Journal of Case Reports and Reviews in Medicine (ISSN: 3069-0749)
Case Report Volume: 1 & Issue: 3
Abstract
The South Asian phenotype is associated with a unique cluster of cardiometabolic risk factors, including visceral obesity, insulin resistance, and a heightened propensity for type-2 diabetes mellitus (DM) and cardiovascular disease. This case report presents a comprehensive 30- year longitudinal clinical profile of an 87-year-old South Asian male with a history of hypertension, left ventricular hypertrophy (LVH), and type-2 DM. Despite early-onset cardiac dysfunction and progressive vascular changes, the patient maintained good glycemic control and stable cardiovascular status through pharmacologic management, a heart-healthy diet, and regular exercise. Advanced diagnostic tools including wearable cardiac rhythm monitors, stress echocardiography, and technetium-99 myocardial perfusion imaging (MPI) were employed to assess myocardial function and ischemic risk. Although transient ST-segment depressions were observed during ambulatory and stress ECG monitoring, nuclear imaging revealed no inducible ischemia but did show a fixed perfusion defect indicative of a myocardial scar. Importantly, artificial intelligence (AI) tools played a key role in integrating and interpreting complex multimodal data enhancing the diagnostic process through automated ECG analysis, risk stratification, and pattern recognition in nuclear imaging. This case underscores the growing utility of AI in improving accuracy, efficiency, and early detection in elderly patients with complex cardiometabolic conditions. It also highlights the importance of continuous, multimodal monitoring and personalized care strategies in managing chronic disease in high-risk populations.