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.
Lipids Health Dis
; 20(1): 118, 2021 Sep 29.
Article
en En
| MEDLINE
| ID: mdl-34587955
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 ANDMETHODS:
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.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Plaquetas
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Enfermedad de la Arteria Coronaria
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Stents Liberadores de Fármacos
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Lípidos
Tipo de estudio:
Diagnostic_studies
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Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Año:
2021
Tipo del documento:
Article