Ashhar Alam/New Delhi

A large share of Indians who go on to suffer heart attacks may not be flagged as “high-risk” by commonly used cardiovascular risk calculators, raising concerns about their suitability for South Asian populations, according to new research.

The study, titled “Comparison of ASCVD Risk Prediction Models in STEMI: Insights from a South Asian Cohort,” analysed data from 4,975 patients who experienced their first heart attack. It was conducted by researchers from institutions including Govind Ballabh Pant Institute of Postgraduate Medical Education and Research, ESIC Medical College Faridabad, and the Delhi Cancer Registry at AIIMS.

Researchers evaluated five widely used global risk assessment tools the Framingham Risk Score, ACC/AHA ASCVD 2013 model, WHO risk charts, JBS-3 calculator, and the PREVENT score to determine how accurately they identify high-risk individuals in India.

The findings revealed wide inconsistencies. While some models classified around one-fifth of patients as high-risk, others identified significantly fewer. Notably, the ASCVD 2013 model flagged just over 12 per cent of patients as high-risk, leaving the majority categorised under low or moderate risk despite later experiencing heart attacks.

Cardiologist Dr Mohit Gupta, associated with the research, noted that many Indian patients are misclassified when assessed using Western-developed tools. He emphasised that physiological and demographic differences mean such models may fail to reflect the actual risk profile of Indian populations.

The study highlights that heart disease in Indians often presents earlier and is influenced by distinct factors, including a higher prevalence of diabetes, different fat distribution patterns, and unique metabolic characteristics. Environmental and lifestyle elements such as pollution, stress, and dietary habits further compound the risk.

Because of these differences, existing tools may underestimate cardiovascular risk, potentially delaying preventive interventions and treatment. Researchers also observed that most models tend to cluster a large number of individuals into a “moderate-risk” category, making clinical decision-making more challenging.

Among the tools assessed, the PREVENT score showed relatively better distribution across risk categories, but it too failed to identify a substantial number of patients who eventually suffered heart attacks.

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The analysis was based on pre-event health indicators such as blood pressure, cholesterol levels, diabetes status, and smoking history, comparing predicted risk with actual outcomes.

The study concludes that there is an urgent need to develop and validate risk prediction models tailored specifically to India and South Asia. Without such region-specific tools, experts warn, a significant number of high-risk individuals may continue to go undetected, increasing the likelihood of preventable cardiac events.