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AI-backed method uses only waist size and age to detect pre-diabetes

AI-focussed technique presented by researchers in Italy finds that just two variables, waist size and age, can detect early stages of type 2 diabetes

Latest study from researchers in Italy find a no-cost, AI-based method in order to detect dysglycemia , often seen as an indicator of type 2 diabetes. The study, published in the Diabetes Research and Clinical Practice on February 26, was pioneered by Enrico Buccheri, MD, of the University of Catania and colleagues.

NHANES cross-sectional data for 2007-2016 was used and the authors collected data for 47 variables. Using an AI-based technique, they deduced that age and waist circumference variables are the sole variables required to detect dysglycemia. 

Additionally, the researchers find few disparities between their method and the gold standard for dysglycemia screening. They comment:

Despite its outstanding simplicity, the accuracy of our model turns out to be equivalent to that of more complex tools previously published in the literature and widely used to perform cross-sectional studies,

The authors conclude in the paper:

The use of uniquely two variables allows to obtain a zero-cost screening tool of analogous precision than that of more complex tools widely adopted in the literature. The newly developed tool has clinical use as it significantly simplifies the screening of dysglycemia. Furthermore, we suggest that the definition of an age-related waist circumference cut-off might help to improve existing diabetes risk factors.

The benefit of this new method is that it incurs no costs, which could become integral for screening large populations for dysglycemia.

Source: AI in Healthcare

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