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Occupational Exposures and Computed Tomographic Imaging Characteristics in the SPIROMICS Cohort

2018· article· en· W2895970929 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnals of the American Thoracic Society · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University Health Centre
FundersNational Institute of Environmental Health SciencesNational Institutes of HealthGrifolsRegeneron PharmaceuticalsSunovionForest Research InstituteCOPD FoundationGlaxoSmithKlineIkariaNational Heart, Lung, and Blood InstituteNovartis Pharmaceuticals CorporationAstraZenecaChiesi FarmaceuticiSanofiFoundation for the National Institutes of Health
KeywordsMedicineCOPDComputed tomographicCohortAirwayRadiologyComputed tomographyPulmonary diseaseCohort studyInternal medicineSurgery

Abstract

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RATIONALE: Quantitative computed tomographic (CT) imaging can aid in chronic obstructive pulmonary disease (COPD) phenotyping. Few studies have identified whether occupational exposures are associated with distinct CT imaging characteristics. OBJECTIVES: To examine the association between occupational exposures and CT-measured patterns of disease in the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). METHODS: Participants underwent whole-lung multidetector helical CT at full inspiration and expiration. The association between occupational exposures (self-report of exposure to vapors, gas, dust, or fumes [VGDF] at the longest job) and CT metrics of emphysema (percentage of total voxels < -950 Hounsfield units at total lung capacity), large airways (wall area percent [WAP] and square-root wall area of a single hypothetical airway with an internal perimeter of 10 mm [Pi10]), and small airways (percent air trapping [percent total voxels < -856 Hounsfield units at residual volume] and parametric response mapping of functional small-airway abnormality [PRM fSAD]) were explored by multivariate linear regression, and for central airway measures by generalized estimating equations to account for multiple measurements per individual. Models were adjusted for age, sex, race, current smoking status, pack-years of smoking, body mass index, and site. Airway measurements were additionally adjusted for total lung volume. RESULTS: ) was 73 (27) % predicted. Forty-nine percent reported VGDF exposure. VGDF exposure was associated with higher emphysema (β = 1.17; 95% confidence interval [CI], 0.44-1.89), greater large-airway disease as measured by WAP (segmental β = 0.487 [95% CI, 0.320-0.654]; subsegmental β = 0.400 [95% CI, 0.275-0.527]) and Pi10 (β = 0.008; 95% CI, 0.002-0.014), and greater small-airway disease was measured by air trapping (β = 2.60; 95% CI, 1.11-4.09) and was nominally associated with an increase in PRM fSAD (β = 1.45; 95% CI, 0.31-2.60). These findings correspond to higher odds of percent emphysema, WAP, and air trapping above the 95th percentile of measurements in nonsmoking control subjects in individuals reporting VGDF exposure. CONCLUSIONS: In an analysis of SPIROMICS participants, we found that VGDF exposure in the longest job was associated with an increase in emphysema, and in large- and small-airway disease, as measured by quantitative CT imaging.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.395
Teacher spread0.340 · 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