Pulmonary Abnormalities and Carotid Atherosclerosis in Ex-Smokers without Airflow Limitation
Bibliographic record
Abstract
It is well-established that COPD patients have a burden of vascular disease that cannot be fully-explained by smoking history but the mechanistic links between atherosclerosis and pulmonary disease in COPD patients are not well-understood. Moreover, in ex-smokers without symptoms or other evidence of COPD, subclinical pulmonary and vascular disease, although potentially present, has not been described or evaluated. Hence our aim was to use sensitive three-dimensional (3D) pulmonary and carotid imaging to quantify pulmonary airway/parenchyma abnormalities and atherosclerosis in ex-smokers without airflow limitation or symptoms consistent with COPD. We evaluated 61 subjects without airflow limitation including 34 never- (72 ± 6 years) and 27 ex-smokers (73 ± 9 years), who provided written informed consent to spirometry, plethysmography, (3)He magnetic resonance imaging (MRI) and carotid ultrasound (US) and, for ex-smokers alone, thoracic X-ray computed tomography (CT). Ex-smokers had significantly greater (3)He ventilation defect percent (VDP = 7%, p = 0.001) and carotid total plaque volume (TPV = 250 mm(3), p = 0.002) than never-smokers, although there were no significant differences for spirometry or plethysmography, and CT airway and emphysema measurements were normal. There were univariate relationships for (3)He VDP with carotid intima media thickness (IMT, r = 0.42, p = 0.004), TPV (r = 0.41, p = 0.006) and vessel wall volume (VWV, r = 0.40, p = 0.007). Multivariate models that included age, BMI, FEV1, DLCO and VDP showed that only VDP significantly predicted IMT (β = 0.41, p = 0.001), VWV (β = 0.45, p = 0.003) and TPV (β = 0.38, p = 0.005). In summary, there was imaging evidence of mild airways disease and carotid plaque burden that were related and significantly greater in ex-smokers without airflow limitation than in never-smokers.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".