Heart failure (HF) is a complex clinical syndrome with a huge social burden in terms of cost, morbidity, and mortality. Brain natriuretic peptide (BNP) appears to be the gold standard in supporting the daily clinical management of patients with HF. Novel biomarkers may supplement BNP to improve the understanding of this complex disease process and, possibly, to personalize care for the different phenotypes, in order to ameliorate prognosis. In this review, we will examine some of the most promising novel biomarkers in HF. Inflammation plays a pivotal role in the genesis and progression of HF and, therefore, several candidate molecules have been investigated in recent years for diagnosis, prognosis, and therapy monitoring. Noncoding RNAs are attractive as biomarkers and their potential clinical applications may be feasible in the era of personalized medicine. Given the complex pathophysiology of HF, it is reasonable to expect that the future of biomarkers lies in the application of precision medicine, through wider testing panels and “omics” technologies, to further improve HF care delivery.

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Background Coronavirus disease 2019 (COVID-19) is a pandemic disease that is causing a public health emergency. Characteristics and clinical significance of myocardial injury remain unclear. Methods This retrospective single-center study analyzed analyzed 189 patients who received a COVID-19 diagnosis out of all 758 subjects with a high sensitive troponin I (Hs-TnI) measurement within the first 24 h of admission at the Policlinico A.Gemelli (Rome, Italy) between February 20th 2020 to April 09th 2020. Results The prevalence of myocardial injury in our COVID-19 population is of 16%. The patients with cardiac injury were older, had a greater number of cardiovascular comorbidities and higher values of acute phase and inflammatory markers and leucocytes. They required more frequently hospitalization in Intensive Care Unit (10 [32.3%] vs 18 [11.4%]; p = .003) and the mortality rate was significantly higher (17 [54.8%] vs. 15 [9.5%], p < .001). Among patients in ICU, the subjects with myocardial injury showed an increase need of endotracheal intubation (8 out of 9 [88%] vs 7 out of 19[37%], p = .042). Multivariate analyses showed that hs-TnI can significantly predict the degree of COVID-19 disease, the intubation need and in-hospital mortality. Conclusions In this study we demonstrate that hs-Tn can significantly predict disease severity, intubation need and in-hospital death. Therefore, it may be reasonable to use Hs-Tn as a clinical tool in COVID-19 population in order to triage them into different risk groups and can play a pivotal role in the detection of subjects at high risk of cardiac impairment during both the early and recovery stage.

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Objective Early detection of pulmonary arterial hypertension (PAH) is crucial to improve patient outcomes. The aim of this study was to compare the positive predictive value (PPV) between the echocardiography-derived tricuspid annular plane systolic excursion/systolic pulmonary artery pressure (TAPSE/sPAP) ratio and the DETECT algorithm for PAH screening in a cohort of systemic sclerosis (SSc) patients. Methods 51 SSc patients were screened for PAH using DETECT algorithm and echocardiography. Results Echocardiography was recommended by the DETECT algorithm step 1 in 34 patients (66.7%). Right heart catheterization (RHC) was recommended by the DETECT algorithm step 2 in 16 patients (31.4%). PAH was confirmed by RHC in 5 patients. DETECT algorithm positive predictive value (PPV) was 31.3%.TAPSE/sPAP ratio was higher in SSc patients not referred for RHC than in SSc patients referred for RHC according to DETECT algorithm step 2 [0.83 (0.35-1.40) mm/mmHg vs 0.74 (0.12-1.09) mm/mmHg, p &lt; 0.05]. Using a cut-off of 0.60 mm/mmHg, 8 (15.7%) SSc patients had a TAPSE/sPAP ratio ≤0.60 mm/mmHg. PAH was confirmed by RHC in 5 patients. PPV of TAPSE/sPAP was 62.5%. In multiple regression analysis, TAPSE/sPAP was associated with age (β coefficient = -0.348 [95% CI, -0.011 to -0.003]; p &lt; 0.01), DETECT algorithm step 1 (β coefficient = 1.023 [95% CI, 0.006-0.024]; p &lt; 0.01) and DETECT algorithm step 2 (β coefficient = -1.758 [95% CI, -0.059 to -0.021]; p &lt; 0.0001). Conclusion In SSc patients with a DETECT algorithm step 2 total score &gt;35 the TAPSE/sPAP ratio can be used to further select patients requiring RHC to confirm PAH diagnosis.

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