Circulating microRNAs (miRNAs) are potential biomarkers for cardiovascular diseases. Our study aimed to determine whether miR-22-5p, miR-132-5p, and miR-150-3p represent novel biomarkers for acute myocardial infarction (AMI). Plasma samples were isolated from 35 AMI patients and 55 matched controls. Total RNA was extracted, and quantitative real-time PCR and ELISA were performed to investigate the expressions of miRNAs and cardiac troponin I (cTnI), respectively. We found that plasma levels of miR-22-5p and miR-150-3p were significantly higher during the early stage of AMI and their expression levels peaked earlier than cTnI. Conversely, circulating miR-132-5p was sustained at a low level during the early phase of AMI. All three circulating miRNAs were correlated with plasma cTnI levels. A receiver operating characteristic (ROC) analysis suggested that each single miRNA had considerable diagnostic efficacy for AMI. Moreover, combining the three miRNAs improved their diagnostic efficacy. Furthermore, neither heparin nor medications for coronary heart disease (CHD) affected plasma levels of miR-22-5p and miR-132-5p, but circulating miR-150-3p was downregulated by medications for CHD. We concluded that plasma miR-22-5p, miR-132-5p, and miR-150-3p may serve as candidate diagnostic biomarkers for early diagnosis of AMI. Moreover, a panel consisting of these three miRNAs may achieve a higher diagnostic value.
Objective To systematically evaluate the prognostic impact of atrial fibrillation (AF) in patients with hypertrophic cardiomyopathy (HCM). Methods The Chinese and English databases (PubMed, EMBASE, Cochrane Library, Chinese National Knowledge Infrastructure, and Wanfang database were systematically searched to include observational studies on the prognosis of AF in cardiovascular events or death in patients with HCM; these were evaluated using Revman 5.3. Results After systematic search and screening, a total of 11 studies with a high study quality were included in this study. Meta-analysis showed that patients with HCM accompanied by AF had a higher risk of all-cause death (odds ratio [OR] = 2.75; 95% confidence interval [CI]: 2.18–3.47; P < 0.001), heart-related death (OR = 2.62; 95%CI: 2.02–3.40; P < 0.001), sudden cardiac death (OR = 7.09; 95%CI: 5.77–8.70; P < 0.001), heart-failure-related death (OR = 2.04; 95%CI: 1.24–3.36; P = 0.005), and stroke death (OR = 17.05; 95%CI: 6.99–41.58; P < 0.001) compared with patients with HCM without AF. Conclusion Atrial fibrillation is a risk factor for adverse survival outcomes in patients with HCM, and aggressive interventions are needed in this population to avoid the occurrence of adverse outcomes.
This study was aimed to explore the value of the twin neural network model in the classification and recognition of cardiac ultrasound images of patients with atrial fibrillation. 80 patients with cardiac atrial fibrillation were selected and randomly divided into experimental group (40 cases) and control group (40 cases). The twin neural network (TNN) model was combined with traditional ultrasound, Doppler spectrum, tissue velocity, and strain imaging technology to obtain the patient’s cardiac structure parameters and analyze and compare related indicators. The results showed that the total atrial emptying fraction (TA-EF value) of the experimental group was 53.08%, which was significantly lower than that of the control group ( P < 0.05 ). There were no significant differences in left atrial diameter (LAD), left ventricular end-diastolic diameter (LVEDD), left atrial maximum volume (LAVmax), and left ventricular ejection fraction (LVEF) between the two groups. In the experimental group, the average peak velocity of mitral valve annulus (Em) was 8.49 cm/s, the peak velocity of lateral wall systole (Vs) was 6.82 cm/s, and the propagation velocity of left ventricular blood flow (Vp) was 51.2 cm/s, which were significantly reduced ( P < 0.05 ). The average values of peak strains in the middle and upper left atrium of the experimental group were significantly lower than those of the control group ( P < 0.05 ). It can be concluded that the combined use of the TNN model can more accurately and quickly classify and recognize ultrasound images.
Objective. To explore the predictive value of ABC bleeding score and SAMe-TT2R2 score on the risk of bleeding in patients with nonvalvular atrial fibrillation (NVAF) complicated with coronary heart disease (CHD) after anticoagulation. Methods. 149 patients with NVAF complicated with CHD were followed up in our hospital for one year. The bleeding events during the follow-up period were observed, the ABC bleeding score and SAMe-TT2R2 score were calculated, the predictive value of the two scoring methods for the main bleeding risk was analyzed by the ROC curve, and the AUC area under the ROC curve of the two scoring methods was compared by the Delong test. Results. There were 32 bleeding events during the follow-up period. The AUC of ABC bleeding score and SAMe-TT2R2 score were 0.775 ( P < 0.01 ) and 0.624 ( P < 0.05 ), respectively. The Delong test showed that the AUC of ABC bleeding score was significantly higher than that of SAMe-TT2R2 score (d = 2.177, P < 0.05 ). Conclusion. Both the ABC bleeding score and SAMe-TT2R2 score can predict the risk of bleeding after anticoagulation in patients with NVAF and CHD. The critical value of the SAMe-TT2R2 score for predicting bleeding events in patients with NVAF and CHD may need to be increased to 4 or 5, and the prediction ability of ABC bleeding score is significantly better than that of the SAMe-TT2R2 score.
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