ArticleCritical care (London, England)2022
Sepsis subphenotyping based on organ dysfunction trajectory.
Article in Critical care (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07773571 (Development of an ICU Physiological State Space Monitor Based on the ICCA Database), which is not on this map. Cited by 61 papers.
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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.
Development of an ICU Physiological State Space Monitor Based on the ICCA Database: A Single-Center Retrospective Observational Study
Who cites it
61 citing papers in PubMed, 79 citations in OpenAlex.
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- Anion gap trajectory patterns and prognosis in sepsis patients: A multicenter retrospective study.Medicine · 2026Article
- Comparative prognostic performance of SOFA-1 and SOFA-2 in patients with sepsis at ICU admission.Clinical medicine (London, England) · 2026Article
- 7-day longitudinal proteomics of critically ill patients: a pilot study.Scientific reports · 2026Observational
- Early heart-rate trajectory phenotypes predict short-term mortality in critically ill patients: a dynamic time-warping cluster analysis.Journal of clinical monitoring and computing · 2026Article
- Elastic functional Cox regression model with shape predictors.Journal of applied statistics · 2026Article
- Dynamic prognostic nutritional index and 28-day mortality in sepsis: a joint modeling analysis.Nutrition & metabolism · 2026Article
- SOFA-2 score predicts mortality in pneumonia-associated sepsis: a retrospective cohort study.Critical care (London, England) · 2026Article
- Contrastive Transformer-Driven Discovery of Temporal Hemodynamic Subphenotypes in Cardiac Surgery Patients.medRxiv : the preprint server for health sciences · 2026Article
- Distinct 72-hour fluid balance trajectories are associated with 28-day mortality in a multicenter cohort of sepsis patients.Scientific reports · 2026Observational
- Dynamic association between triglyceride-glucose-body mass index and hospital mortality in critically ill patients with heart failure: a multicenter retrospective cohort study.Cardiovascular diabetology · 2026Observational
- Predictive Model of Dynamic Subphenotypes for 30-Day Mortality in Emergency Department Patients with Suspected Infection Using the Vital Signs of the First 24 Hours: An Analytical Cohort Study in a Tertiary Care Clinic.Journal of clinical medicine · 2026Article
- 101 machine learning algorithms for predicting mortality in critically ill patients with spinal cord injury and sarcopenia: a multi-database study.BMC medical informatics and decision making · 2026Observational
- Precision medicine in sepsis: reappraising glucocorticoid therapy through the lens of molecular endotypes.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026Review
- Data-driven spatial-temporal framework for exploring the heterogeneity and temporality of sepsis.Chinese medical journal · 2026Review
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- The immunology of sepsis: translating new insights into clinical practice.Nature reviews. Nephrology · 2026Review
- Timing of Core Sepsis Bundle Elements Initiation in Critically Ill Patients: A Multicenter Target Trial Emulation Study.Clinical epidemiology · 2026Article
1 more citing papers are in PubMed but not listed here.
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundSepsis is a heterogeneous syndrome, and the identification of clinical subphenotypes is essential. Although organ dysfunction is a defining element of sepsis, subphenotypes of differential trajectory are not well studied. We sought to identify distinct Sequential Organ Failure Assessment (SOFA) score trajectory-based subphenotypes in sepsis.
methodsWe created 72-h SOFA score trajectories in patients with sepsis from four diverse intensive care unit (ICU) cohorts. We then used dynamic time warping (DTW) to compute heterogeneous SOFA trajectory similarities and hierarchical agglomerative clustering (HAC) to identify trajectory-based subphenotypes. Patient characteristics were compared between subphenotypes and a random forest model was developed to predict subphenotype membership at 6 and 24 h after being admitted to the ICU. The model was tested on three validation cohorts. Sensitivity analyses were performed with alternative clustering methodologies.
resultsA total of 4678, 3665, 12,282, and 4804 unique sepsis patients were included in development and three validation cohorts, respectively. Four subphenotypes were identified in the development cohort: Rapidly Worsening (n = 612, 13.1%), Delayed Worsening (n = 960, 20.5%), Rapidly Improving (n = 1932, 41.3%), and Delayed Improving (n = 1174, 25.1%). Baseline characteristics, including the pattern of organ dysfunction, varied between subphenotypes. Rapidly Worsening was defined by a higher comorbidity burden, acidosis, and visceral organ dysfunction. Rapidly Improving was defined by vasopressor use without acidosis. Outcomes differed across the subphenotypes, Rapidly Worsening had the highest in-hospital mortality (28.3%, P-value < 0.001), despite a lower SOFA (mean: 4.5) at ICU admission compared to Rapidly Improving (mortality:5.5%, mean SOFA: 5.5). An overall prediction accuracy of 0.78 (95% CI, [0.77, 0.8]) was obtained at 6 h after ICU admission, which increased to 0.87 (95% CI, [0.86, 0.88]) at 24 h. Similar subphenotypes were replicated in three validation cohorts. The majority of patients with sepsis have an improving phenotype with a lower mortality risk; however, they make up over 20% of all deaths due to their larger numbers.
conclusionsFour novel, clinically-defined, trajectory-based sepsis subphenotypes were identified and validated. Identifying trajectory-based subphenotypes has immediate implications for the powering and predictive enrichment of clinical trials. Understanding the pathophysiology of these differential trajectories may reveal unanticipated therapeutic targets and identify more precise populations and endpoints for clinical trials.
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