Circulating microRNA-1 in the diagnosis and predicting prognosis of patients with chest pain: A prospective cohort study

12Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Background: To investigate the early diagnostic and prognostic value of microRNA-1 in patients with acute chest pain. Methods: This study enrolled 341 patients attacked by chest pain within 3 h, and another 100 volunteers as control group. Circulating microRNA-1 was collected and determined by real-time quantitative reverse transcription-polymerase chain reaction. The clinical follow-up period was 720 days. Results: There were 174 patients in acute myocardial infarction (AMI) group, 167 in non-AMI group. The relative expression of microRNA-1 was significantly increased within 3 h in AMI group, and it continued rising within 12 h, lower at 24 h than that 12 h in AMI group without reperfusion therapy. Otherwise, microRNA-1 concentration was markedly low at 12 h after primary percutaneous coronary intervention in AMI group. The 95% reference range of circulating microRNA-1 was 0.171-0.653. It was significantly available for microRNA-1 to early diagnose AMI with an optimal cutoff value of 2.215 and diagnostic accuracy could be improved when combined with cardiac troponin I. It was not statistically significant for microRNA-1 to forecast future AMI but might prognose mortality of 720 days in chest pain patients. In patients with chest pain, microRNA-1 concentration was high with major adverse cardiac events within 30 days, low with high overall survival within 720 days. Conclusions: Circulating microRNA-1 might diagnose early AMI and predict the prognosis of patients with chest pain.

Cite

CITATION STYLE

APA

Su, T., Shao, X., Zhang, X., Han, Z., Yang, C., & Li, X. (2019). Circulating microRNA-1 in the diagnosis and predicting prognosis of patients with chest pain: A prospective cohort study. BMC Cardiovascular Disorders, 19(1). https://doi.org/10.1186/s12872-018-0987-x

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free