AI algorithm to detect diabetes from ECG

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AI algorithm to detect diabetes from ECG
AI algorithm to detect diabetes from ECG

Nevertheless, adoption of this AI algorithm into routine practice will need robust validation on external, independent datasets

An (artificial intelligence) AI algorithm derived from the features of individual heartbeats recorded on an ECG (electrocardiogram) has been developed by a team of Indian scientists. The AI algorithm can accurately predict diabetes and pre-diabetes.

The team from Lata Medical Research Foundation in Nagpur included clinical data from 1,262 individuals. A standard 12-lead ECG heart trace lasting 10 seconds was done for each of the participants. And 100 unique structural and functional features for each lead were combined for each of the 10,461 single heartbeats recorded to generate a predictive AI algorithm named DiaBeats.

With an overall accuracy of 97 per cent and a precision of 97 per cent, irrespective of influential factors, such as age, gender, and co-existing metabolic disorders, the DiaBeats algorithm quickly detected diabetes and pre-diabetes based on the shape and size of individual heartbeats.

Underpinning cardiac changes that are typical of diabetes and pre-diabetes, important ECG features consistently matched the known biological triggers.

The approach, if validated in larger studies, could be used to screen for the disease in low resource settings, the team said.

“In theory, our study provides a relatively inexpensive, non-invasive, and accurate alternative (to current diagnostic methods) which can be used as a gatekeeper to effectively detect diabetes and pre-diabetes early in its courses.”

“Nevertheless, adoption of this AI algorithm into routine practice will need robust validation on external, independent datasets,” they cautioned.

Around the world, an estimated 463 million adults had diabetes in 2019. Detecting the disease in its early stages is key to preventing subsequent serious health problems, but diagnosis relies heavily on the measurement of blood glucose.

This is not only invasive but also challenging to roll out as a mass screening test in low resource settings.

Structural and functional changes in the cardiovascular system occur early on even before indicative blood glucose changes, and these show up on an ECG heart trace.

The researchers also acknowledged that the study participants were all at high risk of diabetes and other metabolic disorders, so unlikely to represent the general population. And DiaBeats was slightly less accurate in those taking prescription meds for diabetes, high blood pressure, high cholesterol, etc.

Nor were data available for those who became pre-diabetic or diabetic, making it impossible to determine the impact of early screening.

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