Delhi doctors develop a system to prevent post-heart attack fatalities

Over 1.4 million Indian suffer a heart attack every year, of whom 8-10% die within a month.

A team of Delhi-based doctors has now developed an indigenous system, based on machine learning, to predict a patient’s chances of dying within 30 days of suffering a heart attack or going on to survive.

The system collects data on heart attack patients from the North Indian ST-segment Elevation Myocardial Infarction (NORIN STEMI) registry.

And it takes less than two minutes to generate a score based on the data that can help doctors identify whether an individual is a high-risk patient who can succumb within 30 days or capable of surviving beyond the crucial period.

Also read: Can continuous glucose monitoring devices help you lose weight?

The model was evolved in a collaborative effort by the Department of Cardiology at the GB Pant Institute of Postgraduate Medical Education and Research (GIPMER), New Delhi; SBILab and Centre of Excellence in Healthcare, both attached to the Indraprastha Institute of Information Technology, New Delhi.

Professor Mohit Gupta, one of the two principal developers of the model, said India hasn’t had a tool so far to assess the survival rate of heart attack patients in the country.

“These tools that we employ here are used on the American population and a model specifically verified on the Indian population for predicting the survival chances of a patient after a heart attack is needed,” he said.

Gupta said the model is a tool specially designed for population of India, noting that reasons for the incidence of heart disease in the country are different from those in Western countries.

“While preparing this model, we used customised reasons for heart attack while we conducted a study on 4,000 heart attack patients,” he said.

Also read: Stryker augments R&D in India with new global technology centre in Gurugram

How does assessing the survival rate of a patient help?

Gupta said doctors in India, being a resource-limited country, can use the tool to identify and concentrate on improving the chances of survival of high-risk patients.

“If we get to know that a patient’s chance of survival is 10 percent as compared to that of another one who has a 20 percent chance, the resources can be diverted to the one who has a higher chance,” he explained.

The researchers now want to conduct a pan-India study.