ReviewCurrent heart failure reports2014
Biomarkers for risk prediction in acute decompensated heart failure.
Review in Current heart failure reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 20 citations in OpenAlex.
- Circulating miR-30d Predicts Survival in Patients with Acute Heart Failure.Cellular physiology and biochemistry : international journal of experimental cellular physiology, biochemistry, and pharmacology · 2017Trial
- Development and validation of an integrated prognostic model for all-cause mortality in heart failure: a comprehensive analysis combining clinical, electrocardiographic, and echocardiographic parameters.BMC cardiovascular disorders · 2025Article
- Prevalence and prognostic impact of subclinical pulmonary congestion at discharge in patients with acute heart failure.ESC heart failure · 2020Article
- GDF15 and Growth Control.Frontiers in physiology · 2018Review
- From Inflammation to Fibrosis-Molecular and Cellular Mechanisms of Myocardial Tissue Remodelling and Perspectives on Differential Treatment Opportunities.Current heart failure reports · 2017Review
- Predictive and Prognostic Biomarkers of Respiratory Diseases due to Particulate Matter Exposure.Journal of cancer prevention · 2017Review
- Soluble ST2 for Prediction of Heart Failure and Cardiovascular Death in an Elderly, Community-Dwelling Population.Journal of the American Heart Association · 2016Observational
- Temporal cardiac remodeling post-myocardial infarction: dynamics and prognostic implications in personalized medicine.Heart failure reviews · 2016Article
- Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Risk prediction in patients admitted with acute decompensated heart failure (ADHF) remains a challenge. Biomarkers may improve risk prediction, which in turn may help to better inform patients regarding short-term and long-term prognosis, therapy and care. Most data on biomarkers have been derived from patient cohorts with chronic heart failure. In ADHF, currently, risk tools largely rely on common clinical and biochemical parameters. However, ADHF is not a single disease. It presents in various manners and different etiologies may underlie ADHF, which are reflected by different biomarkers. In the last decade, many studies have reported the prognostic value of these biomarkers. These studies have attempted to describe a value for statistical modeling, e.g., reclassification indices, in an effort to report incremental value over a clinical model or the "gold standard". However, the overall incremental predictive value of biomarkers has been modest compared to already existing clinical models. Natriuretic peptides, e.g., (NTpro-)BNP, are the benchmark, but head-to-head comparisons show that there are novel biomarkers with comparable prognostic value. Multimarker strategies may provide superior risk stratification. Future studies should elucidate cost-effectiveness of single or combined biomarker testing. The purpose of this review was to provide an update on current biomarkers and to identify new promising biomarkers than can be used in prognostication of acute heart failure.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.