Heart Disease Risk Calculators Inadequate for Indian Population, Study Finds

A new study reveals that current heart disease risk calculators may be inadequate for the Indian population, potentially leading to underestimation of risk and delayed treatment, highlighting the urgent need for India-specific risk assessment tools.

Widely used heart disease risk calculators may be failing to identify a large proportion of Indians at risk, with nearly 80 per cent of patients who eventually suffered a heart attack not being classified as 'high-risk' beforehand, according to new research.

The research titled "Comparison of ASCVD Risk Prediction Models in STEMI: Insights from a South Asian Cohort" was conducted by a team of scientists from Govind Ballabh Pant Institute of Postgraduate Medical Education and Research, ESIC Medical College, Faridabad, the Delhi Cancer Registry at AIIMS, among others.

The study, conducted on 4,975 patients with first-time heart attacks, found significant differences in how five major global risk prediction models categorised individuals, raising concerns over their reliability for South Asian populations.

Researchers compared widely used tools such as the Framingham Risk Score (FRS), ACC/AHA ASCVD 2013 model, WHO risk charts, JBS-3 calculator and the newer Predicting Risk of Cardiovascular Disease Events (PREVENT) score.

They found that while some models classified about 20 per cent of patients as 'high-risk', others identified far fewer, with the ASCVD 2013 model flagging only about 12.3 per cent, meaning a large majority were placed in 'low' or 'moderate-risk' categories.

"When we put Indian heart attack patients through these Western models, many of them are wrongly classified. Physiologically, they should be considered 'high-risk' patients, especially since they went on to have a heart attack, but these models place them in low- and medium-risk categories, raising serious concerns about prevention," Dr Mohit Gupta, Professor of Cardiology at GB Pant Hospital and a researcher involved in the study, told PTI.

Inadequacy of Western Models for Indian Patients

The study noted that heart disease develops differently in Indians compared to Western populations, with earlier onset and a different mix of risk factors such as higher diabetes burden, distinct fat distribution and metabolic patterns.

As a result, when Indian patients are assessed using these tools, their actual risk is often underestimated, which can delay treatment and preventive care.

"Indian patients behave differently from others. Many factors like genetics, pollution, lifestyle and stress levels have an impact. Even being Indian or South Asian in itself is a risk factor. We urgently need an indigenous risk calculator tailored to our population," Dr Gupta added.

Notably, even the best-performing models failed to flag the majority of patients who later developed acute myocardial infarction or heart attack, highlighting gaps in current risk prediction systems.

The study also found that most models tend to group a large number of patients into a broad 'moderate-risk' category, making it difficult for doctors to clearly decide who needs aggressive treatment.

In contrast, the Predicting Risk of Cardiovascular Disease Events (PREVENT) score was able to spread patients more clearly across low, moderate and 'high-risk' categories, instead of clustering most people in the middle. However, even this model missed a large number of patients who eventually suffered a heart attack, the study said.

Researchers analysed medical records of nearly 5,000 patients aged 40-79 years who were admitted with their first heart attack, using pre-event health data such as blood pressure, cholesterol levels, diabetes status and smoking history to estimate risk through five different models and compare it with actual outcomes.

The study concluded that there is an urgent need to develop and validate India- or South Asia-specific risk prediction tools, as relying on existing global models could lead to underestimation of risk and preventable deaths.