Do CAD genetic risk scores predict cardiovascular risk?

CAD genetic risk scores (GRSs) predict risk independently from clinical tools, like QRISK3. We assessed the added value of GRSs for a variety of cardiovascular traits (CV GRSs) for predicting CAD and MACE and tested their early-life screening potential by comparing against the CAD GRS only.

Does catboost improve risk prediction?

The CatBoost algorithm model improved risk prediction compared with the CAD consortium clinical model (AUROC 0.726, 95% CI 0.664–0.789; MCC 0.223). The accuracy of the ML model was 74.3%.

Which rpm predicts CAD in the general population?

We identified 11 articles containing 28 RPMs predicting CAD in the general population. External validation in the UK Biobank, LifeLines, and PREVEND cohorts yielded comparable moderate-to-good discrimination and calibration for most RPMs, indicating that no single best-performing RPM could be distinguished.

Can machine learning predict obstructive CAD?

Methods: Eight machine learning models for the prediction of obstructive CAD were trained on a cohort of 1,312 patients (randomly split into a training [80%] and internal validation sets [20%]). Twelve clinical and blood biomarker features assessed on admission were used to inform the models.