Predictive model development combining CT-FFR and SYNTAX score for major adverse cardiovascular events in complex coronary artery disease.

ABSTRACT: Patients with complex coronary artery disease (CAD) often have poor clinical outcomes. This study aimed to develop a predictive model for assessing the 1-year risk of major adverse cardiovascular events (MACE) in patients with stable complex CAD, using retrospective data collected from January 2020 to September 2023 at Guangzhou Red Cross Hospital. The goal was to enable early risk stratification and intervention to improve clinical outcomes. A total of 369 patients were included and randomly divided into a training set (70%) for model development and a validation set (30%) for performance evaluation. Predictive factors were selected using least absolute shrinkage and selection operator (LASSO) regression, followed by logistic regression to construct the model and create a nomogram. Seven

SUBMITTER: Luo W 

PROVIDER: S-EPMC11871039 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature