Angiotensin Receptor-Neprilysin Inhibition

The role of biomarkers in the prognosis and risk stratification in heart failure: A systematic review

Acute heart failure (AHF) episodes are marked by high rates of morbidity and mortality during the episode and minimal advancements in its care. Multiple biomarker monitoring is now a crucial supplementary technique in the therapy of AHF. A scientific literature search was conducted by assessing and evaluating the most pertinent research that has been published, including original papers and review papers with the use of PubMed, Medline, and Cochrane databases. Established biomarkers like natriuretic peptides (BNP, NT-proBNP) and cardiac troponins play crucial roles in diagnostic and prognostic evaluation. Emerging biomarkers such as microRNAs, osteopontin, galectin-3, ST2, and GDF-15 show promise in enhancing risk stratification and predicting adverse outcomes in HF. However, while these biomarkers offer valuable insights, their clinical utility requires further validation and integration into practice. Continued research into novel biomarkers holds promise for early HF detection and risk assessment, potentially mitigating the global burden of HF. Understanding the nuances of biomarker utilization is crucial for their effective incorporation into clinical practice, ultimately improving HF management and patient care.

Assessment of acute heart failure prognosis: the promising role of prognostic models and biomarkers

Numerous models and biomarkers have been proposed to estimate prognosis and improve decision-making in patients with acute heart failure (AHF). The present literature review provides a critical appraisal of externally validated prognostic models in AHF, combining clinical data and biomarkers. We perform a literature review of clinical studies, using the following terms: "acute heart failure," "acute decompensated heart failure," "prognostic models," "risk scores," "mortality," "death," "hospitalization," "admission," and "biomarkers." We searched MEDLINE and EMBASE databases from 1990 to 2020 for studies documenting prognostic models in AHF. External validation of each prognostic model to another AHF cohort, containing at least one biomarker, was prerequisites for study selection. Among 358 initially screened studies, 9 of them fulfilled all searching criteria. The majority of prognostic models were simplified, including a narrow number of variables (up to 10), with good performance regarding calibration and discrimination (c-statistics > 0.65). Unfortunately, the derived and validated cohorts showed a wide variety in patients' characteristics (e.g., cause of AHF and therapy). Moreover, the prognostic models used various time-points and a plethora of combinations of variables determining different cut-off values. Although the application of valid prognostic models in AHF population is quite promising, a precise methodological approach should be set for the derivation and validation of prognostic models in AHF with unified characteristics to establish an effective performance in clinical practice.