Evidence map›Paper›PMID 29172665›Full record

ArticleBiomarkers in medicine2017

Group analysis identifies differentially elevated biomarkers with distinct outcomes for advanced acute kidney injury in cardiac surgery.

Haiqun Lin, Rebecca Scherzer, Heather Thiessen Philbrook, Steven G Coca, Francis Perry Wilson, Amit X Garg, Michael G Shlipak, Chirag R Parikh

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomarkers in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Trial
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.

Haiqun LinDepartment of Biostatistics, Yale University School of Medicine, Connecticut, 60 College Street, New Haven, CT 06520, USA.
Rebecca ScherzerDepartment of Medicine, University of California San Francisco & Veterans Affairs Medical Center, San Francisco, CA 94121, USA.
Heather Thiessen PhilbrookDivision of Nephrology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA.
Steven G CocaDivision of Nephrology, Icahn School of Medicine, Mount Sinai Hospital, New York, NY 10029, USA.
Francis Perry WilsonDivision of Nephrology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA.
Amit X GargDivision of Nephrology, Department of Medicine & Department of Epidemiology & Biostatistics, University of Western Ontario, London, N6A 3K7, Canada.
Michael G ShlipakDepartment of Medicine, University of California San Francisco & Veterans Affairs Medical Center, San Francisco, CA 94121, USA.
Chirag R ParikhDivision of Nephrology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT 06510, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Novel Biomarkers in Cardiac Surgery to Detect Acute Kidney InjuryR01HL085757 · NHLBI · YALE UNIVERSITY · PI PARIKH, CHIRAG R · 2007 to 2019
$10.3M
Mediators & prognostic value of muscle mass & function in chronic kidney diseaseK23DK097201 · NIDDK · YALE UNIVERSITY · PI WILSON, FRANCIS PERRY · 2013 to 2017
$916k
NCATS NIH HHS UL1 TR001863NHLBI NIH HHS R01 HL085757NIDDK NIH HHS K23 DK097201
6 · The paper itself

Abstract

aimTo investigate early postoperative biomarkers for risk discrimination of advanced acute kidney injury (AKI). MATERIALS &

methodsPostoperative plasma biomarkers including NGAL, h-FABP, CK-MB, hsTNT, NT-proBNP, IL-6, IL-10 and VEGF were analyzed using group-based method among 426 patients with AKI after cardiac surgery.

resultsSix patient groups with distinct biomarker patterns were identified. Individual biomarker displayed significant difference across the groups. The groups showed better discrimination for advanced AKI than any single biomarker either with or without adjusting for clinical variables. Average concentration of a single biomarker within each group, mortality and risk of a secondary outcome all demonstrated an approximately U-shaped relationship with proportion of advanced AKI within each group.

conclusionThe group-based analysis revealed that the order of the patient groups with an increasing likelihood of advanced AKI had a nonlinear relationship with average concentration of an individual biomarker, mortality and risk of other outcomes.

Indexed as

Acute Kidney InjuryAgedAged, 80 and overBiomarkersCardiac Surgical ProceduresFemaleHumansMaleMiddle AgedPostoperative ComplicationsBiomarkersadvanced AKIbiomarkers of AKIgroup-based analysis

Identifiers

PMID29172665
PMCPMC5753615

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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.