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Consensus Statement

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, Patrick Murray, Nattachai Srisawat, Daniel De Backer, Vedran Premuzic, Rajit K. Basu, Claudio Ronco, Marlies Ostermann*, Kianoush Kashani*, John A. Kellum*, Zhiyong Peng*

What is STARDaki?

STARDaki is a domain-specific extension of the STARD 2015 checklist for diagnostic accuracy studies of AKI biomarkers. Developed through a systematic review of 107 studies and a modified Delphi consensus process with 17 international experts from 10 countries, it provides 30 reporting elements across 17 domains to standardize the reporting of AKI biomarker research.

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International Experts

Interactive Checklist

Browse all 30 items with STARD 2015 comparisons, or switch to fill mode to track your reporting progress.

Expert-Endorsed

Developed by 17 international experts from 10 countries using the RAND/UCLA Appropriateness Method.

Evidence-Based

Built on a systematic review of 107 AKI biomarker studies assessing STARD compliance and methodological quality.

Bilingual

Available in English and Chinese to serve the global AKI research community.

The Tool

STARDaki Checklist

30 items extending STARD 2015 for AKI biomarker studies. Browse to compare with STARD 2015, or switch to Fill mode to track reporting progress.

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Abbreviations

AKI, Acute Kidney Injury; KDIGO, Kidney Disease: Improving Global Outcomes; AUC, Area Under the Curve; PPV, Positive Predictive Value; NPV, Negative Predictive Value; LR+, Likelihood Ratio Positive; LR-, Likelihood Ratio Negative; NGAL, Neutrophil Gelatinase-Associated Lipocalin; FDA, Food and Drug Administration; CE, Conformité Européenne; LLoD, Lower Limit of Detection; ULoD, Upper Limit of Detection; GEE, Generalized Estimating Equations; EHR, Electronic Health Record; ICU, Intensive Care Unit; CKD, Chronic Kidney Disease; AUPRC, Area Under the Precision-Recall Curve; RRT, Renal Replacement Therapy.
Evidence Base

Why STARDaki Was Developed

A systematic review of 107 AKI biomarker studies revealed critical gaps in reporting quality, motivating the need for standardized reporting guidance.

Acute kidney injury (AKI) affects 5–12% of hospitalized patients and over 50% of ICU patients. While biomarkers offer promise for early detection, existing studies are heterogeneous and poorly reported.

We systematically reviewed 107 AKI biomarker diagnostic accuracy studies and found that on average, only 54.5% of STARD 2015 items were properly reported. Critical methodological details—such as blinding of reference standard assessors, sample size justification, and handling of indeterminate results—were frequently missing. The wide performance ranges observed across studies are not shortcomings of individual biomarkers but a predictable consequence of heterogeneous reporting.

STARD 2015 Compliance & QUADAS-2 Assessment

STARD Compliance and QUADAS-2

Systematic Review

  • 13,057 articles identified across PubMed, Embase, Cochrane Library, Web of Science
  • 107 studies included; 19 for descriptive analysis
  • 48-hour sampling-to-diagnosis window for biomarker evaluation
  • STARD 2015 and QUADAS-2 quality assessment
PRISMA flowchart

Delphi Consensus

  • 17-member panel from 10 countries across Europe, North America, Asia
  • RAND/UCLA Appropriateness Method with iterative surveys
  • Round 1: mean 4.66 (AR 95%) → Round 2 confirmed: mean 4.54 (AR 94%)
  • Final 30-element checklist approved by unanimous vote
Delphi results

Detailed supporting information—including complete search strategies, individual study quality assessments, and Delphi survey materials—is available in the supplementary materials.

Team

Development Team & Expert Panel

A 7-member development team and 17 expert panelists from 10 countries across Europe, North America, and Asia.

Development Team (7 members)

Expert Panel (17 members)

Resources

How to Cite & Download

Citation

Yu H, Li Y, Mo GP, et al. STARDaki: A Consensus-Based STARD Extension for Standardized Reporting of Diagnostic Accuracy in Acute Kidney Injury. 2026.

@article{yu2026stardaki,
  title={STARDaki: A Consensus-Based STARD Extension...},
  author={Yu, Haichuan and Li, Yiming and Mo, Gaozhi P. and others},
  year={2026}}

Expert Panel

Haichuan Yu
Yiming Li
Gaozhi P. Mo
Zhe Luo
Alexander Zarbock
Dana Fuhrman
Yan Kang
Dechang Chen
Thomas Rimmelé
John Prowle
Patrick Murray
Nattachai Srisawat
Daniel De Backer
Vedran Premuzic
Rajit K. Basu
Claudio Ronco
Marlies Ostermann*
Kianoush Kashani*
John A. Kellum*
Zhiyong Peng*

* Corresponding authors

Contact Us

Haichuan Yu
(Development Team)
yuhaichuan@whu.edu.cn
Marlies Ostermann
(Supervisor)
m.ostermann@nhs.net
Kianoush Kashani
(Supervisor)
Kashani.Kianoush@mayo.edu
John A. Kellum
(Supervisor)
kellum@pitt.edu
Zhiyong Peng
(Supervisor)
pengzy5@hotmail.com
Wuhan University

Supported by the National Natural Science Foundation of China (Zhiyong Peng, No. 82272208 and 82572484)

© 2026 STARDaki Working Group. All rights reserved.

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