Role of Post-Stent Physiological Assessment in a Risk Prediction Model After Coronary Stent Implantation
Doyeon Hwang, Joo Myung Lee, Seokhun Yang, Mineok Chang, Jinlong Zhang, Ki Hong Choi, Chee Hae Kim, Chang-Wook Nam, Eun-Seok Shin, Jae-Jin Kwak, Joon-Hyung Doh, Masahiro Hoshino, Rikuta Hamaya, Yoshihisa Kanaji, Tadashi Murai, Jun-Jie Zhang, Fei Ye, Xiaobo Li, Zhen Ge, Shao-Liang Chen, Tsunekazu Kakuta, Bon-Kwon Koo, Doyeon Hwang, Joo Myung Lee, Seokhun Yang, Mineok Chang, Jinlong Zhang, Ki Hong Choi, Chee Hae Kim, Chang-Wook Nam, Eun-Seok Shin, Jae-Jin Kwak, Joon-Hyung Doh, Masahiro Hoshino, Rikuta Hamaya, Yoshihisa Kanaji, Tadashi Murai, Jun-Jie Zhang, Fei Ye, Xiaobo Li, Zhen Ge, Shao-Liang Chen, Tsunekazu Kakuta, Bon-Kwon Koo
Abstract
Objectives: The aim of this study was to develop a risk model incorporating clinical, angiographic, and physiological parameters to predict future clinical events after drug-eluting stent implantation.
Background: Prognostic factors after coronary stenting have not been comprehensively investigated.
Methods: A risk model to predict target vessel failure (TVF) at 2 years was developed from 2,200 patients who underwent second-generation drug-eluting stent implantation and post-stent fractional flow reserve (FFR) measurement. TVF was defined as a composite of cardiac death, target vessel myocardial infarction, and clinically driven target vessel revascularization. A random survival forest model with automatic feature selection by minimal depth analysis was used for risk model development.
Results: During 2 years of follow-up, the cumulative incidence of TVF was 5.9%. From clinical, angiographic, and physiological parameters, 6 variables were selected for the risk model in order of importance within the model as follows: total stent length, post-stent FFR, age, post-stent percentage diameter stenosis, reference vessel diameter, and diabetes mellitus. Harrell's C index of the random survival forest model was 0.72 (95% confidence interval [CI]: 0.62 to 0.82). This risk model showed better prediction ability than models with clinical risk factors alone (Harrell's C index = 0.55; 95% CI: 0.41 to 0.59; p for comparison = 0.005) and with clinical risk factors and angiographic parameters (Harrell's C index = 0.65; 95% CI: 0.52 to 0.77; p for comparison = 0.045). When the patients were divided into 2 groups according to the median of total stent length (30 mm), post-stent FFR and total stent length showed the highest variable importance in the short- and long-stent groups, respectively.
Conclusions: A risk model incorporating clinical, angiographic, and physiological predictors can help predict the risk for TVF at 2 years after coronary stenting. Total stent length and post-stent FFR were the most important predictors. (International Post PCI FFR Registry; NCT04012281).
Keywords: drug-eluting stent; fractional flow reserve; outcome; risk model.
Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Source: PubMed