Validation of machine learning-based risk stratification scores for patients with acute coronary syndrome treated with percutaneous coronary intervention.

ABSTRACT:

Aims

This study aimed to validate the machine learning-based Global Registry of Acute Coronary Events (GRACE) 3.0 score and PRAISE (Prediction of Adverse Events following an Acute Coronary Syndrome) in patients with acute coronary syndrome (ACS) treated with percutaneous coronary intervention (PCI) for predicting mortality.

Methods and results

Data of consecutive patients with ACS treated with PCI in a tertiary centre in the Netherlands between 2014 and 2021 were used for external validation. The GRACE 3.0 score for predicting in-hospital mortality was evaluated in 2759 patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) treated with PCI. The PRAISE score for predicting one-year mortality was evaluated in 4347 patients with ACS treated with PCI. Both risk score

SUBMITTER: Molenaar MA 

PROVIDER: S-EPMC11570391 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature