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Value of S100A12 in predicting in-stent restenosis in patients with coronary drug-eluting stent implantation

In-stent restenosis (ISR) after drug-eluting stent (DES) placement has recently emerged as a major concern for cardiologists. Identification of biomarkers to predict ISR may be invaluable for tailored management strategies. The present study aimed to evaluate the prognostic utility of circulating S1...

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Detalles Bibliográficos
Autores principales: Liang, Hengyi, Cui, Yuqi, Bu, Haoran, Liu, Hang, Yan, Pengcheng, Cui, Lianqun, Chen, Liming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7282035/
https://www.ncbi.nlm.nih.gov/pubmed/32536993
http://dx.doi.org/10.3892/etm.2020.8721
Descripción
Sumario:In-stent restenosis (ISR) after drug-eluting stent (DES) placement has recently emerged as a major concern for cardiologists. Identification of biomarkers to predict ISR may be invaluable for tailored management strategies. The present study aimed to evaluate the prognostic utility of circulating S100 calcium-binding protein A12 (S100A12) for ISR. Out of 2,443 patients with DES-based percutaneous coronary intervention (PCI) and follow-up angiography at ~1 year after DES-based PCI, 258 patients were diagnosed with ISR and 258 patients without ISR were randomly selected as controls. Serum S100A12 levels were determined in the two subsets on admission. The association between ISR and the circulating levels of S100A12 was determined by constructing two multivariate stepwise logistic regression models. In addition, S100A12 was assessed for its ability to predict ISR using receiver operating characteristic (ROC) curve analysis. The serum levels of S100A12 at baseline were significantly elevated in patients in the ISR group compared with those in the non-ISR group (P<0.001). In the multivariate logistic regression analysis, after adjusting for conventional cardiovascular risk factors, laboratory parameters and medication after the procedure, the S100A12 level was revealed to be independently associated with ISR. When a cut-off for serum S100A12 levels of 34.75 ng/ml was used, the ROC curve was able to predict ISR with 72.8% sensitivity and 79.1% specificity, and the area under the ROC curve was 0.796 (95% CI: 0.757 to 0.834, P<0.001). Furthermore, addition of S100A12 to established risk factors significantly improved the predictive power of reference models for ISR. S100A12 may serve as an independent marker to predict ISR in patients undergoing coronary DES implantation.