Development and validation of a risk prediction nomogram for in-stent restenosis in patients undergoing percutaneous coronary intervention.

ABSTRACT:

Background

This study aimed to develop and validate a nomogram to predict probability of in-stent restenosis (ISR) in patients undergoing percutaneous coronary intervention (PCI).

Methods

Patients undergoing PCI with drug-eluting stents between July 2009 and August 2011 were retrieved from a cohort study in a high-volume PCI center, and further randomly assigned to training and validation sets. The least absolute shrinkage and selection operator (LASSO) regression model was used to screen out significant features for construction of nomogram. Multivariable logistic regression analysis was applied to build a nomogram-based predicting model incorporating the variables selected in the LASSO regression model. The area under the curve (AUC) of the receiver operating characteristi

SUBMITTER: He W 

PROVIDER: S-EPMC8442286 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature