Evidence map›Paper›PMID 31768917›Full record

ReviewCurrent heart failure reports2019

Synthesizing Markers of Kidney Injury in Acute Decompensated Heart Failure: Should We Even Keep Looking?

Alexander S Manguba, Xavier Vela Parada, Steven G Coca, Anuradha Lala

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current heart failure reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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 2 institutions in 1 country.

Alexander S MangubaDepartment of Medicine, Icahn School of Medicine at Mount Sinai/St. Luke's-Roosevelt Hospital Center, New York, NY, USA.
Xavier Vela ParadaDepartment of Medicine, Icahn School of Medicine at Mount Sinai/St. Luke's-Roosevelt Hospital Center, New York, NY, USA.
Steven G CocaDivision of Nephrology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Anuradha LalaThe Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. anu.lala@mountsinai.org.
Icahn School of Medicine at Mount Sinai · USSt. Luke's-Roosevelt Hospital Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewThis review discusses evidence that has accumulated over the years on the diagnostic and prognostic utility of biomarkers of kidney injury in the setting of acute decompensated heart failure. RECENT

findingsDespite numerous studies evaluating several different biomarkers both in the serum and urine, the current body of evidence does not support routine use of any of these biomarkers for the purposes of diagnosis of acute kidney injury or for prognosis after hospitalization for acute decompensated heart failure. All studies are observational in nature and, as such, are likely limited by numerous confounders, the most important of which is modification of decongestive therapy in response to worsening renal function. More recent evidence suggests that worsening renal function or kidney injury does not always portend poor outcomes after hospitalization for heart failure. There is currently no conclusive evidence to recommend the routine use of biomarkers of kidney injury in acute decompensated heart failure.

Indexed as

Acute DiseaseAcute Kidney InjuryBiomarkersHeart FailureHospitalizationHumansPrognosisBiomarkersAcute decompensated heart failureAcute kidney injuryBiomarkersCardiorenal syndromeWorsening renal function

Identifiers

PMID31768917
OpenAlexW2989920702

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.