S113 The effect of small airways disease and emphysema on the association between smoking and lung function, and bronchodilator response
Bibliographic record
Abstract
<h3>Introduction and objectives</h3> The airflow limitation of COPD results from small airway disease and emphysema. These phenotypes are likely to have independent genetic risk factors. It is not known if the heterogeneity of COPD accounts for the relatively weak association between pack-years smoked and forced expiratory volume in 1 s (FEV<sub>1</sub>) seen within smoking populations, or bronchodilator response (BDR). This study aimed to assess the effect of these phenotypes on the association between smoking and FEV<sub>1</sub> and on BDR. <h3>Method</h3> The international COPD genetics network is a multi-centre study aimed at identifying genes that predispose to COPD, in which high resolution computed tomography (HRCT) was used to quantify components of the COPD phenotype: (i) emphysema detected by radiologists (RE), (ii) emphysema assessed as per cent low-attenuation area (%LAA) and (iii) airway wall thickness (AWT) for airways with an internal perimeter of 10 mm (Pi10), 20 mm (Pi20), and average per cent wall area (WA%). They were then assessed for their effect on the association between smoking and lung function (FEV<sub>1</sub>% predicted (FEV<sub>1</sub>%)), and on BDR. <h3>Results</h3> RE data were available for 1159 individuals, 745 had complete data for Pi10, Pi20, AWT% and %LAA. The association between pack-years smoked and FEV<sub>1</sub>% was greater in those without (r=−0.41), compared to those with, RE (r=−0.12, p<0.001 for difference in effect). AWT and RE correlated with FEV<sub>1</sub>% but had different relationships with smoking; AWT was positively associated with pack-years but there was no relationship between RE severity and pack-years smoked. RE, %LAA and AWT made independent contributions to FEV<sub>1</sub>%. Post-bronchodilator increase in FEV<sub>1</sub> was inversely associated with severity of RE (Abstract S113 Table 1), even after adjustment for pre-bronchodilator FEV<sub>1</sub> (p<0.01). BDR was also inversely associated with %LAA (p=0.02, and p≤0.05 adjusted for baseline FEV<sub>1</sub>). <h3>Conclusion</h3> The AWT component of COPD, but not the severity of RE, increases with pack-years smoked, and the association between pack-years and FEV1% is greatest in those with an airway predominant phenotype. This suggests different gene-smoking interactions between phenotypes. RE and %LAA independently contribute to FEV1% and therefore measure different components of emphysema, however both were inversely associated with BDR.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".