Evidence map›Paper›PMID 35133653›Full record

ArticleAmerican journal of industrial medicine2022

Estimating mortality from coal workers' pneumoconiosis among Medicare beneficiaries with pneumoconiosis using binary regressions for spatially sparse data.

Rajib Paul, Oluwaseun Adeyemi, Ahmed A Arif

Open access · hybridAbstract read
In one paragraph

Article in American journal of industrial medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.8field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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.

Rajib PaulDepartment of Public Health Sciences, The University of North Carolina at Charlotte, Charlotte, North Carolina, USA.ORCID 0000-0002-5120-7525
Oluwaseun AdeyemiDepartment of Public Health Sciences, The University of North Carolina at Charlotte, Charlotte, North Carolina, USA.
Ahmed A ArifDepartment of Public Health Sciences, The University of North Carolina at Charlotte, Charlotte, North Carolina, USA.ORCID 0000-0002-0237-9937
University of North Carolina at Charlotte · US

Funding

The Federal Office of Rural Health Policy (FORHP), Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services (HHS) under cooperative agreement U1CRH30041
6 · The paper itself

Abstract

backgroundCoal workers' pneumoconiosis (CWP) is an occupational lung disease due to inhalation of coal dust. We estimated mortality from CWP and other pneumoconioses among Medicare beneficiaries.

methodsWe used the 5% Medicare Limited Claims Data Set, 2011-2014, to identify patients diagnosed with ICD-9-CM 500 (CWP) through 505 (Asbestosis, Pneumoconiosis due to other silica or silicates, Pneumoconiosis due to other inorganic dust, Pneumonopathy due to inhalation of other dust, and Pneumoconiosis, unspecified) codes. We applied binary regression models with spatial random effects to determine the association between CWP and mortality. Our inferences are based on Bayesian spatial hierarchical models, and model fitting was performed using Integrated Nested Laplace Approximation (INLA) algorithm in R/RStudio software.

resultsThe median age of the sample was 76 years. In a sample of 8531 Medicare beneficiaries, 2568 died. Medicare beneficiaries with CWP had 25% higher odds of death (adjusted OR: 1.25, 95% CI: 1.07, 1.46) than those with other types of pneumoconiosis. The number of comorbid conditions elevated the odds of death by 10% (adjusted OR: 1.10, 95% CI: 1.09, 1.10).

conclusionCWP increases the likelihood of death among Medicare beneficiaries. Healthcare professionals should make concerted efforts to monitor patients with CWP to prevent premature mortality.

Indexed as

AnthracosisCoal MiningPneumoconiosisAgedBayes TheoremCoalDustHumansMedicareUnited StatesCoalDustBayesian analysiscomorbiditylung diseaseoccupational hazardspatial models

Identifiers

PMID35133653
PMCPMC9305938
OpenAlexW4210897243

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.