Background: Cardiovascular diseases (CVD) and other non-communicable diseases (NCDs) such as diabetes, hypertension, and obstructive sleep apnea (OSA) are rising in prevalence, particularly in the Indian population. Early risk identification is crucial but often delayed due to reliance on symptomatic hospital-based assessments. Current risk prediction tools, though widely used, lack validation for the Indian population.

Objective: This cross-sectional study aims to assess the utility of a coronary artery disease consumer mobile application incorporating the BEATS score—a digital biomarker—to stratify CVD and NCD risk in asymptomatic individuals aged 30–60 years. The study further aims to validate the BEATS score against the MESA score and examine correlations with body fat composition and six lifestyle factors.

Methods: A total of 1,000 employees from 10 selected industries/ educational institutions within 20km radius from PSG hospitals will participate. After a 5-day app-based assessment, participants undergo clinical and laboratory evaluations including CT Coronary Calcium Score, body fat composition, blood pressure, glucose levels, lipid profile, and lifestyle assessment. The BEATS score will be compared with clinical outcomes and MESA scores to assess validity.

Expected Outcomes: The study anticipates that the BEATS score will show significant correlation with subclinical atherosclerosis and lifestyle factors, offering a non-invasive, cost-effective alternative for early CVD risk detection. Findings may support large-scale implementation of digital health tools in preventive care.

Significance: This study emphasizes the national importance of digital tools for personalized risk assessment, promoting a culture of preventive healthcare and addressing gaps in early CVD detection in the Indian population.