Comparison of Conventional And Non-Conventional Cardiovascular Risk Factors And Their Association With Acute Coronary Syndrome

Abstract

Background: Acute Coronary Syndrome (ACS) encompasses a spectrum of clinical presentations with varying pathophysiology. Understanding the prevalence of both conventional and non-conventional cardiovascular risk factors in ACS patients, and their relationship to ACS subtypes, is essential for targeted preventive strategies.

Methods: A cross-sectional study involving 222 patients diagnosed with ACS. Conventional risk factors assessed included hypertension, diabetes mellitus, dyslipidemia, smoking status, obesity, overweight, and family history of ACS. Non-conventional factors included chronic kidney disease (CKD), rheumatoid arthritis, inflammatory bowel disease, serum cortisol levels (as a marker of psychosocial stress), anxiety (measured by HAM-A score), and physical activity levels. Statistical analyses (Chi-square and ANOVA) determined associations between risk factors and ACS subtypes.

Results: The prevalence of conventional risk factors was high: hypertension (60–70%), diabetes mellitus (45–66%), dyslipidemia (47–58%), and family history of ACS (25–40%). Smoking status distribution comprised non-smokers (40–55%), ex-smokers (20–30%), and current smokers (25–45%). Notably, 45.0% of patients were overweight or obese. Among non-conventional risk factors, CKD was present in 18.5%, rheumatoid arthritis in 5.9%, and inflammatory bowel disease in 2.3%. Mean serum cortisol was 15.4 mcg/dL and the mean HAM-A anxiety score was 22.5. Physical inactivity was prevalent, with 56.3% sedentary, 33.3% moderately active, and 10.4% highly active patients. Significant associations were observed between hypertension, CKD, or psychosocial stress levels and ACS subtypes. Mean age was comparable across ACS groups regardless of the clinical subtype. The results suggest that broad-based interventions targeting all major risk factors are warranted, and that focusing solely on predicting ACS subtype based on risk factor profiles may have limited utility.