1. A prediction model based on platelet parameters, lipid levels, and angiographic characteristics to predict in-stent restenosis in coronary artery disease patients implanted with drug-eluting stents.
- Author
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Gai, Min-Tao, Zhu, Bing, Chen, Xiao-Cui, Liu, Fen, Xie, Xiang, Gao, Xiao-Ming, Ma, Xiang, Fu, Zhen-Yan, Ma, Yi-Tong, and Chen, Bang-dang
- Subjects
CORONARY artery disease ,LDL cholesterol ,CORONARY restenosis ,PREDICTION models ,PERCUTANEOUS coronary intervention ,BLOOD platelets ,SYSTOLIC blood pressure - Abstract
Background: The present study was aimed to establish a prediction model for in-stent restenosis (ISR) in subjects who had undergone percutaneous coronary intervention (PCI) with drug-eluting stents (DESs). Materials and methods: A retrospective cohort study was conducted. From September 2010 to September 2013, we included 968 subjects who had received coronary follow-up angiography after primary PCI. The logistic regression analysis, receiver operator characteristic (ROC) analysis, nomogram analysis, Hosmer–Lemeshow χ
2 statistic, and calibration curve were applied to build and evaluate the prediction model. Results: Fifty-six patients (5.79%) occurred ISR. The platelet distribution width (PDW), total cholesterol (TC), systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and lesion vessels had significant differences between ISR and non-ISR groups (all P < 0.05). And these variables were independently associated with ISR (all P < 0.05). Furthermore, they were identified as predictors (all AUC > 0.5 and P < 0.05) to establish a prediction model. The prediction model showed a good value of area under curve (AUC) (95%CI): 0.72 (0.64–0.80), and its optimized cut-off was 6.39 with 71% sensitivity and 65% specificity to predict ISR. Conclusion: The incidence of ISR is 5.79% in CAD patients with DES implantation in the Xinjiang population, China. The prediction model based on PDW, SBP, TC, LDL-C, and lesion vessels was an effective model to predict ISR in CAD patients with DESs implantation. [ABSTRACT FROM AUTHOR]- Published
- 2021
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