Mortality Risk Profiles for Sepsis: A Novel Longitudinal and Multivariable Approach

Abstract

Objectives: To determine if a set of time-varying biological indicators can be used to: 1) predict the sepsis mortality risk over time and 2) generate mortality risk profiles. Design: Prospective observational study. Setting: Nine Canadian ICUs. Subjects: Three-hundred fifty-six septic patients. Interventions: None. Measurements and Main Results: Clinical data and plasma levels of biomarkers were collected longitudinally. We used a complementary log-log model to account for the daily mortality risk of each patient until death in ICU/hospital, discharge, or 28 days after admission. The model, which is a versatile version of the Cox model for gaining longitudinal insights, created a composite indicator (the daily hazard of dying) from the “day 1” and “change” variables of six time-varying biological indicators (cell-free DNA, protein C, platelet count, creatinine, Glasgow Coma Scale score, and lactate) and a set of contextual variables (age, presence of chronic lung disease or previous brain injury, and duration of stay), achieving a high predictive power (conventional area under the curve, 0.90; 95% CI, 0.86–0.94). Including change variables avoided misleading inferences about the effects of day 1 variables, signifying the importance of the longitudinal approach. We then generated mortality risk profiles that highlight the relative contributions among the time-varying biological indicators to overall mortality risk. The tool was validated in 28 nonseptic patients from the same ICUs who became septic later and was subject to 10-fold cross-validation, achieving similarly high area under the curve. Conclusions: Using a novel version of the Cox model, we created a prognostic tool for septic patients that yields not only a predicted probability of dying but also a mortality risk profile that reveals how six time-varying biological indicators differentially and longitudinally account for the patient’s overall daily mortality risk.

The Concentration of Large Extracellular Vesicles Differentiates Early Septic Shock From Infection

“…The difference in the number of lEVs between septic shock and infected patients was most prominent at the onset of the disease and gradually reduced as the patients progress through their clinical course. The observed longitudinal changes of plasma lEVs concentration is similar to many biologically active compounds with elevated levels during sepsis (e.g., c-reactive protein, interleukin 6) (15)(16)(17). Given that point-of-care EV quantification tests are under development (18), our findings suggest that lEVs quantification could be one of the means to identify patients with septic shock early in its course.…”

Immunothrombosis Biomarkers for Distinguishing Coronavirus Disease 2019 Patients From Noncoronavirus Disease Septic Patients With Pneumonia and for Predicting ICU Mortality

“…For predicting mortality, we let the dependent variable be the probability of dying and used the values of all biomarkers on the “last” day, which is defined as the most recent day on which a nonmissing value was available. Our choice of the last-day values over the day 1 values of biomarkers for ICU mortality analysis was based on our previous finding that longitudinal changes in biomarker levels are more important than the day 1 biomarker values in determining their predictive powers on ICU mortality ( 27 ). We also report additional findings from multivariate logit models via the “forward stepwide method” ( Supplemental Text 2, Supplemental Tables 5–10, and Supplemental Fig.…”

Prognostic Value of Nucleated RBCs for Patients With Suspected Sepsis in the Emergency Department: A Single-Center Prospective Cohort Study

“…Development and validation of multivariable predictive models require a different study design ( 19 ). There are several suggested multivariable predictive models for patients with sepsis ( 20 , 21 ), but to our knowledge none that include NRBCs. Thus, inclusion of NRBCs might improve existing predictive models.…”