Machine Learning-Based Prediction of 28-Day Mortality in Patients with Sepsis-Induced Cardiomyopathy: An Integrated Analysis of Inflammatory Biomarkers

Background

Sepsis-induced cardiomyopathy (SICM) is a common complication of sepsis and is associated with poor short-term outcomes. However, effective tools for early risk stratification remain limited. This study aimed to develop a machine learning (ML)-based model to predict 28-day mortality in patients with SICM.