Echocardiographic phenotypes in sepsis: identifying subgroups using latent profile analysis.

backgroundSepsis 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.

methodsThis 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.

resultsThere 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

conclusionsUsing an unsupervised clustering analysis, we identified five phenotypes of cardiac function in sepsis based on commonly recorded echocardiographic data: diastolic dysfunction, left ventricular systolic dysfunction with low cardiac index, right ventricular dilation with elevated tricuspid regurgitation gradient, hyperdynamic cardiac function, and normal. The right ventricular dilation group had the highest mortality. Future research should explore mechanisms and potential treatment implications for these groups.