Identifying Markers of Cardiac Arrythmias in Patients with Diabetes Mellitus Type 2

Diabetes mellitus type 2 presents a significant public health challenge globally, predisposing affected individuals to a heightened risk of cardiovascular complications including arrhythmias. This paper investigates the intricate relationship between diabetes mellitus type 2 and arrhythmias, exploring underlying mechanisms and clinical correlations, including glycemic control, cardiovascular parameters, and lifestyle factors. Additionally, the study integrates multimodal data from wearable medical devices, offering a more comprehensive assessment. The design of the clinical study allowed us to analyze the concurrent variations in home health monitoring data (cardiological and glycemic indices) along with clinical and questionnaire data, aiming at identifying prognostic factors of cardiac arrhythmias in type 2 diabetes. Ensemble and boosting machine learning algorithms were utilized to identify key factors contributing to arrhythmia risk. Feature importance analysis identified elevated low-density lipoprotein LDL levels as a potential risk factor, consistent with existing literature.Clinical Relevance- The study highlights the critical role of lipid management in mitigating cardiovascular risks for patients with type 2 diabetes mellitus. The identification of elevated LDL levels as a significant predictor of arrhythmic events underscores the importance of incorporating lipid monitoring into routine care, advocating for aggressive lipid-lowering strategies.