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

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 χ2 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.

A Nomogram for Predicting In-Stent Restenosis Risk in Patients Undergoing Percutaneous Coronary Intervention: A Population-Based Analysis

“…Another systemic factor noted in our study to be closely related to ISR after PCI is preoperative neutrophil/ lymphocyte ratio, the index associated with inflammatory response and neointimal proliferation, 4,5,17,18 which was consistent with the previous research that neutrophil/lymphocyte is a strong inflammatory marker [19][20][21][22] and closely associated with Cardiovascular disease. In contrast to previous reports, we also discovered that RC had a higher predictive value for ISR than LDL-C.…”

“…3 Life-threatening consequences can arise should the ISR continue to deteriorate without prompt recognition and treatment. Therefore, early identification of risk factors for ISR is crucial in preventing major Previous studies 5,6 summarized the predictors of ISR as follows: medication history (eg, clopidogrel), prior PCI, stent characteristics, and some indicators concerning inflammatory responses and lipid metabolism (eg, TC, LDL-C, CRP, monocyte). 11 Similar to the previous studies, 11 we also found that monocytes can be one of the independent risk factors for ISR.…”

“…The preoperative factors comprised the following: the morphological characteristics of the diseased vessel, the location of the lesion, the degree of stenosis, and part of blood biochemical indicators which are associated with inflammatory responses and lipid metabolism. [3][4][5][6][7][8] Among these, the levels of monocyte and LDL-C are considered to be critical factors related to inflammatory response and to lipid metabolism, [9][10][11] respectively.…”

Prognostic Role of Fasting Remnant Cholesterol with In-Stent Restenosis After Drug-Eluting Stent Implantation

“…An increasing number of studies have shown that dyslipidemia and ISR are indissolubly linked. 6 To the best of our knowledge, the majority of the previous related literature 7 , 8 has concentrated on investigating the impact of low-density lipoprotein cholesterol (LDL-C) levels on ISR. However, a growing number of studies have demonstrated that patients are still at considerable risk of developing cardiovascular disease even after lowering LDL-C to recommended concentrations and controlling other risk factors (eg, hypertension and diabetes).…”

“…Unfortunately, there have not been much data to bear out the relationship between RC and ISR. What is more, most of the published studies 8 , 10 , 11 , 15 are retrospective with small sample sizes and use multi-factor logistic regression statistics. It is well known that retrospective studies have many confounding factors and that multifactor logistic regression may suffer from overfitting and covariance, so we attempted to address this by reducing the dimensionality 16 (using LASSO regression).…”