Predictive value of LncRNA on coronary restenosis after percutaneous coronary intervention in patients with coronary heart disease: A protocol for systematic review and meta-analysis - Liu, Shengxiang (Medicine (Baltimore), 2021)
BACKGROUND. Evidence shows that long-stranded non-coding RNA (LncRNA) can predict coronary artery restenosis in patients suffering from coronary heart disease after percutaneous coronary intervention, suggesting that LncRNA may become a promising biomarker for the diagnosis of coronary artery restenosis after percutaneous coronary intervention. However, its accuracy has not been systematically evaluated. Therefore, it is necessary to perform meta-analysis to certify the diagnostic value of LncRNA on coronary artery restenosis after percutaneous coronary intervention. METHODS. PubMed, EMBASE, Cochrane Library, and Web of Science were searched for relevant studies to explore the potential diagnostic values of LncRNA on coronary artery restenosis after percutaneous coronary intervention from inception to December 2020. Data were extracted by two experienced researchers independently. The risk of bias about the meta-analysis was confirmed by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Data was synthesized and heterogeneity was investigated as well. All of the above statistical analysis was carried out with Stata 14.0. RESULTS. This study proved the pooled diagnostic performance of LncRNA on coronary artery restenosis after percutaneous coronary intervention. CONCLUSION. This study clarified confusions about the specificity and sensitivity of LncRNA on coronary artery restenosis after percutaneous coronary intervention, thus further guiding their promotion and application. ETHICS AND DISSEMINATION. Ethical approval is not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms. This review would be disseminated in a peer-reviewed journal or conference presentations. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/4QT2P.