Evidence map›Paper›PMID 42517928›Full record

SynthesisIntensive care medicine2026

STARDaki: a consensus-based STARD extension for standardized reporting of diagnostic accuracy in acute kidney injury.

Haichuan Yu, Yiming Li, Gaozhi P Mo, Zhe Luo, Alexander Zarbock, Dana Fuhrman, Yan Kang, Dechang Chen, Thomas Rimmelé, John Prowle and 10 more

Abstract readSystematic Review
In one paragraph

Synthesis in Intensive care medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

20 authors.

Haichuan Yu *Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Yiming Li *Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Gaozhi P Mo *Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Zhe LuoCardiac Intensive Care Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Alexander ZarbockDepartment of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany.
Dana FuhrmanDivisions of Critical Care Medicine, Nephrology and Hypertension, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Yan KangDepartment of Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, China.
Dechang ChenDepartment of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Thomas RimmeléMedical-Surgical Intensive Care Unit , Pasteur University Hospital, Nice, France.
John ProwleWilliam Harvey Research Institute, Queen Mary University of London, London, UK.
Patrick MurraySchool of Medicine, University College Dublin, Dublin, Ireland.
Nattachai SrisawatDivision of Nephrology, Department of Medicine, Faculty of Medicine, and Center of Excellence in Critical Care Nephrology, Chulalongkorn University, Bangkok, Thailand.
Daniel De BackerDepartment of Intensive Care, CHIREC Hospitals, Université Libre de Bruxelles, Brussels, Belgium.
Vedran PremuzicDepartment of Nephrology, Hypertension, Dialysis and Transplantation, School of Medicine, University of Zagreb, Zagreb, Croatia.
Rajit K BasuDepartment of Pediatrics, Division of Critical Care Medicine, Northwestern University Feinberg School of Medicine, Ann & Robert Lurie Children's Hospital of Chicago, Chicago, USA.
Claudio RoncoInternational Renal Research Institute of Vicenza, Department of Nephrology, Dialysis and Transplantation, San Bortolo Hospital, Vicenza, Italy.
Marlies Ostermann *Department of Intensive Care and Nephrology, King's College London, Guy's and St Thomas' NHS Foundation Trust, London, UK. m.ostermann@nhs.net.ORCID http://orcid.org/0000-0001-9500-9080
Kianoush Kashani *Division of Nephrology and Hypertension, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, USA. Kashani.Kianoush@mayo.edu.
John A Kellum *Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, USA. kellum@pitt.edu.
Zhiyong Peng *Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China. pengzy5@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBiomarkers have been identified to predict, diagnose and prognosticate acute kidney injury (AKI) but existing studies are heterogenous and contradictory.

objectiveTo compare diagnostic performance of AKI biomarkers, evaluate the quality of AKI biomarker studies and to develop standards for reporting studies of diagnostic test accuracy (DTA) of AKI biomarkers.

methodsA systematic literature review was conducted to identify studies focusing on the diagnostic performance of AKI biomarkers published before February 2025. Retrieved DTA studies were assessed for methodological quality and completeness using the QUADAS-2 and Standards for Reporting Diagnostic Accuracy (STARD) 2015 checklists. An international 17 member expert panel was convened to agree consensus standards for AKI biomarker studies (STARDaki) via a modified Delphi process.

results122 DTA studies for AKI biomarkers were identified, but 15 were insufficiently reported. Of the remaining 107 studies, only 19 reported on diagnosis of AKI within 48 h of sampling. Of these studies, only 16 were considered high-quality based on the QUADAS-2 criteria. The compliance level with the STARD checklist was too low to permit meta-analysis. The expert panel agreed criteria for patient selection, reference standards, and reporting of test-retest reliability to supplement the STARD guidance for AKI biomarker studies.

conclusionMost studies examining AKI biomarker performance fail to conform to the STARD standards for reporting, leading to poor diagnostic accuracy estimates and reduced clinical applicability and generalizability. An expert panel proposed STARDaki criteria to advance the development and clinical use of AKI biomarkers ( www.stardaki.icu ).

Indexed as

Acute Kidney InjuryBiomarkersChecklistConsensusDelphi TechniqueHumansBiomarkersAcute kidney injuryBiomarkersGuideline extension

Identifiers

PMID42517928
PMCPMC13433398

What OpenQuestion holds

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Registered trials

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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.