Evidence mapPaperPMID 41669246Full record

SynthesisFrontiers in endocrinology2025

A meta-analysis of serum uric acid and diabetic nephropathy risk in type 2 diabetes.

Jing Zhao, Lingzhu Zhao

Abstract readMeta-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 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Article
  3. 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

2 authors.

Jing ZhaoDepartment of Nephrology & Hemodialysis Center, Xi'an Ninth Hospital, Xi'an, Shaanxi, China.
Lingzhu ZhaoDepartment of Neurology-Unit 1, Xi'an Ninth Hospital, Xi'an, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the correlation between serum uric acid (SUA) levels and the risk of diabetic kidney disease (DKD) in patients with type 2 diabetes mellitus (T2DM), and to evaluate the potential clinical implications of uric acid-lowering interventions. Methods: Relevant studies on the relationship between serum uric acid levels and the risk of DKD in patients with type 2 diabetes mellitus were collected by systematically searching databases such as PubMed, Web of Science, and Cochrane Library. The quality of the included studies was evaluated using the Cochrane risk-of-bias assessment tool, and Meta-analysis was performed using RevMan 5.3 software. The primary outcome indicators included the incidence of DKD, the odds ratio (OR) and 95% confidence interval (CI) of the relationship between serum uric acid levels and the risk of DKD. Results: After retrieval and screening, 8 randomized controlled trials (RCTs) (with a sample size of 491) were included in the Meta-analysis. The results showed that the estimated glomerular filtration rate (eGFR) in the hyperuricemia group was lower than that in the normal group (MD = 4.40, 95% CI [0.66, 8.14], Conclusion: Elevated serum uric acid levels are significantly associated with an increased risk of DKD in patients with type 2 diabetes mellitus. Monitoring serum uric acid levels may help to identify high-risk individuals for DKD at an early stage and provide a reference for clinical intervention.

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesUric AcidBiomarkersGlomerular Filtration RateHumansRandomized Controlled Trials as TopicRisk FactorsBiomarkersUric Aciddiabetic kidney diseaseinterventionmeta-analysisserum uric acidtype 2 diabetes mellitus

Identifiers

PMID41669246
PMCPMC12883379

What Socratic 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 Socratic graph.