On the progression of airway mucus-occlusions over 12 years in ex-smokers with and without COPD
Bibliographic record
Abstract
Background: Airway mucus is common in ex-smokers with COPD (Okajima; Chest 2020) and predictive of all-cause mortality (Diaz; JAMA 2023). Changes in mucus-plugs over time is not well-understood in patients with ex-smokers with mild COPD, hence we investigated the evolution of mucus-occlusions over a 12-year period in ex-smokers with and without COPD. Methods & Results: As part of the TINCAN cohort study, ex-smokers with (n=5) and without COPD (n=12) consented to spirometry, St. George's Respiratory Questionnaire (SGRQ), CT and MRI at baseline, 3- and 12-years later. CT mucus-score was estimated. At the 3-year visit there was significantly worse FEV1/FVC% (P=.02), MRI ventilation defect percent (VDP; P=.001) and emphysema (CT RA950; P=.02) but no change in mucus-score/count or FEV1. At the 12-year visit there was significantly worse FEV1/FVC% (P=.008), 6MWD (P=.003), VDP (P=.005) and RA950 (P<.001) but no change in mucus-score/count or FEV1. While total mucus burden increased (n=41+40= 81 plugs) over 12 years, this was mainly due to a single GOLD2 patient with 26 new plugs. In 9 of 17 participants, mucus-count and score were diminished or unchanged. Conclusions: In mild COPD and ex-smokers without COPD, mucus-score and mucus-count did not significantly change over a period of 12-years, which suggests limited influence of airway occlusions in the worsening FEV1/FVC, VDP in mildly obstructed lung disease. erj;66/suppl_69/PA3621/F1 F1 F1
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".