Key result
A five-variable clinical model predicts ISR with an AUC of 0.72.
Why the study?
The study aimed to establish a prediction model for in-stent restenosis in patients who had undergone PCI with drug-eluting stents.
Does a prediction model based on platelet parameters, lipid levels, and angiographic characteristics predict in-stent restenosis in CAD patients with DES implantation?
Cohort (n=968)
No
Does a prediction model based on platelet parameters, lipid levels, and angiographic characteristics predict in-stent restenosis in CAD patients with DES implantation?
Answers are grounded in this paper and cite their sources.
A prediction model incorporating platelet distribution width, systolic blood pressure, total cholesterol, LDL-C, and number of lesion vessels effectively predicts in-stent restenosis after drug-eluting stent implantation.
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.
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Gai et al. (2021) conducted a cohort in Coronary artery disease with drug-eluting stents (n=968). Prediction model (PDW, TC, LDL-C, SBP, lesion vessels) was evaluated on Prediction of in-stent restenosis (ISR) (AUC 0.72, 95% CI 0.64-0.80, p=<0.001). A prediction model based on platelet distribution width, systolic blood pressure, total cholesterol, LDL-C, and lesion vessels effectively predicted in-stent restenosis with an AUC of 0.72.
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