ArticleNature communications2025
Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07511582 (Efficacy, Safety, and Tolerability of Methylprednisolone in Critically Ill Patients With the Hyperinflammatory Phenotype), which is not on this map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Efficacy, Safety, and Tolerability of Methylprednisolone in Critically Ill Patients With the Hyperinflammatory Phenotype: A Multicenter, Randomized, Double-Blind, Placebo-Controlled Phase II Trial
Who cites it
15 citing papers in PubMed.
- Article
- Lymphopenia and elevated NLR identify patients with septic shock who may benefit from corticosteroids: a target trial emulation study.Intensive care medicine experimental · 2026Article
- The Acute Respiratory Distress Syndrome (ARDS): epidemiology, etiology, molecular mechanisms, diagnosis and therapeutic strategies.Molecular biomedicine · 2026Review
- Empowering clinical trial design with agentic intelligence and real-world data.Nature communications · 2026Article
- The role of hemoadsorption in septic shock: toward a personalized approach.Critical care (London, England) · 2026Review
- Large language model-augmented offline reinforcement learning framework for sepsis management in critical care.NPJ digital medicine · 2026Article
- Time-varying associations between corticosteroid dose and hospital mortality in ARDS: a sliding-window analysis of MIMIC-IV.BMC pulmonary medicine · 2026Observational
- Clinical subphenotypes of sepsis based on mixed continuous and categorical data and differences in treatment effects: a cluster analysis of multicenter observational studies.Critical care (London, England) · 2026Observational
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Article
- Early versus delayed enteral nutrition in septic shock: a target trial emulation study.Frontiers in nutrition · 2026Article
- Normal initial lactate level in sepsis patients: is lactate still useful for prognosis prediction?World journal of emergency medicine · 2026Article
- Opportunities, challenges and future perspectives for target trial emulation in critical care clinical research.Critical care (London, England) · 2025Review
- Federated Target Trial Emulation using Distributed Observational Data for Treatment Effect Estimation.medRxiv : the preprint server for health sciences · 2025Article
- Artificial intelligence-assisted phenotyping of sepsis: Research progress, clinical challenges, and translational prospects.Digital healthReview
Corrections and comments
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Authors and funding
10 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.