Evidence mapPaperPMID 40980175Full record

ReviewFrontiers in cardiovascular medicine2025

A systematic review of the connection between serum uric acid levels and the risk of cardiovascular disease.

Jin-Jin Wang, Jin-Ke Yi, Li-Rong Zhou, Jun Chen, Bin-Qiang Zhang, Hui-Min Huang, Ying Wei

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 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
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  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

7 authors.

Jin-Jin Wang *Experiment Center of Medicine, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Jin-Ke Yi *Rehabilitation Department, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Li-Rong Zhou *Department of Endocrinology and Metabolism, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Jun ChenExperiment Center of Medicine, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Bin-Qiang ZhangExperiment Center of Medicine, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Hui-Min Huang *Experiment Center of Medicine, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.
Ying Wei *Experiment Center of Medicine, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Serum uric acid (SUA) has emerged as a significant biomarker for cardiovascular disease (CVD) risk assessment, garnering increasing attention in recent years. As CVD remains a leading cause of global mortality, identifying effective biomarkers for risk stratification is of paramount importance. Current evidence indicates a strong association between elevated SUA levels and increased CVD risk. However, the precise mechanisms and confounding factors underlying this relationship remain unclear. This review examines the link between SUA and CVD, exploring potential biological pathways-including metabolic syndrome, inflammatory responses, and oxidative stress-that may mediate this association. By synthesizing existing literature, this article aims to provide insights for future research and clinical applications, ultimately enhancing the understanding of SUA's utility in CVD risk evaluation.

Indexed as

cardiovascular diseaseinflammatory responsemetabolic syndromerisk assessmentserum uric acid

Identifiers

PMID40980175
PMCPMC12446315

What Socratic holds

Textmetadata
LicenceCC BY
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.