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Multicenter Study
. 2025 May 13;16(1):4450.
doi: 10.1038/s41467-025-59643-z.

Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory

Affiliations
Multicenter Study

Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory

Suraj Rajendran et al. Nat Commun. .

Abstract

Corticosteroids decrease the duration of organ dysfunction in sepsis and a range of overlapping and complementary infectious critical illnesses, including septic shock, pneumonia and the acute respiratory distress syndrome (ARDS). The risk and benefit of corticosteroids are not fully defined using the construct of organ dysfunction duration. This retrospective multicenter, proof-of-concept study aimed to evaluate the association between usage of corticosteroids and mortality of patients with sepsis, pneumonia and ARDS by emulating a target trial framework stratified by predicted organ dysfunction trajectory. The study employed a two staged machine learning (ML) methodology to first subphenotype based on organ dysfunction trajectory then predict this defined trajectory. Once patients were classified by predicted trajectory we conducted a target trial emulation. Our analysis revealed that the association between corticosteroid use and 28-day mortality varied by predicted trajectory and between cohorts.Our findings suggest that matching treatment strategies to empirically observed pathobiology may offer a more nuanced understanding of corticosteroid utility.

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Conflict of interest statement

Competing interests: E.S. received personal fees from Axle Informatics outside of stated work. The remaining authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Overview of analyses conducted in study.
Relevant covariates and patient information were extracted from multiple data cohorts. These patients were then stratified and processed as per trial emulation setup. Statistical methods were then used to determine relevant outcomes.
Fig. 2
Fig. 2. Kaplan–Meier plots for eICU-MIMIC.
Different outcomes for both treated and untreated patients in the entire cohort and RI, RW subphenotypes are depicted. Kaplan Meier plots were based on propensity-score matched cohorts. Bands around the Kaplan–Meier curves indicate 95% confidence intervals.
Fig. 3
Fig. 3. Hazard ratios and cumulative incidence for 28-day mortality in the eICU-MIMIC cohort.
Forest plot shows the hazard ratios (center of the bar) with 95% confidence intervals for each patient stratification. Dashed vertical line represents a hazard ratio of 1. Cumulative incidences for treated and untreated patients are shown on the right. n = 13704 for All patients, n = 4102 for RI patients, n = 4802 for RW patients. Source data are provided as a Source Data file.
Fig. 4
Fig. 4. Hazard ratios and cumulative incidence for time to ICU discharge outcome in eICU-MIMIC cohort.
Forest plot shows the hazard ratios (center of the bar) and 95% confidence intervals for each patient stratification. Dashed vertical line represents a hazard ratio of 1. Cumulative incidences for treated and untreated patients are shown on the right. n = 13702 for All patients, n = 4112 for RI patients, n = 4818 for RW patients. Source data are provided as a Source Data file.
Fig. 5
Fig. 5. Hazard ratios and cumulative incidence for time to cessation of mechanical ventilation outcome in eICU-MIMIC cohort.
Forest plot shows the hazard ratios (center of the bar) and 95% confidence intervals for each patient stratification. Dashed vertical line represents a hazard ratio of 1. Cumulative incidences for treated and untreated patients are shown on the right. n = 9576 for All patients, n = 2986 for RI patients, n = 3744 for RW patients. Source data are provided as a Source Data file.

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