Trial reportIntensive care medicine2022
Development and validation of novel sepsis subphenotypes using trajectories of vital signs.
Trial report in Intensive care medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05826223 (Implementation and Prospective Validation of a Sepsis Sub-phenotyping Algorithm Based on Vital Sign Trajectories), which is not on this map. Cited by 90 papers.
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.
Implementation and Prospective Validation of a Sepsis Sub-phenotyping Algorithm Based on Vital Sign Trajectories
Who cites it
90 citing papers in PubMed, 132 citations in OpenAlex.
- Predicting mortality with machine learning & biomarkers: A cohort analysis from aerosolized β₂-agonist for treatment of acute lung injury (ALTA) trial.Physiological reports · 2026Trial
- Plasma matrix metalloproteinase-3 predicts mortality in acute respiratory distress syndrome: a biomarker analysis of a randomized controlled trial.Respiratory research · 2023Trial
- Bedside monitoring of the vascular response to norepinephrine in early septic shock: VNERi trajectories and comparison with dynamic clinical measures.Journal of clinical monitoring and computing · 2026Article
- Article
- Noradrenaline-trajectory phenotypes in septic shock: derivation and external validation in two independent cohorts.Intensive care medicine experimental · 2026Article
- 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
- Association between blood urea nitrogen trajectory phenotypes and prognosis in patients with sepsis: a multicenter retrospective cohort study.BMC infectious diseases · 2026Observational
- Artificial intelligence-driven cluster analysis for identifying clinical phenotypes in suspected sepsis patients in the emergency department.BMC emergency medicine · 2026Article
- Stratifying mortality risk in hypotension using outcome-oriented clustering of vital sign trajectories.iScience · 2026Article
- 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
- Treatment Response Phenotyping Informed by Patient Physiologic Characteristics Could Drive Precision Critical Care Through Augmented Intelligence: A Narrative Review.CHEST critical care · 2026Article
- Establishment and validation of a rat sepsis model aligned with sepsis-3 via Staphylococcus aureus tail vein infection.Applied microbiology and biotechnology · 2026Article
- 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
- Correlation between sub-phenotypes of coagulopathy and prognosis in sepsis patients in ICU using longitudinal group trajectory modeling: a retrospective analysis.European journal of medical research · 2026Article
- Data-driven spatial-temporal framework for exploring the heterogeneity and temporality of sepsis.Chinese medical journal · 2026Review
- Article
- Early enteral nutrition and dynamic metabolic-inflammatory trajectories in sepsis: a retrospective cohort study.Frontiers in medicine · 2026Article
- Neutrophil-to-lymphocyte and neutrophil-to-platelet ratios for predicting 28-day mortality in sepsis: A retrospective cohort study.PloS one · 2026Article
- Clinical subphenotypes and molecular endotypes in sepsis: toward an integrated and dynamic framework.Annals of intensive care · 2026Review
- Development and Validation of a 28-Day Mortality Prediction Model for Patients with Sepsis Complicated by Autoimmune Diseases Using Two Machine Learning Methods.Journal of inflammation research · 2026Article
30 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 1 country.
Funding
Abstract
purposeSepsis is a heterogeneous syndrome and identification of sub-phenotypes is essential. This study used trajectories of vital signs to develop and validate sub-phenotypes and investigated the interaction of sub-phenotypes with treatment using randomized controlled trial data.
methodsAll patients with suspected infection admitted to four academic hospitals in Emory Healthcare between 2014-2017 (training cohort) and 2018-2019 (validation cohort) were included. Group-based trajectory modeling was applied to vital signs from the first 8 h of hospitalization to develop and validate vitals trajectory sub-phenotypes. The associations between sub-phenotypes and outcomes were evaluated in patients with sepsis. The interaction between sub-phenotype and treatment with balanced crystalloids versus saline was tested in a secondary analysis of SMART (Isotonic Solutions and Major Adverse Renal Events Trial).
resultsThere were 12,473 patients with suspected infection in training and 8256 patients in validation cohorts, and 4 vitals trajectory sub-phenotypes were found. Group A (N = 3483, 28%) were hyperthermic, tachycardic, tachypneic, and hypotensive. Group B (N = 1578, 13%) were hyperthermic, tachycardic, tachypneic (not as pronounced as Group A) and hypertensive. Groups C (N = 4044, 32%) and D (N = 3368, 27%) had lower temperatures, heart rates, and respiratory rates, with Group C normotensive and Group D hypotensive. In the 6,919 patients with sepsis, Groups A and B were younger while Groups C and D were older. Group A had the lowest prevalence of congestive heart failure, hypertension, diabetes mellitus, and chronic kidney disease, while Group B had the highest prevalence. Groups A and D had the highest vasopressor use (p < 0.001 for all analyses above). In logistic regression, 30-day mortality was significantly higher in Groups A and D (p < 0.001 and p = 0.03, respectively). In the SMART trial, sub-phenotype significantly modified treatment effect (p = 0.03). Group D had significantly lower odds of mortality with balanced crystalloids compared to saline (odds ratio (OR) 0.39, 95% confidence interval (CI) 0.23-0.67, p < 0.001).
conclusionSepsis sub-phenotypes based on vital sign trajectory were consistent across cohorts, had distinct outcomes, and different responses to treatment with balanced crystalloids versus saline.
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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.