Echocardiographic phenotypes in sepsis: identifying subgroups using latent profile analysis

作者：Tatyana Shvilkina, Gabriel Erion-Barner, Timothy P. Downs, Ryan C. Burke, Nadim Kattouf, Jordan B. Strom, Robert E. Gerszten, Tamar Sofer, Daniel B. Kramer, Michael W. Donnino, Michael J. Lanspa, Nathan I. Shapiro · 发表于：Journal of Intensive Care · 年份：2026 · DOI：10.1186/s40560-026-00873-8 · 被引用次数：2 · 研究领域：Sepsis Diagnosis and Treatment、Cardiovascular Function and Risk Factors、Hemodynamic Monitoring and Therapy

Sepsis remains a leading cause of mortality, and optimizing treatment is challenging due to patient heterogeneity. Identification of cardiac phenotypes may inform precision medicine approaches and guide resuscitation. We performed a clustering analysis of patients with sepsis using echocardiographic data without using any a priori definitions of cardiac dysfunction or outcomes to establish the subgroups. This was a retrospective cohort study of patients admitted to the hospital with sepsis at a single academic center. Patients were identified using sepsis-related ICD codes, and those who had echocardiogram performed within 14 days of admission underwent chart review to ensure sepsis-3 criteria were met. Those with preexisting heart disease were excluded. Clustering by echocardiographic variables was performed using latent profile analysis. Clinical features such as patient characteristics, laboratory studies, sepsis source, and outcomes were compared across the clusters. There were 2,071 patients included in the analysis. Our cluster analysis yielded five phenotypes: cluster 1, elevated mean E/e′ 24.5 (SD 9.6); cluster 2, reduced ejection fraction, mean 33.1% (SD 10.6), and cardiac index 2.6 L/min/m 2 (SD 0.9); cluster 3, right ventricular dilation with right ventricular basal diameter 4.5 cm (SD 0.9) and elevated tricuspid regurgitation gradient 60.0 mmHg (SD 13.5); cluster 4, hyperdynamic with mean left ventricular ejection fraction 75% (SD10.9) and mean cardiac index 6.6 L...