SURVIVAL ANALYSIS OF CORONARY ARTERY DISEASE: A CASE STUDY OF DISTRICT PESHAWAR
Abstract
Statistics plays a crucial role in modern research, particularly in the field of medicine, where various statistical techniques are applied to analyze data. One such technique is survival analysis, which has wide applications in biostatistics. In Pakistan, coronary artery disease (CAD) has been a major health issue, characterized by the narrowing of arteries supplying blood to the heart, leading to symptoms such as chest pain, shortness of breath, and even death. The study conducted at the Post Graduate Medical Institute, Lady Reading Hospital (LRH), Peshawar, analyzed data from 215 CAD patients to identify significant factors contributing to the disease and its severity. The results showed that most patients were male, with a small proportion of females. About 17% of patients experienced an event during the one-year study period, and 32% had diabetes while 9.3% had high cholesterol levels. The majority of patients had severe disease, with three blocked vessels, and 82 had total occlusion. Cox regression analysis revealed that hypercholesterolemia, Left Main Stem Disease (LMSD), total occlusion, and the combined effect of diabetes and smoking were significant factors contributing to the disease. Gender-specific findings indicated that male survival was associated with cholesterol levels, number of blocked vessels, LMSD, and the interaction between hypertension and smoking, with males showing high odds of events in cases of hypercholesterolemia, hypertension, and smoking. For females, diabetes, hypertension, and age were the primary risk factors. Age is a non-modifiable risk factor for females, while for males, hypercholesterolemia, hypertension, and smoking were modifiable and controllable risk factors. The study concludes that cholesterol levels, diabetes, and smoking are key risk factors for CAD, with gender-specific differences in the risk factors.
Keywords: Coronary Artery Disease (CAD), Survival Analysis, Risk Factors, Cox Regression. Hypercholesterolemia.