Evidence map›Paper›PMID 39827188›Full record

ArticleScientific reports2025

Investigating the role of the metabolic score for visceral Fat in assessing the prevalence of chronic kidney disease from the NHANES 1999-2018.

Xingcheng Zhou, Jiayi Xiang, Shuxian Zhang, Jun Yang, Yi Tang, Yalan Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

6 authors.

Xingcheng Zhou *Department of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China.
Jiayi Xiang *Fifth Department of Medicine (Nephrology/Endocrinology/Rheumatology), University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany.
Shuxian ZhangDepartment of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China.
Jun YangDepartment of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China.
Yi TangDepartment of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China.
Yalan WangDepartment of Pathology, College of Basic Medicine, Chongqing Medical University, Chongqing, China. 100475@cqmu.edu.cn.

Funding

China Postdoctoral Science Foundation 2024MD764050Chongqing Medical University R1087National Natural Science Foundation of China 82402559
6 · The paper itself

Abstract

This study investigates the association between the Metabolic Score for Visceral Fat (METS-VF) and chronic kidney disease (CKD), assessing METS-VF as a potential predictor of CKD risk. Utilizing data from the 1999-2018 National Health and Nutrition Examination Survey (NHANES), this cross-sectional study included 24,387 adult participants. Multivariable logistic regression, restricted cubic spline models, and threshold effect analyses were employed to explore the relationship. The results revealed a significant positive association, with multivariable logistic regression showing that each unit increase in METS-VF was associated with an 86% higher risk of CKD (OR: 1.86, 95% CI: 1.48-2.34). Critical METS-VF thresholds (6.10 and 7.55) were identified, at which CKD risk increased substantially. Subgroup analyses indicated that the association was particularly pronounced among older adults and males. These findings suggest that METS-VF is a reliable predictor for assessing CKD risk and that lifestyle interventions, including dietary modifications and exercise programs, may mitigate this risk.

Indexed as

Intra-Abdominal FatRenal Insufficiency, ChronicAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedNutrition SurveysPrevalenceRisk FactorsUnited States

Identifiers

PMID39827188
PMCPMC11742988

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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.