ArticleeLife2020
Spectral clustering of risk score trajectories stratifies sepsis patients by clinical outcome and interventions received.
Article in eLife, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed.
- Impact of the updated SOFA-2 score on sepsis diagnosis and prognosis: a retrospective multicenter cohort study.Critical care (London, England) · 2026Observational
- Modulating Vimentin: A Systems-Level Therapeutic Strategy for Sepsis and Complex Diseases.Life (Basel, Switzerland) · 2026Article
- Temporal phenotyping and prognostic stratification of patients with sepsis through longitudinal clustering.BioData mining · 2025Article
- Serum small RNA profiling identifies prognostic biomarkers for sepsis mortality prediction.Frontiers in medicine · 2025Article
- A common data model for the standardization of intensive care unit medication features.JAMIA open · 2024Article
- Targeting the host response in sepsis: current approaches and future evidence.Critical care (London, England) · 2023Review
- Cluster analysis driven by unsupervised latent feature learning of medications to identify novel pharmacophenotypes of critically ill patients.Scientific reports · 2023Article
- Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model.Critical care (London, England) · 2023Observational
- Sepsis biomarkers and diagnostic tools with a focus on machine learning.EBioMedicine · 2022Review
- Methods for Phenotyping Adult Patients in Sepsis and Septic Shock: A Scoping Review.Critical care explorations · 2022Article
- Individualized resuscitation strategy for septic shock formalized by finite mixture modeling and dynamic treatment regimen.Critical care (London, England) · 2021Article
- Prediction of Impending Septic Shock in Children With Sepsis.Critical care explorations · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Sepsis is not a monolithic disease, but a loose collection of symptoms with diverse outcomes. Thus, stratification and subtyping of sepsis patients is of great importance. We examine the temporal evolution of patient state using our previously-published method for computing risk of transition from sepsis into septic shock. Risk trajectories diverge into four clusters following early prediction of septic shock, stratifying by outcome: the highest-risk and lowest-risk groups have a 76.5% and 10.4% prevalence of septic shock, and 43% and 18% mortality, respectively. These clusters differ also in treatments received and median time to shock onset. Analyses reveal the existence of a rapid (30-60 min) transition in risk at the time of threshold crossing. We hypothesize that this transition occurs as a result of the failure of compensatory biological systems to cope with infection, resulting in a bifurcation of low to high risk. Such a collapse, we believe, represents the true onset of septic shock. Thus, this rapid elevation in risk represents a potential new data-driven definition of septic shock.
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