Differences in regional air trapping in current smokers with normal spirometry
Bibliographic record
Abstract
We investigated regional air trapping on computed tomography in current smokers with normal spirometry. It was hypothesised that presence of regional air trapping may indicate a specific manifestation of smoking-related changes. 40 current smokers, 40 patients with chronic obstructive pulmonary disease (COPD), and 40 healthy never- smokers underwent computed tomography scans. Regional air trapping was assessed on end-expiratory scans and emphysema, micronodules and bronchial wall thickening on inspiratory scans. The ratio of expiratory and inspiratory mean lung attenuation (E/I) was calculated as a measure of static (fixed) air trapping. Regional air trapping was present in 63% of current smokers, in 45% of never smokers and in 8% of COPD patients (p<0.001). Current smokers with and without regional air trapping had E/I ratio of 0.81 and 0.91, respectively (p<0.001). Forced expiratory volume in 1 s (FEV1) was significantly higher and emphysema less frequent in current smokers with regional air trapping. Current smokers with regional air trapping had higher FEV1and less emphysema on computed tomography. In contrast, current smokers without regional air trapping resembled COPD. Our results highlight heterogeneity among smokers with normal spirometry and may contribute to early detection of smoking related structural changes in the lungs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".