A major Indian study has raised serious concerns over the effectiveness of widely used global heart risk calculators, revealing that nearly 80% of patients who suffered a first heart attack were not identified as high-risk beforehand.

The findings, based on a retrospective analysis of more than 5,000 patients, suggest that standard models—largely developed using Western populations – may be ill-suited to detect cardiovascular risk patterns in India, where heart disease often presents earlier and differently.

Western Risk Models Missing Indian Patterns

The study, led by Dr Mohit Dayal Gupta of GB Pant Hospital in Delhi, found that commonly used heart risk calculators significantly underestimate risk in Indian patients. These tools, which guide doctors on preventive treatments and monitoring, rely heavily on factors such as age and LDL cholesterol.

However, in the Indian context, these indicators may not adequately capture underlying risk. While only 11% to 20% of patients in the study were classified as high-risk by these models, all of them eventually experienced a heart attack.

“Indian patients behave differently. We have different risk factors and patterns, and Western scores may not always be appropriate,” Dr Gupta noted.

The mismatch arises because these models were built using data from populations where cardiovascular disease typically occurs later in life. In contrast, the study found that the average age of Indian patients suffering a heart attack was just 54, highlighting the growing burden of premature heart disease.

Unique ‘South Asian Phenotype’ Drives Risk

Researchers pointed to what is often described as a “South Asian phenotype”, characterised by a distinct cluster of risk factors that are not adequately captured by conventional scoring systems.

Many Indian patients develop cardiovascular risk at a younger age, often accompanied by diabetes or insulin resistance – even in individuals who do not appear overweight. Cholesterol patterns can also be misleading, with low levels of protective HDL cholesterol and high triglycerides, even when LDL cholesterol is not significantly elevated.

In addition, hidden abdominal fat – often present despite a normal body mass index – further increases risk. Other contributing factors include smoking, psychosocial stress, and a high prevalence of metabolic disorders.

Crucially, many of these elements, including lipoprotein(a), ApoB levels, central obesity, and chronic kidney disease, are not adequately factored into existing global risk calculators.

Delayed Intervention And Missed Prevention

The implications of these findings are significant. Risk calculators are central to clinical decision-making, determining who receives preventive medication such as statins and who is monitored more closely.

When patients are misclassified as low or intermediate risk, early intervention is often delayed, leaving individuals vulnerable to sudden cardiac events.

Experts warn that the “intermediate risk” category has become a grey zone for many Indian patients, where uncertainty leads to under-treatment despite underlying danger.

Call For India-Specific Risk Tools

The study has renewed calls for the development of India-specific cardiovascular risk assessment tools that better reflect local population characteristics.

Researchers argue that until such models are widely available, doctors should use global calculators cautiously and supplement them with clinical judgement, taking into account factors such as family history, early onset diabetes, lifestyle stress, and additional biomarkers.

The findings also underscore the need for earlier and more comprehensive screening, particularly in younger individuals who may not fit traditional high-risk profiles.

As cardiovascular disease continues to be a leading cause of mortality in India, the study highlights a critical gap in prevention strategies – one that could be addressed through more tailored, population-specific approaches to risk assessment.

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