Evidence map›Paper›PMID 39789632›Full record

ArticleDiabetology & metabolic syndrome2025

Cadmium and selenium blood levels in association with congestive heart failure in diabetic and prediabetic patients: a cross-sectional study from the national health and nutrition examination survey.

Renyue Ji, Haisheng Wu, Hongli Lin, Yang Li, Yumeng Shi

Abstract read
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Article in Diabetology & metabolic syndrome, 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

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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

Who cites it

4 citing papers in PubMed.

  1. Review
  2. An Exploration of Machine Learning Methods in Human Biomonitoring.International journal of environmental research and public health · 2026
    Review
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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

5 authors.

Renyue JiSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pok Fu Lam, Hong Kong, SAR, China.
Haisheng WuSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pok Fu Lam, Hong Kong, SAR, China.
Hongli LinSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pok Fu Lam, Hong Kong, SAR, China.
Yang LiSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pok Fu Lam, Hong Kong, SAR, China.
Yumeng ShiSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, 7 Sassoon Road, Pok Fu Lam, Hong Kong, SAR, China. shiyume@hku.hk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEpidemiological research on the association between heavy metals and congestive heart failure (CHF) in individuals with abnormal glucose metabolism is scarce. The study addresses this research gap by examining the link between exposure to heavy metals and the odds of CHF in a population with dysregulated glucose metabolism.

methodThis cross-sectional study includes 7326 patients with diabetes and prediabetes from the National Health and Nutrition Examination Survey from 2011 to 2018. The exposure variables are five environmental heavy metals-cadmium (Cd), lead (Pb), mercury (Hg), selenium (Se), and manganese (Mn)-and the endpoint is CHF, determined via face-to-face interviews. Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes.

resultMultivariate logistic regression analysis Shows that only blood Cd exhibited a significant linear positive correlation with CHF odds (OR: 1.26, 95%CI 1.07-1.47, p = 0.005), there was a significant 14% decrease in the odds rate of CHF for each additional standard deviation of log10 Se (OR: 0.86,95%CI 0.76-0.96, P = 0.009). The WQS index for the metal mixture only marginally increased the odds of CHF by 1% (OR = 1.01, 95% CI 1.00-1.02, P = 0.032). BKMR analysis demonstrated a positive association between Cd levels and the odds of CHF, an inverse relationship with Se levels in patients with diabetes and prediabetes. However, no significant association was observed between the metal mixture and CHF.

conclusionThis cross-sectional study demonstrates that increased Cd levels are associated with a higher odds of CHF in patients with diabetes and pre-diabetes, whereas elevated blood Se levels significantly mitigate this odds.

Indexed as

Congestive heart failureDiabetesHeavy metalsNHANESPrediabetes

Identifiers

PMID39789632
PMCPMC11715992

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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.