ArticleCardiovascular toxicology2026
Association Between Blood Heavy Metals and Selenium with All-Cause Mortality in Cardiovascular-Kidney-Metabolic Syndrome Populations: Exploring the Mediating Effects of Inflammatory Biomarkers.
Article in Cardiovascular toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular-kidney-metabolic (CKM) syndrome, characterized by the pathophysiological interplay among metabolic disorders, chronic kidney disease (CKD), and cardiovascular disease (CVD), significantly elevates mortality risk. Environmental heavy metal exposure and selenium deficiency are implicated in these conditions, but their combined impact on CKM syndrome is unclear. To investigate the associations of blood heavy metals (lead [Pb], cadmium [Cd], mercury [Hg], manganese [Mn]) and selenium (Se) with all-cause mortality in CKM populations, and examine the mediating role of inflammatory biomarkers. This cross-sectional study with prospective mortality follow-up included 6,072 participants from NHANES (2011-2018). Kaplan-Meier curves, multivariable Cox regression models, and restricted cubic spline (RCS) analyses were employed to assess all-cause mortality associations. Subgroup and interaction analyses evaluated risks across demographic strata. Mediation analysis was employed to explore the mediating effects of inflammatory biomarkers (NLR, MLR, NMLR, and SIRI). The Weighted quantile sum (WQS) model was utilized to estimate the effects of combined blood metal exposures. Among 6,072 participants, 409 deaths occurred during follow-up. In the fully adjusted model, there was a significant negative correlation between blood selenium levels and all-cause mortality in the CKM population. Compared with the lowest quartile (Q1), the highest selenium quartile (Q4) was associated with a 38% reduced mortality risk (HR = 0.62, 95% CI: 0.45-0.85, P = 0.003). RCS analysis revealed an L-shaped dose-response relationship (P for nonlinear = 0.002). Subgroup analyses confirmed consistent associations in both non-advanced CKM (stages 0-2) and advanced CKM (stages 3-4) (all P < 0.05, P for interaction = 0.163). Mediation analysis revealed that NLR, MLR, NMLR, and SIRI partially mediated the association between blood selenium and all-cause mortality, and the mediated proportions were relatively modest (ranging from 3.57 to 5.29%). Higher blood selenium was associated with reduced all-cause mortality in CKM syndrome after adjustment for measured confounders, and mediation analysis suggested a potential partial role of inflammation in this association. These findings underscore the need for targeted interventions to mitigate mortality in this high-risk population.
Indexed as
Identifiers
42766214What OpenQuestion holds
Registered trials
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.