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Aims: Heart failure (HF), a global pandemic affecting millions of individuals, calls for adequate predictive guidance for improved therapy. Congestion, a key factor in HF‐related hospitalizations, further underscores the need for timely interventions. Proactive monitoring of intracardiac pressures, guided by pulmonary artery (PA) pressure, offers opportunities for efficient early‐stage intervention, since haemodynamic congestion precedes clinical symptoms. Methods: The BioMEMS study, a substudy of the MONITOR‐HF trial, proposes a multifaceted approach integrating blood biobank data with traditional and novel HF parameters. Two additional blood samples from 340 active participants in the MONITOR‐HF trial were collected at baseline, 3‐, 6‐, and 12‐month visits and stored for the BioMEMS biobank. The main aims are to identify the relationship between temporal biomarker patterns and PA pressures derived from the CardioMEMS‐HF system, and to identify the biomarker profile(s) associated with the risk of HF events and cardiovascular death. Conclusion: Since the prognostic value of single baseline measurements of biomarkers like N‐terminal pro‐B‐type natriuretic peptide is limited, with the BioMEMS study we advocate a dynamic, serial approach to better capture HF progression. We will substantiate this by relating repeated biomarker measurements to PA pressures. This design rationale presents a comprehensive review on cardiac biomarkers in HF, and aims to contribute valuable insights into personalized HF therapy and patient risk assessment, advancing our ability to address the evolving nature of HF effectively. [ABSTRACT FROM AUTHOR]

Introduction: Heart failure is a serious burden on health care systems due to frequent hospital admissions. Early recognition of outpatients at risk for clinical deterioration could prevent hospitalization. Still, the role of signs and symptoms in monitoring heart failure patients is not clear. The heart failure coach is a web-based telemonitoring application consisting of a 9-item questionnaire assessment of heart failure signs and symptoms and developed to identify outpatients at risk for clinical deterioration. If deterioration was suspected, patients were contacted by a heart failure nurse for further evaluation. Methods: Heart failure coach questionnaires completed between 2015 and 2018 were collected from 287 patients, completing 18,176 questionnaires. Adverse events were defined as all-cause mortality, heart failure- or cardiac-related hospital admission or emergency cardiac care visits within 30 days after completion of each questionnaire. Multilevel logistic regression analyses were performed to assess the association between the heart failure coach questionnaire items and the odds of an adverse event. Results: No association between dyspnea and adverse events was observed (odds ratio 1.02, 95% confidence interval 0.79–1.30). Peripheral edema (odds ratio 2.21, 95% confidence interval 1.58–3.11), persistent chest pain (odds 2.06, 95% confidence interval 1.19–3.58), anxiety about heart failure (odds ratio 2.12, 95% confidence interval 1.44–3.13), and extensive struggle to perform daily activities (odds ratio 2.23, 95% confidence interval 1.38–3.62) were significantly associated with adverse outcome. Discussion: Regular assessment of more than the classical signs and symptoms may be helpful to identify heart failure patients at risk for clinical deterioration and should be an integrated part of heart failure telemonitoring programs. [ABSTRACT FROM AUTHOR]