS: The Inflammatix-Severity-2 severity score was superior at predicting secondary infections and overall adverse clinical outcomes compared with other common metrics. Combining a rapidly measured transcriptomic metric with clinical or physiologic indices offers the potential to optimize risk-based resource utilization and patient management adjustments that may improve outcomes in surgical sepsis. Hospitalized patients who are septic and present with an elevated IMX-SEV2 severity score and preexisting comorbidities may be ideal candidates for clinical interventions aimed at reducing the risk of secondary infections and adverse clinical outcomes.