Diagnostic and predictive value of micro RNA-133a and micro RNA-499a-5p in patients with sepsis induced cardiomyopathy

Objective To investigate the value of micro RNA (miR)-133a and miR-499a-5p in diagnosing sepsis-induced cardiomyopathy (SIC) and predicting mortality in patients with SIC. Methods Blood samples collected from 70 sepsis patients with sepsis were included and divided into SIC group(n=54) and control group(n=16, sepsis without cardiomyopathy) according to diagnostic criteria to calculate the incidence of SIC. Blood samples were examined for serum levels of miR-133a and miR-499a-5p using Real-Time polymerase chain reaction (PCR) and baseline data were recorded. The comparison was made between SIC group and control group. The patients were followed up for 28 d to record their survival. Pearson correlation analysis was used to test the correlations of miR-133a and miR-499a-5p with troponin I (cTnI), creatine kinase-MB (CK-MB), N-terminal B-type natriuretic peptide(NT-proBNP) and left ventricular ejection fraction (LVEF) in patients with SIC. The diagnostic value of miR-133a and miR-499a-5p for SIC was analyzed using receiver operating characteristic(ROC) curve. Multivariate Logistic regression analysis was used to analyze the correlations of miR-133a, miR-499a-5p and other risk factors with the 28 d mortality in patients with sepsis. The predictive value of these indicators for evaluating the prognosis of SIC was analyzed using ROC curve. Results The expression levels of miR-133a and miR-499a-5p in patients with SIC were both significantly higher than the expression levels in patients without SIC(P<0.05). Pearson correlation analysis showed that miR-133a and miR-499a-5p were positively correlated with cTnI levels (miR-133a, r=0.329, P=0.005; miR-499a-5p, r= 0.574, P=0.000). The area under the ROC curve of miR-133a, miR-499a-5p and miR-133a combined with miR-499a-5p was 0.676, 0.737 and 0.758. During the follow-up period for 28 d, 19 of the 54 (35.2%) SIC patients died. Logistic regression analysis indicated that miR-133a was independent risk factor for the 28 d mortality of SIC patients. The ROC curve analysis showed that the area under the curve of miR-133a was 0.826 (95%CI 0.703~0.948). Conclusions MiR-133a and miR-499a-5p can be novel biomarkers for the diagnosis of SIC. miR-133a has good predictive value in assessing the 28 d mortality of patients with SIC. Key words: Sepsis; Sepsis-induced cardiomyopathy; Micro RNA-133a; Micro RNA-499a-5p; Biomarker