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The Impact of Occupational Exposures on the Risk of Idiopathic Pulmonary Fibrosis: A Systematic Review and Meta-Analysis

2023· review· en· W4389729337 on OpenAlexaff
Sheiphali A. Gandhi, Bohyung Min, Jane C. Fazio, Kerri A. Johannson, Craig Steinmaus, Carl Reynolds, Kristin J. Cummings

Bibliographic record

VenueAnnals of the American Thoracic Society · 2023
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of Calgary
FundersNational Cancer InstituteWellcome TrustCalifornia Department of Public Health
KeywordsMedicineOdds ratioIdiopathic pulmonary fibrosisConfidence intervalMeta-analysisPopulationEnvironmental healthInternal medicineLung

Abstract

fetched live from OpenAlex

Abstract Rationale Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic pulmonary disorder of unknown etiology that is characterized by a usual interstitial pneumonia pattern. Previous meta-analyses have reported associations between occupational exposures and IPF, but higher-quality studies have been published in recent years, doubling the number of studied patients. Objectives To provide a contemporary and comprehensive assessment of the relationship between occupational exposures and IPF. Methods We searched PubMed, Embase, and Web of Science through July 2023 to identify all publications on occupational exposure and IPF. We conducted a meta-analysis of the occupational burden, odds ratio (OR), and population attributable fraction (PAF) of exposures. Five exposure categories were analyzed: vapors, gas, dust, and fumes (VGDF); metal dust; wood dust; silica dust; and agricultural dust. A comprehensive bias assessment was performed. The study protocol was registered in the International Prospective Register of Systematic Reviews (identifier CRD42021267808). Results Our search identified 23,942 publications. Sixteen publications contained relative risks needed to calculate pooled ORs and PAFs, and 12 additional publications reported an occupational burden within a case series. The proportion of cases with occupational exposures to VGDF was 44% (95% confidence interval [CI], 36–53%), with a range of 8–17% within more specific exposure categories. The pooled OR was increased for VGDF at 1.8 (95% CI, 1.3–2.4), with a pooled PAF of 21% (95% CI, 15–28%). ORs and PAFs, respectively, were found to be 1.6 and 7% for metal dust, 1.6 and 3% for wood dust, 1.8 and 14% for agricultural dust, and 1.8 and 4% for silica dust. The pooled ORs and PAFs within specific exposure categories ranged from 1.6 to 1.8 and from 4% to 14%, respectively. We identified some publication bias, but it was not sufficient to diminish the association between occupational exposures and IPF based on sensitivity analysis and bias assessment. Conclusions Our findings indicate that 21% of IPF cases (or approximately one in five) could be prevented by removal of occupational exposure (alongside a pooled OR of 1.8). Additionally, 44% of patients with IPF report occupational exposure to VGDF. This meta-analysis suggests that a considerable number of cases of IPF are attributable to inhaled occupational exposures and warrant increased consideration in the clinical care of patients and future prevention efforts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.038
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.204
GPT teacher head0.467
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2023
Admission routes1
Has abstractyes

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