New Delhi: They had no red flags. No “high risk” tag. According to standard medical calculators, he was not the kind of patient doctors worry about. Then the heart attack happened – suddenly and without warning. Doctors say this is no longer unusual. A major Indian study suggests this may be the norm.In a retrospective analysis of more than 5,000 Indian patients, widely used global cardiovascular risk calculators failed to identify the majority of people at risk, with nearly 80% of those who had previously had a heart attack not previously flagged as high risk. Researchers led by Dr Mohit Dayal Gupta at Delhi’s GB Pant Hospital say Western models ignore India-specific risk patterns, often placing patients in the low or moderate category despite the underlying risk.These models are used by doctors to decide who needs treatment, but the study found that they often misclassify risk and sometimes produce conflicting results. In all models, only 11%–20% of patients were labeled high risk, even though all ultimately had a heart attack.“Indian patients and populations behave completely differently. We have different risk factors, different patterns and so Western scores may not always be appropriate,” Dr Gupta said.

‘80% of people who have their first heart attack were not labeled high risk’

At the heart of the problem is a mismatched relationship. Most of these risk calculators were designed using Western populations, where heart disease occurs later. In India, it strikes earlier and behaves differently – the study found that the average age of patients was just 54, underscoring how premature heart disease has become.Researchers say Indians show a distinct “South Asian phenotype”. Heart risk appears earlier, often with diabetes and insulin resistance, even at normal body weight. Cholesterol patterns are confusing – low HDL and high triglycerides, while LDL may not be very high. Despite appearing thin, many people have hidden abdominal fat, a risk that is missed by BMI-based assessments. Smoking and psychosocial stress, along with traditional risk factors such as diabetes, smoking, and dyslipidemia, further increase this hidden burden.This is why Western risk scores underperform. They depend heavily on age and LDL cholesterol, which leads to underestimation in young Indians. As a result, many patients fall into the “intermediate risk” category – a gray zone that often delays preventive treatment. Importantly, these models ignore key factors such as insulin resistance, lipoprotein (a), apoB, central obesity and chronic kidney disease.The impact is significant. These scores determine who gets preventive medications and close monitoring. When the risk is underestimated, intervention often occurs only after a major incident.The findings have raised renewed demand for customized risk scores, as the Indian population is poorly represented in global datasets. Experts say that until such tools are developed, risk calculators should be used along with clinical judgment, including family history, diabetes, psychosocial stressors, and early screening.