Evidence map›Paper›PMID 22450126›Full record

ReviewNature reviews. Cardiology2012

Novel biomarkers in chronic heart failure.

Tariq Ahmad, Mona Fiuzat, G Michael Felker, Christopher O'Connor

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Cardiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 2 pooled it
10.9field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

55 citing papers in PubMed, 2 syntheses or guidelines pooled it, 125 citations in OpenAlex.

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  7. An integrated overview of acute heart failure: a narrative review of pathophysiological mechanisms and contributing factors.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Tariq AhmadDivision of Cardiology, Duke University School of Medicine, 2400 Pratt Street, Durham, NC 27705, USA. ariq.ahmad@duke.edu
Mona Fiuzat
G Michael Felker
Christopher O'Connor
Duke University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding of chronic heart failure (HF) has progressed from a syndrome of disordered hemodynamics caused by alterations in the structure of the heart to one that involves intertwined molecular pathways in disarray. Accordingly, the assessment and treatment of patients with chronic HF has shifted from a focus on hemodynamics to modification of maladaptive molecular processes. Accumulating evidence shows that molecular biomarkers of disease could provide a unique window into the pathophysiology of chronic HF, potentially improving our ability to predict adverse outcomes, provide novel drug targets, and even help gauge therapeutic efficacy. The more 'traditional' biomarkers such as cardiac troponin, natriuretic peptides, and C-reactive protein have been studied in large cohorts of patients with chronic HF and have relatively established clinical applications. In this Review, we summarize the properties, clinical data, and potential applications of some emerging biomarkers that could uniquely indicate the level of biomechanical stretch, inflammation, ventricular remodeling, myocardial injury, and renal dysfunction that occurs in chronic HF. We will also discuss the potential role for these biomarkers within a multimarker-based strategy that could, in the future, lead to better care for these patients.

Indexed as

AnimalsBiomarkersChronic DiseaseHeart FailureHumansPredictive Value of TestsPrognosisBiomarkers

Identifiers

PMID22450126
OpenAlexW1976828141

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.