Integrated Management of Post-Myocardial Infarction Patients Using Genetic Analysis and Remote Control
Abstract
Coronary heart disease (CHD) remains a leading cause of mortality and morbidity worldwide, particularly due to complications following myocardial infarction (MI). Despite advancements in therapeutic strategies, the prognosis for MI patients varies significantly, necessitating a comprehensive approach that integrates genetic and non-genetic factors. This study addresses the knowledge gap by evaluating the influence of genetic polymorphisms and non-genetic factors on the 12-month prognosis of MI patients. Using a cohort of 250 post-MI patients, we conducted genetic analysis on polymorphisms of the AGT, ADRB1, APOE, LPL, and CYP2C19 genes and assessed their correlation with clinical outcomes using modern statistical methods. Our findings indicate significant associations between specific gene polymorphisms and patient prognosis, highlighting the importance of personalized medicine. The results suggest that incorporating genetic analysis into the management of MI patients can improve survival rates and inform targeted therapeutic interventions, offering a novel approach to enhancing patient care in clinical settings.