Evidence map›Paper›PMID 25152498›Full record

ArticleJournal of cardiac failure2014

A combined-biomarker approach to clinical phenotyping renal dysfunction in heart failure.

Jeffrey M Testani, Kevin Damman, Meredith A Brisco, Susan Chen, Olga Laur, Alexander J Kula, W H Wilson Tang, Chirag Parikh

Open access · greenAbstract read
In one paragraph

Article in Journal of cardiac failure, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

17 citing papers in PubMed, 47 citations in OpenAlex.

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  15. The kidney in heart failure: an update.European heart journal · 2015 · on this map
    Review
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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

8 authors at 4 institutions in 2 countries.

Jeffrey M TestaniDepartment of Internal Medicine and Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut. Electronic address: jeffrey.testani@yale.edu.
Kevin DammanUniversity Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Meredith A BriscoDepartment of Internal Medicine, Medical University of South Carolina, Charleston, South Carolina.
Susan ChenDepartment of Internal Medicine and Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut.
Olga LaurDepartment of Internal Medicine and Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut.
Alexander J KulaDepartment of Internal Medicine and Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut.
W H Wilson TangSection of Heart Failure and Cardiac Transplantation, Cleveland Clinic, Cleveland, Ohio.
Chirag ParikhDepartment of Internal Medicine and Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut.
Yale University · USCleveland Clinic · USMedical University of South Carolina · USUniversity of Groningen · NL

Funding

Mentoring Program for Translational and Patient Oriented Research in AKIK24DK090203 · NIDDK · YALE UNIVERSITY · PI PARIKH, CHIRAG R · 2012 to 2016
$896k
Cardio-renal phenotype and prognosis in chronic heart failureK23HL114868 · NHLBI · YALE UNIVERSITY · PI TESTANI, JEFFREY M · 2012 to 2017
$845k
NHLBI NIH HHS K23 HL114868NHLBI NIH HHS K23HL114868NHLBI NIH HHS L30 HL115790NHLBI NIH HHS L30HL115790NIDDK NIH HHS K24 DK090203NIDDK NIH HHS K24DK090203
6 · The paper itself

Abstract

backgroundDifferentiating heart failure (HF) induced renal dysfunction (RD) from intrinsic kidney disease is challenging. It has been demonstrated that biomarkers such as B-type natriuretic peptide (BNP) or the blood urea nitrogen to creatinine ratio (BUN/creat) can identify high- vs low-risk RD. Our objective was to determine if combining these biomarkers could further improve risk stratification and clinical phenotyping of patients with RD and HF. METHODS AND

resultsA total of 908 patients with a discharge diagnosis of HF were included. Median values were used to define elevated BNP (>1296 pg/mL) and BUN/creat (>17). In the group without RD, survival was similar regardless of BNP and BUN/creat (n = 430, adjusted P = .52). Similarly, in patients with both a low BNP and BUN/creat, RD was not associated with mortality (n = 250, adjusted hazard ratio [HR] = 1.0, 95% confidence interval [CI] 0.6-1.6, P = .99). However, in patients with both an elevated BNP and BUN/creat those with RD had a cardiorenal profile characterized by venous congestion, diuretic resistance, hypotension, hyponatremia, longer length of stay, greater inotrope use, and substantially worse survival compared with patients without RD (n = 249, adjusted HR = 1.8, 95% CI 1.2-2.7, P = .008, P interaction = .005).

conclusionsIn the setting of decompensated HF, the combined use of BNP and BUN/creat stratifies patients with RD into groups with significantly different clinical phenotypes and prognosis.

Indexed as

AdultAgedBiomarkersBlood Urea NitrogenCardio-Renal SyndromeCohort StudiesConfidence IntervalsCreatinineFemaleGlomerular Filtration RateHeart FailureHospitals, UniversityHumansMaleMiddle AgedPhenotypeBiomarkersCreatinineblood urea nitrogen to creatinine ratioBNPCardiorenal syndromedecompensated heart failure

Identifiers

PMID25152498
PMCPMC4292792
OpenAlexW2050005443

What OpenQuestion holds

Textmetadata
LicenceTDM
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.