Construction of A Prediction Model for Atrial Fibrillation in Patients with Dilated Cardiomyopathy and Heart Failure

Abstract

Dilated cardiomyopathy (DCM) is a common myocardial disease characterized by enlargement of the heart cavity and decreased systolic function, often leading to heart failure (HF) and arrhythmia. The occurrence of atrial fibrillation (AF) is closely related to the progression and prognosis of the disease. In recent years, with the advancement of medical imaging and biomarkers, models for predicting the occurrence of AF in DCM patients have gradually become a research hotspot. This article aims to review the current situation of AF in DCM patients and explore the importance and possible methods of constructing predictive models to provide reference for clinical prevention and treatment. We comprehensively analyzed the risk factors for AF in DCM patients from epidemiological data, pathophysiological mechanisms, clinical and laboratory indicators, electrocardiogram and imaging parameters, and biomarkers, and evaluated the effectiveness of existing predictive models. Through analysis of existing literature and research, this article proposes a predictive model that integrates multiple parameters to improve the accuracy of predicting AF in DCM patients and provide a scientific basis for personalized treatment.