Evidence map›Paper›PMID 40331139›Full record

SynthesisFrontiers in endocrinology2025

A systematic review and meta-analysis of microRNAs in the diagnosis of early diabetic kidney disease.

Lujie Jiang, Li Li, Ke Zhang, Liping Zheng, Xinhuan Zhang, Yanlian Hou, Mingfeng Cao, Yan Wang

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. miRNA in the Progression of Diabetic Kidney Disease: New Insight.International journal of molecular sciences · 2025
    Review
  10. 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.

Lujie Jiang *Department of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.
Li Li *Department of Endocrinology, The First People's Hospital of Taian, Taian, Shandong, China.
Ke Zhang *Department of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.
Liping ZhengDepartment of Endocrinology, The First People's Hospital of Ningyang, Taian, Shandong, China.
Xinhuan ZhangDepartment of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.
Yanlian HouDepartment of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.
Mingfeng CaoDepartment of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.
Yan WangDepartment of Endocrinology, The Second Affiliated Hospital of Shandong First Medical University, Taian, Shandong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study was to comprehensively assess the overall diagnostic value of circulating microRNAs (miRNAs or miRs) as biomarkers for the early diagnosis of diabetic kidney disease (DKD) through Meta-analysis, and to identify potential molecular biomarkers with higher diagnostic value for early DKD. Methods: The CNKI, Wanfang date, VIP, Pubmed, Embase, Web of Science, and Cochrane Library until January 2024 were searched. Relevant studies associated with the value of miRNAs in the diagnosis of early DKD were selected. Case numbers, sensitivity, and specificity were extracted from the included literature for both the observation and control groups. Results: Nine studies including 655 cases of early DKD patients and 664 cases as a control group were conducted. The comprehensive sensitivity was 0.76, comprehensive specificity was 0.74, combined positive likelihood ratio was 2.9 and the combined negative likelihood ratio was 0.33, diagnostic odds ratio (DOR) was 9. The summary receiver operating characteristic (SROC) curve was drawn and the area under the curve (AUC) was 0.79. Blood and urine source data were analyzed and showed that urine source miRNA had a higher sensitivity (0.82vs 0.68) and a higher DOR (10.5vs 8.2) than blood source miRNA. Conclusion: MiRNAs may serve as promising noninvasive biomarkers for the early diagnosis of DKD. The diagnostic value of miRNAs in urine samples may be higher than that in blood samples. The combined detection of some miRNAs or other clinical indicators can enhance the accuracy of early DKD diagnosis. Systematic Review Registration: https://osf.io, identifier DOI: 10.17605/OSF.IO/FC6DK.

Indexed as

Diabetic NephropathiesMicroRNAsBiomarkersEarly DiagnosisHumansBiomarkersMicroRNAsdiagnostic testsearly diabetic kidney diseasemeta-analysismicroRANsystematic review

Identifiers

PMID40331139
PMCPMC12052537

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.