Evidence mapPaperPMID 40420198Full record

SynthesisCritical care (London, England)2025

Novel biomarkers for predicting successful liberation of renal replacement therapy for acute kidney injury: a systematic review.

Qing Xu, Zhifeng Zhou, Lu Jin, Chen Liu, Peiyun Li, Fang Wang, Ling Zhang, Ping Fu

Abstract readSystematic Review
In one paragraph

Synthesis in Critical care (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

8 authors.

Qing XuDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Zhifeng ZhouDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Lu JinDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Chen LiuDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Peiyun LiDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Fang WangDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.
Ling ZhangDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China. zhangling_crrt@163.com.
Ping FuDepartment of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, 37 Guoxue Street, Chengdu, 610041, China.

Funding

National Key Research and Development Program of China 2023YFC2411800
6 · The paper itself

Abstract

introductionRenal replacement therapy (RRT) is commonly used in critically ill patients with acute kidney injury (AKI). However, optimal timing of RRT liberation remains controversy. This meta-analysis evaluates novel biomarkers to predict successful RRT liberation in critically ill AKI patients.

methodsThe systematic review reported following PRISMA guidelines, PubMed, Embase, and Scopus were searched up to May 2, 2025, and were screened using predefined criteria. Methodological quality was assessed using the Newcastle-Ottawa scale. Pooled ROC-AUCs with 95% CIs were calculated; heterogeneity was evaluated using I

resultsSixteen studies (3020 patients) involving 23 biomarkers were included. Urinary neutrophil gelatinase-associated lipocalin (uNGAL) demonstrated fair predictive performance with 4 studies (AUC 0.766, I

conclusionuNGAL moderately predicts short-term RRT liberation, while other biomarkers (e.g., PENK) require further validation. Standardizing definitions of successful liberation and integrating dynamic biomarker changed with clinical indicators (e.g., urine output) may enhance predictive accuracy. Further large-scale, prospective, and multicenter studies are needed to validate these findings.

Indexed as

Acute Kidney InjuryBiomarkersRenal Replacement TherapyHumansLipocalin-2BiomarkersLipocalin-2BiomarkerRenal replacement therapy (RRT)Successful liberationSuccessful weaning

Identifiers

PMID40420198
PMCPMC12105276

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.