Inflammatory Biomarkers' Function in Cardiovascular Event Prediction

Abstract

The study's methodology involved enrolling 1,090 patients who had coronary angiography. Twenty-four indicators of inflammation were gathered before angiography. Distinct patterns of inflammatory biomarkers were identified by cluster analyses using unsupervised machine learning. The link between inflammatory biomarker clusters and individual biomarker associations with major adverse cardiovascular events (MACE; non-fatal myocardial infarction or stroke, and CV mortality) over a median follow-up of 3.67 years was evaluated using Cox proportional hazard regression.