Evidence map›Paper›PMID 42248994›Full record

ArticleScientific reports2026

Association of serum uric acid with cardiovascular-kidney-metabolic syndrome in elderly populations: results from Chinese and US cohorts.

Wencai Ke, Kangan Wang, Biying Wu, Bingbing Zha, Yong Lin

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Wencai Ke *Department of Clinical Laboratory, Fifth People's Hospital of Shanghai Fudan University, Shanghai, China.
Kangan Wang *Department of Endocrinology, Fifth People's Hospital of Shanghai Fudan University, 801 Heqing Road, Shanghai, 200240, China.
Biying WuDepartment of Clinical Laboratory, Fifth People's Hospital of Shanghai Fudan University, Shanghai, China.
Bingbing ZhaDepartment of Endocrinology, Fifth People's Hospital of Shanghai Fudan University, 801 Heqing Road, Shanghai, 200240, China. bingbingzha@fudan.edu.cn.
Yong LinDepartment of Laboratory Medicine, Shanghai Medical School, Huashan Hospital of Fudan University, Fudan University, Shanghai, 200030, China. linyong7007@163.com.

Funding

the Medical Specialty Construction Project of Minhang District, Shanghai No.2025MWTZB01the Shanghai Municipal Key Clinical Specialty Grant No. 2024ZDXK0016
6 · The paper itself

Abstract

Cardiovascular-kidney-metabolic (CKM) syndrome is highly prevalent among the elderly. Serum uric acid (SUA) may serve as a potential marker for CKM, but evidence on the association between SUA levels and the progression of CKM syndrome remains scarce and controversial. This study aims to investigate the relationship between SUA levels and CKM syndrome in elderly populations by utilizing cohort data from China and the United States. We analyzed 3,299 participants from the Shanghai Friendship Community Elderly Cohort (SFCEC) and 2,372 from the US National Health and Nutrition Examination Survey (NHANES) 2011-2018.SUA was measured using standardized assays. Ordinal logistic regression models were performed. Restricted cubic spline regression (RCS) was performed to visualize the dose-response relationship. The prevalence of CKM syndrome (stages 1-4) was strikingly high in both elderly cohorts (98.33% in the SFCEC cohort and 98.76% in the NHANES cohort). After comprehensive adjustment, multivariable analysis revealed that each 1 mg/dl increase in SUA was associated with 24.9% (OR = 1.249, 95% CI 1.186-1.315) and 27.8% (OR = 1.278, 95% CI 1.174-1.392) elevated risks of CKM stages in the SFCEC and NHANES cohorts, respectively. Compared with the lowest tertile, participants in the highest tertile demonstrated significantly increased CKM risks (SFCEC: OR = 1.966, 95% CI 1.653-2.339; NHANES: OR = 1.975, 95% CI 1.472-2.650). RCS analysis indicated a positive linear dose-response relationship between SUA levels and CKM staging. A significant interaction by sex was observed (P < 0.001), suggesting potential sex differences that warrant further investigation. This study reveals that elevated SUA levels are associated with higher CKM stages in the elderly population.Further research is needed to evaluate the potential role of SUA measurement in CKM risk assessment.

Indexed as

Cardio-Renal SyndromeMetabolic SyndromeUric AcidAgedBiomarkersChinaCohort StudiesEast Asian PeopleFemaleHumansMaleNutrition SurveysPrevalenceRisk FactorsUnited StatesBiomarkersUric AcidCardiovascular-kidney-metabolic (CKM) syndromeElderly populationSerum uric acid (SUA)

Identifiers

PMID42248994
PMCPMC13484483

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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.