Aims Bioactive adrenomedullin (bio-ADM) is a vascular-derived peptide hormone that has emerged as a promising biomarker for assessment of congestion in decompensated heart failure (HF). We aimed to evaluate diagnostic and prognostic performance of bio-ADM for HF in comparison to amino-terminal pro-B-type natriuretic peptide (NT-proBNP), with decision thresholds derived from invasive haemodynamic and population-based studies. Methods and resultsNormal reference ranges for bio-ADM were derived from a community-based cohort (n = 5060). Correlations with haemodynamic data were explored in a cohort of HF patients undergoing right heart catheterization (n = 346). Mortality and decision cutoffs for bio-ADM was explored in a cohort of patients presenting in the ER with acute dyspnoea (n = 1534), including patients with decompensated HF (n = 570). The normal reference range was 8-39 pg/mL. The area under the receiver operating characteristic curve (AUROC) for discrimination of elevated mean right atrial pressure (mRAP) and pulmonary arterial wedge pressure (PAWP) was 0.74 (95% CI = 0.67-0.79) and 0.70 (95% CI = 0.64-0.75), respectively, with optimal bio-ADM decision cutoff of 39 pg/mL, concordant with cubic spline analyses. NT-proBNP discriminated PAWP slightly better than mRAP (AUROC 0.73 [95% CI = 0.68-0.79] and 0.68 [95% CI = 0.61-0.75]). Bio-ADM correlated with (mRAP, r = 0.55) while NT-proBNP correlated with PAWP. Finally, a bio-ADM decision cutoff of 39 pg/mL associated with 30 and 90 day mortality and conferred a two-fold increased odds of HF diagnosis, independently from NT-proBNP. Conclusions Bio-ADM tracks with mRAP and associates with measures of systemic congestion and with mortality in decompensated HF independently from NT-proBNP. Our findings support utility of bio-ADM as a biomarker of systemic venous congestion in HF and nominate a decision threshold.

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Background: The contribution of endothelial injury in the pathogenesis of COVID-19-associated acute respiratory distress syndrome (ARDS) and resulting respiratory failure remains unclear. Plasma endostatin, an endogenous inhibitor of angiogenesis and endothelial dysfunction is upregulated during hypoxia, inflammation and progress of pulmonary disease. Aim: To investigate if plasma endostatin is associated to hypoxia, inflammation and 30-day mortality in patients with severe COVID-19 infection. Method: Samples for blood analysis and plasma endostatin quantification were collected from adult patients with ongoing COVID-19 (n = 109) on admission to intensive care unit (day 1). Demographic characteristics and 30-day mortality data were extracted from medical records. The ability of endostatin to predict mortality was analyzed using receiving operating characteristics and Kaplan–Meier analysis with a cutoff at 46.2 ng/ml was used to analyze the association to survival. Results: Plasma endostatin levels correlated with; PaO2/FiO2 (r = -0.3, p < 0.001), arterial oxygen tension (r = -0.2, p = 0.01), lactate (r = 0.2, p = 0.04), C-reactive protein (r = 0.2, p = 0.04), ferritin (r = 0.2, p = 0.09), D-dimer (r = 0.2, p = 0.08) and IL-6 (r = 0.4, p < 0.001). Nonsurvivors at 30 days had higher plasma endostatin levels than survivors (72 ± 26 vs 56 ± 16 ng/ml, p = 0.01). Receiving operating characteristic curve (area under the curve 0.7) showed that plasma endostatin >46.2 ng/ml predicts mortality with a sensitivity of 92% and specificity of 71%. In patients with plasma endostatin >46.2 ng/ml probability of survival was lower (p = 0.02) in comparison to those with endostatin <46.2 ng/ml. Conclusion: Our results suggest that plasma endostatin is an early biomarker for disease severity in COVID-19.

The patients’ burden of comorbidities is a cornerstone in risk assessment, clinical management and follow-up. The aim of this study was to evaluate if biomarkers associated with comorbidity burden can predict outcome in acute dyspnea patients. We included 774 patients with dyspnea admitted to an emergency department and measured 80 cardiovascular protein biomarkers in serum collected at admission. The number of comorbidities for each patient were added, and a multimorbidity score was created. Eleven of the 80 biomarkers were independently associated with the multimorbidity score and their standardized and weighted values were summed into a biomarker score of multimorbidities. The biomarker score and the multimorbidity score, expressed per standard deviation increment, respectively, were related to all-cause mortality using Cox Proportional Hazards Model. During long-term follow-up (2.4 ± 1.5 years) 45% of the patients died and during short-term follow-up (90 days) 12% died. Through long-term follow-up, in fully adjusted models, the HR (95% CI) for mortality concerning the biomarker score was 1.59 (95% CI 1348–1871) and 1.18 (95% CI 1035–1346) for the multimorbidity score. For short-term follow-up, in the fully adjusted model, the biomarker score was strongly related to 90-day mortality (HR 1.98, 95% CI 1428–2743), whereas the multimorbidity score was not significant. Our main findings suggest that the biomarker score is superior to the multimorbidity score in predicting long and short-term mortality. Measurement of the biomarker score may serve as a biological fingerprint of the multimorbidity score at the emergency department and, therefore, be helpful for risk prediction, treatment decisions and need of follow-up both in hospital and after discharge from the emergency department.