ArticleChest2024
Using Trajectories of Bedside Vital Signs to Identify COVID-19 Subphenotypes.
Article in Chest, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Article
- Artificial Intelligence- and Machine Learning-Assisted Subphenotyping for Personalized Immunotherapy in Sepsis.Journal of personalized medicine · 2026Review
- Clinical subphenotypes and molecular endotypes in sepsis: toward an integrated and dynamic framework.Annals of intensive care · 2026Review
- From vital sign trajectories to data-driven targets: defining exploratory blood gas ranges in sepsis-associated thrombocytopenia.Frontiers in medicine · 2026Article
- Multicenter target trial emulation to evaluate corticosteroids for sepsis stratified by predicted organ dysfunction trajectory.Nature communications · 2025Article
- Response.Chest · 2024Article
- The Precision Resuscitation With Crystalloids in Sepsis (PRECISE) Trial: A Trial Protocol.JAMA network open · 2024Article
- Clinical Phenotyping for Prognosis and Immunotherapy Guidance in Bacterial Sepsis and COVID-19.Critical care explorations · 2024Article
- Application progress of latent class growth models in dynamic prevention and control strategies for acquired immunodeficiency syndrome.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024Review
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Authors and funding
5 authors.
Funding
Abstract
backgroundTrajectories of bedside vital signs have been used to identify sepsis subphenotypes with distinct outcomes and treatment responses. The objective of this study was to validate the vitals trajectory model in a multicenter cohort of patients hospitalized with COVID-19 and to evaluate the clinical characteristics and outcomes of the resulting subphenotypes. RESEARCH QUESTION: Can the trajectory of routine bedside vital signs identify COVID-19 subphenotypes with distinct clinical characteristics and outcomes? STUDY DESIGN AND
methodsThe study included adult patients admitted with COVID-19 to four academic hospitals in the Emory Healthcare system between March 1, 2020, and May 31, 2022. Using a validated group-based trajectory model, we classified patients into previously defined vital sign trajectories using oral temperature, heart rate, respiratory rate, and systolic and diastolic BP measured in the first 8 h of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. Heterogeneity of treatment effect to tocilizumab was evaluated.
resultsThe 7,065 patients with hospitalized COVID-19 were classified into four subphenotypes: group A (n = 1,429, 20%)-high temperature, heart rate, respiratory rate, and hypotensive; group B (1,454, 21%)-high temperature, heart rate, respiratory rate, and hypertensive; group C (2,996, 42%)-low temperature, heart rate, respiratory rate, and normotensive; and group D (1,186, 17%)-low temperature, heart rate, respiratory rate, and hypotensive. Groups A and D had higher ORs of mechanical ventilation, vasopressors, and 30-day inpatient mortality (P < .001). On comparing patients receiving tocilizumab (n = 55) with those who met criteria for tocilizumab but were admitted before its use (n = 461), there was significant heterogeneity of treatment effect across subphenotypes in the association of tocilizumab with 30-day mortality (P = .001).
interpretationBy using bedside vital signs available in even low-resource settings, we found novel subphenotypes associated with distinct manifestations of COVID-19, which could lead to preemptive and targeted treatments.
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