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Aims Small studies suggested circulating microRNAs (miRNAs) as biomarkers for heart failure (HF). However, standardized approaches and quality assessment for measuring circulating miRNAs are not uniformly established, and most studies have been small, so that results are inconsistent. We used a standardized data handling protocol, optimized for circulating miRNA qPCRs to remove noise and used it to assess which circulating miRNAs robustly add prognostic information in patients with HF. Methods and results We measured 12 miRNAs in two independent cohorts totalling 2203 subjects. Cohort I (Barcelona) comprised 834 chronic HF patients. Cohort II (Detroit) comprised 1369 chronic HF patients. Each sample was measured in duplicate, and normalized to a very abundant and stable miRNA (miR-486-5p). We used a multistep algorithm to distinguish false amplification signals and thus classify each miRNA measurement as ‘valid’, ‘undetectable’ or ‘invalid’. Higher levels of miR-1254 and miR-1306-5p were significantly associated with risk of the combined endpoint of all-cause mortality and HF hospitalization in both cohorts, with hazard ratios ranging from 1.11 to 1.21 per log increase (P-values 0.004 to 0.009). However, adding these miRNAs to established predictors (age, sex, haemoglobin, renal function, and NT-proBNP) did not further augment the c-statistic beyond 0.69 (cohort I) or 0.70 (cohort II). Conclusion We used a stringent quality assessment for miRNA testing, and were able to replicate the association of miR-1254 and miR-1306-5p with risk of death and HF hospitalization in HF patients of two independent cohorts. However, these two circulating miRNAs failed to improve prognostication over established predictors.

A total of 581 consecutive patients from 21 primary care practices in The Netherlands with type 2 diabetes, in whom the diagnosis of heart failure (HF) was not known, underwent an extensive diagnostic assessment, including medical history taking, physical examination, ECG, and echocardiography. The presence or absence of HF was established by a panel of two cardiologists and one general practitioner following the guidelines on HF of the European Society of Cardiology. In 161 patients, HF was considered present. A model based on the medical history and symptoms had a good discriminative value for detecting or excluding HF [C-statistic after bootstrapping 0.80; 95% confidence interval (CI) 0.76–0.83]. Adding signs improved the C-statistic to 0.82 (95% CI 0.79–0.86). A diagnostic screening score based on the clinical model had good discriminative properties applying a cut-off of 3 points (24.7% risk of HF) with sensitivity 70.8%, specificity 79.0%, negative predictive value 87.6%, and positive predictive value 56.4%. ECG and natriuretic peptides both had independent added value beyond the clinical model and increased the C-statistic to 0.86 (95% CI 0.83– 0.89). With a 20% threshold, the net reclassification of adding ECG and NT-proBNP to the clinical model was only 0.06.

Background: Stroke after cardiac surgery may be caused by emboli emerging from an atherosclerotic ascending aorta (AA). Epiaortic ultrasound scanning (EUS), the current ‘gold’ standard for detecting AA atherosclerosis, has not gained widespread use because there is a lack of optimized ultrasound devices, it lengthens the procedure, it endangers sterility, and there is a false belief by many surgeons that palpation is as sensitive as EUS. Furthermore there is no clear evidence proving that the use of epiaortic scanning changes outcome in cardiac surgery. Various researchers investigated the ability of transesophageal echocardiography (TEE) to discriminate between the presence and absence of AA atherosclerosis. It is acknowledged that TEE has limited value in this, but it has never been supported by a meta-analysis estimating the true diagnostic accuracy of TEE based on all quantitative evidence. We aimed to do this using state-of-the-art methodology of diagnostic meta-analyses. Methods: We searched multiple databases for studies comparing TEE vs. EUS for detection of atherosclerosis. A random-effects bivariate meta-regression model was used to obtain summary estimates of sensitivity and specificity, incorporating the correlation between sensitivity and specificity as well as covariates to explore heterogeneity across studies. Results: We extracted six studies with a total of 346 patients, of whom 419 aortic segments were analyzed, including 100 segments with atherosclerosis [median prevalence 25% (range 17–62%)]. Summary estimates of sensitivity and specificity were 21% (95% CI 13–32%) and 99% (96–99%), respectively. Conclusions: Because of the low sensitivity of TEE for the detection of AA atherosclerosis, a negative test result requires verification by additional testing using epiaortic scanning. In case of a positive test result, AA atherosclerosis can be considered as present, and less manipulative strategies might be indicated.