ReviewIntensive care medicine2025
Sepsis subphenotypes, theragnostics and personalized sepsis care.
Review in Intensive care medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 2 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Effects on mortality of different blood purification techniques in sepsis patients: an umbrella review of systematic reviews and meta-analyses.Renal failure · 2026Pooled it
- Assessing Monoclonal and Polyclonal Antibodies in Sepsis and Septic Shock: A Systematic Review of Efficacy and Safety.International journal of molecular sciences · 2025Pooled it
- Body mass index and baricitinib treatment effect in hospitalized adults with COVID-19: A secondary analysis of ACTT-2.Heart & lung : the journal of critical careTrial
- A multimodal predictive model incorporating transcriptomic-guided blood biomarkers and clinical variables for sepsis-associated acute kidney injury.Renal failure · 2026Article
- Physiological Phenotypes in Comatose ICU Patients: A Retrospective Multidimensional Analysis.Diagnostics (Basel, Switzerland) · 2026Article
- The Acute Respiratory Distress Syndrome (ARDS): epidemiology, etiology, molecular mechanisms, diagnosis and therapeutic strategies.Molecular biomedicine · 2026Review
- Epigenetic regulation of neutrophil dysfunction in sepsis: mechanisms, biomarkers, and translational challenges.Journal of translational medicine · 2026Review
- Using interpretable machine learning to analyze the trajectory changes of serum albumin to predict the mortality rate of sepsis: a cohort study based on MIMIC-IV.BMC infectious diseases · 2026Article
- Update on sepsis treatment.Journal of intensive care · 2026Review
- Review
- The evolution of sepsis care: from protocol-driven management to personalized intensive care.Infection · 2026Review
- Phenotype discovery and mortality prediction in sepsis-induced myocardial dysfunction: a deep learning and stratified modeling approach.BMC medical informatics and decision making · 2026Article
- Predicting 28-day and 90-day mortality in microbiologically-confirmed sepsis: a retrospective cohort study.BMC infectious diseases · 2026Article
- Machine learning-based precision subtyping and risk prediction in sepsis: a retrospective analysis using MIMIC-IV database.BMC infectious diseases · 2026Article
- Clinical subtyping of severe acute pancreatitis reveals heterogeneous associations with early management strategies: a multicenter retrospective cohort study.Critical care (London, England) · 2026Article
- Challenges in early detection and prognostication of sepsis: new approaches from the emergency department and intensive care unit.EClinicalMedicine · 2026Review
- Treatment Response Phenotyping Informed by Patient Physiologic Characteristics Could Drive Precision Critical Care Through Augmented Intelligence: A Narrative Review.CHEST critical care · 2026Article
- Subphenotype- and complication-guided adjunctive fosfomycin versus standard monotherapy inThe Lancet regional health. Europe · 2026Article
- Bench-to-Bedside Insights into the Challenges of Immunosuppression in Sepsis.Pathogens (Basel, Switzerland) · 2026Review
- Update on sepsis and septic shock: from bundles to precision medicine.Intensive care medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Heterogeneity between critically ill patients with sepsis is a major barrier to the discovery of effective therapies. The use of machine learning techniques, coupled with improved understanding of sepsis biology, has led to the identification of patient subphenotypes. This exciting development may help overcome the problem of patient heterogeneity and lead to the identification of patient subgroups with treatable traits. Re-analyses of completed clinical trials have demonstrated that patients with different subphenotypes may respond differently to treatments. This suggests that future clinical trials that take a precision medicine approach will have a higher likelihood of identifying effective therapeutics for patients based on their subphenotype. In this review, we describe the emerging subphenotypes identified in the critically ill and outline the promising immune modulation therapies which could have a beneficial treatment effect within some of these subphenotypes. Furthermore, we will also highlight how bringing subphenotype identification to the bedside could enable a new generation of precision-medicine clinical trials.
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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.