Evidence map›Paper›PMID 42086806›Full record

ReviewPediatric nephrology (Berlin, Germany)2026

Research progress on biomarkers for acute kidney injury in children.

Wenqin Jin, Qing Ye, Dongqing Cheng

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pediatric nephrology (Berlin, Germany), 2026. 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. Article
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

3 authors.

Wenqin JinSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, China.
Qing YeDepartment of Clinical Laboratory, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents' Health And Diseases, Hangzhou, 310052, China. qingye@zju.edu.cn.
Dongqing ChengSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, 310053, China. chengdq@zcmu.edu.cn.

Funding

Joint Fund of Zhejiang Provincial Natural Science Foundation of China LKLY25H200004Joint TCM Science & Technology Projects of National Demonstration Zones for Comprehensive TCM Reform GZY-KJS-ZJ-2025-015Zhejiang Provincial Outstanding Youth Science Foundation LR24H200001
6 · The paper itself

Abstract

Pediatric acute kidney injury (AKI) often presents insidiously and progresses rapidly. Traditional diagnostic criteria based on serum creatinine and urine output are markedly delayed and insufficient to capture injury patterns across different etiologies. This paper aims to summarize recent advances in pediatric AKI biomarker research since the release of the ADQI 23 (2020) consensus. Focusing on three major clinical scenarios-cardiac surgery, sepsis, and nephrotoxic drugs-it reviews early biomarker evidence and explores their potential applications in risk stratification. At the mechanistic level, this paper outlines key pathological pathways in pediatric AKI progression: oxygenation-perfusion imbalance after cardiac surgery, endothelium-immune dysregulation driven by sepsis, and tubular-mitochondrial injury associated with nephrotoxic exposure. In CS-AKI, uNGAL shows the earliest elevation within hours after cardiopulmonary bypass, followed by sequential changes in IL-18, L-FABP, and KIM-1. [TIMP-2] × [IGFBP7] and exosomal miRNA aid in identifying high-risk or severe AKI. In SA-AKI, suPAR and glycocalyx/endothelial injury markers (e.g., syndecan-1, Angpt-2/sTM/Tie-2), combined with urinary DKK3 and complement Ba, can be used for early risk stratification and predicting poor outcomes. In NT-AKI, uNGAL has high negative predictive value for excluding severe AKI, while uKIM-1, uCysC, uOPN, and multi-biomarker combinations can indicate subclinical tubular injury earlier after drug exposure. Overall, single biomarkers struggle to cover AKI heterogeneity. Future efforts should integrate functional dynamic assessments (e.g., FST, RRI), scenario-based multi-biomarker combinations, and AI dynamic models to propose evidence-based, scenario-stratified identification pathways. These will serve as structured references for prospective studies and clinical workflow optimization.

Indexed as

BiomarkersFunctional testingMachine learningMetabolomicsPediatric AKI

Identifiers

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.