Open Access
01-12-2017 | Research
Diagnostic value of microRNA-143 in predicting in-stent restenosis for patients with lower extremity arterial occlusive disease
Authors:
Zhi-Hai Yu, Hai-Tao Wang, Can Tu
Published in:
European Journal of Medical Research
|
Issue 1/2017
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Abstract
Purpose
This study was conducted to explore the diagnostic value of microRNA-143 (miRNA-143) in predicting in-stent restenosis (ISR) of lower extremity arterial occlusive disease (LEAOD).
Methods
From February 2012 to March 2015, 165 patients (112 males and 53 females) with LEAOD undergoing interventional treatment were enrolled in this study. Serum miRNA-143 expression was detected using quantitative real-time polymerase chain reaction (qRT-PCR). Patients were assigned into the restenosis and non-restenosis groups according to routine surveillance postoperative angiography. A logistic regression analysis was conducted to analyze the risk factors for ISR in LEAOD patients. A receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic value of miRNA-143 in predicting ISR for LEAOD patients.
Results
There were 74 and 91 patients in the restenosis and non-restenosis groups, respectively. Before the treatment, there were significant differences in history of diabetes, smoking status, blood sugar level (BSL) at admission, low-density lipoprotein cholesterol (LDL-C) level, and stent diameter between the restenosis and non-restenosis groups (all P < 0.05). Serum miRNA-143 expression was lower in the restenosis group than in the non-restenosis group (P < 0.05). Serum miRNA-143 expression in the restenosis group was correlated with smoking status, history of diabetes, BSL, and LDL-C (all P < 0.05). Logistic regression analysis demonstrated that miRNA-143, LDL-C, and smoking status were correlated with the postoperative ISR (all P < 0.05). ROC curve analysis revealed that the area under the curve (AUC) of miRNA-143 in predicting ISR for LEAOD patients was 0.866.
Conclusion
Our results indicate that miRNA-143 can be a promising tool for predicting the ISR in LEAOD patients.