Can polygenic risk scores improve CAD risk prediction?

Recent advances in polygenic risk scores (PRSs) have sparked a great interest in enhancing disease risk prediction by using the information on millions of variants across the genome [ 11, 12, 13, 14 ]. However, population health utility of PRSs in CAD risk prediction is controversial.

Does genetic information improve predictive accuracy for CAD?

In our analysis, the addition of genetic information to the PCE clinical risk score was associated with a moderate improvement in predictive accuracy for CAD.

Is CAD a risk factor?

69% of adults in the United States are overweight or obese. 35% of adults are obese. Obesity is an independent risk factor for CAD and also increases the risk of developing other CAD risk factors, including hypertension, hyperlipidemia, and diabetes mellitus.

How accurate is CAD based on MPI-SPECT images?

Papandrianos et al. 17 developed deep learning models to diagnose CAD from MPI-SPECT images and achieved an accuracy of 91.86% with the proposed RGB-CNN model.