Evidence map›Paper›PMID 39138396›Full record

SynthesisBMC nephrology2024

Panel miRNAs are potential diagnostic markers for chronic kidney diseases: a systematic review and meta-analysis.

Gantsetseg Garmaa, Rita Nagy, Tamás Kói, Uyen Nguyen Do To, Dorottya Gergő, Dénes Kleiner, Dezső Csupor, Péter Hegyi, Gábor Kökény

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in BMC nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Trial
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
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

9 authors.

Gantsetseg GarmaaInstitute of Translational Medicine, Semmelweis University, Nagyvárad tér 4, Budapest, 1089, Hungary.
Rita NagyCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Tamás KóiCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Uyen Nguyen Do ToCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Dorottya GergőCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Dénes KleinerCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Dezső CsuporCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Péter HegyiCenter for Translational Medicine, Semmelweis University, 1085 Budapest, Üllői út 26, Budapest, Hungary.
Gábor KökényInstitute of Translational Medicine, Semmelweis University, Nagyvárad tér 4, Budapest, 1089, Hungary. kokeny.gabor@semmelweis.hu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate detection of kidney damage is key to preventing renal failure, and identifying biomarkers is essential for this purpose. We aimed to assess the accuracy of miRNAs as diagnostic tools for chronic kidney disease (CKD).

methodsWe thoroughly searched five databases (MEDLINE, Web of Science, Embase, Scopus, and CENTRAL) and performed a meta-analysis using R software. We assessed the overall diagnostic potential using the pooled area under the curve (pAUC), sensitivity (SEN), and specificity (SPE) values and the risk of bias by using the QUADAS-2 tool. The study protocol was registered on PROSPERO (CRD42021282785).

resultsWe analyzed data from 8351 CKD patients, 2989 healthy individuals, and 4331 people with chronic diseases. Among the single miRNAs, the pooled SEN was 0.82, and the SPE was 0.81 for diabetic nephropathy (DN) vs. diabetes mellitus (DM). The SEN and SPE were 0.91 and 0.89 for DN and healthy controls, respectively. miR-192 was the most frequently reported miRNA in DN patients, with a pAUC of 0.91 and SEN and SPE of 0.89 and 0.89, respectively, compared to those in healthy controls. The panel of miRNAs outperformed the single miRNAs (pAUC of 0.86 vs. 0.79, p < 0.05). The SEN and SPE of the panel miRNAs were 0.89 and 0.73, respectively, for DN vs. DM. In the lupus nephritis (LN) vs. systemic lupus erythematosus (SLE) cohorts, the SEN and SPE were 0.84 and 0.81, respectively. Urinary miRNAs tended to be more effective than blood miRNAs (p = 0.06).

conclusionMiRNAs show promise as effective diagnostic markers for CKD. The detection of miRNAs in urine and the use of a panel of miRNAs allows more accurate diagnosis.

Indexed as

BiomarkersMicroRNAsRenal Insufficiency, ChronicDiabetic NephropathiesHumansLupus Erythematosus, SystemicLupus NephritisBiomarkersMicroRNAsMIRN192 microRNA, humanBiomarkerChronic kidney diseaseDiagnostic accuracymicroRNA

Identifiers

PMID39138396
PMCPMC11323638

What Socratic holds

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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.