Evidence map›Paper›PMID 31631727›Full record

ArticleJournal of the American Heart Association2019

Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?

Xin Wang, Bhramar Mukherjee, Sung Kyun Park

Open access · goldAbstract read
In one paragraph

Article in Journal of the American Heart Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
2.9field-weighted citation impact, top 9% of its field
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

33 citing papers in PubMed, 46 citations in OpenAlex.

  1. Urinary Metal Levels after Repeated Edetate Disodium Infusions: Preliminary Findings.International journal of environmental research and public health · 2020
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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

3 authors at 1 institution in 1 country.

Xin WangDepartment of Epidemiology School of Public Health University of Michigan Ann Arbor MI.
Bhramar MukherjeeDepartment of Biostatistics School of Public Health University of Michigan Ann Arbor MI.
Sung Kyun ParkDepartment of Epidemiology School of Public Health University of Michigan Ann Arbor MI.
University of Michigan–Ann Arbor · US

Funding

University of Michigan ERC-supplement (TRT)T42OH008455 · OH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI NEITZEL, RICHARD L · 2005 to 2025
$32.3M
Strategic Vision & Impact on Environmental HealthP30ES017885 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Dana Dolinoy · 2011 to 2026
$21.3M
Exposure to Multipollutants and Obesity, Type-2 Diabetes and Metabolic SyndromeR01ES026578 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PARK, SUNG KYUN · 2016 to 2020
$2.4M
A Longitudinal Study of Endocrine Disruptor Mixtures and Reproductive AgingR01ES026964 · NIEHS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PARK, SUNG KYUN · 2016 to 2021
$2.4M
NIEHS NIH HHS P30 ES017885NIEHS NIH HHS R01 ES026578NIEHS NIH HHS R01 ES026964NIOSH CDC HHS T42 OH008455
6 · The paper itself

Abstract

Background To evaluate whether blood markers of lead, cadmium, and mercury can improve prediction for cardiovascular disease (CVD) mortality when added individually, jointly, or as an integrative index/Environmental Risk Score (ERS), in a model with established risk factors. Methods and Results Our study sample comprised 16 028 adults aged ≥40 years who were enrolled in the National Health and Nutrition Examination Survey 1999-2012 and followed up through December 31, 2015. The study sample was randomly split into training for the ERS construction (n=8043) and testing for the evaluation of prediction performance (n=7985). ERS was computed using elastic-net penalized Cox's model based on the selected metal predictors predicting CVD mortality. During median follow-up of 7.2 years, 517 died from CVD. In the training set, linear terms of cadmium and mercury, squared terms of lead and mercury, and all 3 pairwise interactions were selected by elastic-net for ERS construction. In the testing set, the C-statistic increased from 0.845 when only established CVD risk factors were in the model to 0.854 when the ERS was additionally added to the model. Addition of all linear, squared, and pairwise interaction terms of blood metals to the Cox's models improved C-statistic from 0.845 to 0.857. The improvement remained significant when it was assessed by net reclassification improvement and integrated discrimination improvement. Conclusions Our findings suggest that blood markers of toxic metals can improve CVD risk prediction over the established risk factors and highlight their potential utility for CVD risk assessment, prevention, and precision health.

Indexed as

AgedBiomarkersCadmiumCardiovascular DiseasesFemaleHumansLeadMaleMercuryMiddle AgedPredictive Value of TestsRisk FactorsBiomarkersCadmiumLeadMercuryblood cadmiumblood leadblood mercurycardiovascular mortalityrisk prediction

Identifiers

PMID31631727
PMCPMC6898859
OpenAlexW2980465887

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.