Open AccessA Nomogram for Predicting In-Stent Restenosis Risk in Patients Undergoing Percutaneous Coronary Intervention: A Population-Based Analysis
Author(s) -
Yinhua Luo,
Nguan Soon Tan,
Jingbo Zhao,
Yuanhong Li
Publication year - 2022
Publication title -
international journal of general medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.722
H-Index - 36
ISSN - 1178-7074
DOI - 10.2147/ijgm.s357250
Subject(s) - medicine , conventional pci , percutaneous coronary intervention , nomogram , confidence interval , restenosis , odds ratio , receiver operating characteristic , cardiology , univariate analysis , logistic regression , coronary artery disease , population , stent , multivariate analysis , myocardial infarction , environmental health
In-stent restenosis (ISR) is a fatal complication of percutaneous coronary intervention (PCI). An early predictive model with the medical history of patients, angiographic characteristics, inflammatory indicators and blood biochemical index is urgently needed to predict ISR events. We aim to establish a risk prediction model for ISR in CAD patients undergoing PCI.