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

Abstract

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.

Keywords: biomarkers; longitudinal analysis; mortality; mortality risk profiles; sepsis.

Figure 1.

Relative predictive powers and temporal patterns of the time-varying biological indicators (TVBIs). A, The relative contributions of the day 1 and change variables of the six TVBIs to their combined predictive power in 356 septic patients (difference in the log of hazard of dying between nonsurvivors and survivors). The sizes of areas are proportional to their shares of their combined predictive power (shown in Supplemental Table 5, Supplemental Digital Content 1, http://links.lww.com/CCX/A76). B–G, Temporal patterns of the daily averages of Glasgow Coma Scale (GCS) (B), lactate (C), cell-free DNA (cfDNA) (D), protein C (PC) (E), platelet count (F), and creatinine (G). For each TVBI, the septic patients were divided into four quartile groups based on the values of its day 1 variable. Blue line (best quartile group), green line (second best quartile group), brown line (third best quartile group), and red line (worst quartile group). The normal levels in healthy individuals are as follows: 15 for GCS, 0.5 to 1.0 mmol/L for lactate, 2.2 ± 0.6 µg/mL for cfDNA, 61–133 U/mL for PC, 150 to 400 × 10⁹/L for platelets, and less than or equal to 100 µmol/L for creatinine.

Figure 2.

The trajectories of the Glasgow Coma Scale (GCS) levels (A) and the predicted probabilities of dying in 7 d (B) for three patients with large changes in GCS: brown line for a survivor discharged on day 8; blue line for a survivor censored on day 28; and red line for a nonsurvivor who died on day 5.

Figure 3.

The mortality risk profile that highlights the relative contribution of each time-varying biological indicator (TVBI) to the risk of dying. The top shows the separate effects of day 1 and change variables of each TVBI for a sample patient in terms of his difference in log of hazard from the benchmark, with black bars for day 1 effects and white bars for change effects. Relative to the benchmark, the patient had a higher risk of death that is mainly attributable to unfavorable values of Glasgow Coma Scale (GCS) (contributing 0.77 to the difference), protein C (0.65), lactate (0.52), cell-free DNA (cfDNA) (0.34), and platelets (0.28) on day 1. However, the improvements in GCS, lactate, and cfDNA between day 1 and day 28 helped to reduce the difference in log of hazard markedly by –0.41 for GCS, –0.38 for lactate, and –0.36 for cfDNA, although these were offset by some worsening attributable to changes in creatinine (0.27), platelets (0.14), and protein C (0.08) relative to the benchmark. The middle shows the combined effect of the day 1 and change variables for each TVBI (i.e., the middle is the sum of the “day 1 variable” bar and the “change variable” bar in the top). Since GCS and lactate improved markedly, their combined effects (0.37 and 0.14) became much less than that of protein C (0.73). After translating the information in the middle into the familiar measures of hazard ratios (HRs) by exponentiation, the bottom shows HR-1 for each TVBI, because HR = 1 (no effect) should be represented by a bar of zero length. The three highest HRs between the patient and the benchmark were 2.09 for protein C, 1.51 for platelets, and 1.44 for GCS. The pattern suggests that abnormalities in protein C, platelets, and GCS are the major contributors to this patient’s risk of dying.