Literature DB >> 30789749

Identifying Novel Sepsis Subphenotypes Using Temperature Trajectories.

Sivasubramanium V Bhavani1, Kyle A Carey1, Emily R Gilbert2, Majid Afshar2, Philip A Verhoef1,3, Matthew M Churpek1.   

Abstract

Rationale: Sepsis is a heterogeneous syndrome, and identifying clinically relevant subphenotypes is essential.
Objectives: To identify novel subphenotypes in hospitalized patients with infection using longitudinal temperature trajectories.
Methods: In the model development cohort, inpatient admissions meeting criteria for infection in the emergency department and receiving antibiotics within 24 hours of presentation were included. Temperature measurements within the first 72 hours were compared between survivors and nonsurvivors. Group-based trajectory modeling was performed to identify temperature trajectory groups, and patient characteristics and outcomes were compared between the groups. The model was then externally validated at a second hospital using the same inclusion criteria.Measurements and Main
Results: A total of 12,413 admissions were included in the development cohort, and 19,053 were included in the validation cohort. In the development cohort, four temperature trajectory groups were identified: "hyperthermic, slow resolvers" (n = 1,855; 14.9% of the cohort); "hyperthermic, fast resolvers" (n = 2,877; 23.2%); "normothermic" (n = 4,067; 32.8%); and "hypothermic" (n = 3,614; 29.1%). The hypothermic subjects were the oldest and had the most comorbidities, the lowest levels of inflammatory markers, and the highest in-hospital mortality rate (9.5%). The hyperthermic, slow resolvers were the youngest and had the fewest comorbidities, the highest levels of inflammatory markers, and a mortality rate of 5.1%. The hyperthermic, fast resolvers had the lowest mortality rate (2.9%). Similar trajectory groups, patient characteristics, and outcomes were found in the validation cohort.Conclusions: We identified and validated four novel subphenotypes of patients with infection, with significant variability in inflammatory markers and outcomes.

Entities:  

Keywords:  group-based trajectory modeling; infection; sepsis; temperature

Mesh:

Year:  2019        PMID: 30789749      PMCID: PMC6680307          DOI: 10.1164/rccm.201806-1197OC

Source DB:  PubMed          Journal:  Am J Respir Crit Care Med        ISSN: 1073-449X            Impact factor:   21.405


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