Evidence map›Paper›PMID 39500961›Full record

ArticleScientific reports2024

Association between blood heavy metals and diabetic kidney disease among type 2 diabetic patients: a cross-sectional study.

Hongling Zhao, Ruili Yin, Yan Wang, Zihang Wang, Lijie Zhang, Yongsong Xu, Di Wang, Jianbo Wu, Lingling Wei, Longyan Yang and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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. Review
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  3. Article
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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

11 authors.

Hongling ZhaoCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Ruili YinCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Yan WangCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Zihang WangClinical Medicine, Fujian Medical University Clinical Medicine, Fuzhou, China.
Lijie ZhangCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Yongsong XuCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Di WangCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Jianbo WuCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Lingling WeiCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China.
Longyan YangCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China. lyyang15@ccmu.edu.cn.
Dong ZhaoCenter for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital Capital Medical University, Beijing, China. zhaodong@ccmu.edu.cn.

Funding

National Science Funding in China 82370823Tongzhou District Science and Technology Project KJ2022CX017
6 · The paper itself

Abstract

Studies on the correlation of exposure to metals with diabetic kidney disease (DKD) is scarce, especially concerning the impact of mixed metals on DKD. This study aimed to explore the association of blood heavy metals with DKD risk among type 2 diabetes mellitus (T2DM) patients. This cross-sectional study enrolled patients with T2DM in NHANES 2011-2020. ICP‒MS was applied to detect five metals, namely, Pb, Cd, Hg, Se and Mn, in blood. At the same time, the impacts of exposure to single and mixed metals on DKD were assessed using multivariable logistic regression, WQS, and BKMR models. The relationship was examined based on age, sex, BMI, hypertension, smoking status and PIR. Totally 2362 participants were enrolled for final analysis. Among them, 634 (26.84%) patients undergoing T2DM had DKD. Logistic regression indicated that, Pb (Q4: OR [95% CI]: 1.557 [1.175, 2.064]) was related to DKD when all covariates were adjusted. The WQS analysis, which was set in a positive directional mode, suggested that Pb was correlated positively with a higher incidence of DKD. In BKMR analysis, linear dose‒response curves were generated for Pb when fixing the other metals in the 50th percentile. In addition, exposure to mixed metals was significantly positively related to DKD. Subgroup analysis during logistic regression demonstrated that Pb was significantly and positively related to DKD in females, over 50 years, those with over 25 kg/m

Indexed as

Diabetes Mellitus, Type 2Diabetic NephropathiesMetals, HeavyAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedRisk FactorsMetals, HeavyBKMRBlood heavy metalsDiabetic kidney diseaseNHANESWQS

Identifiers

PMID39500961
PMCPMC11538502

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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.