Late Breaking Abstract - Dysanapsis is a major determinant of airflow limitation among older adults
Bibliographic record
Abstract
<b>Background</b> Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation. Dysanapsis refers to the disproportionate scaling of airway dimensions to lung volume. We sought to quantify the relationship between dysanapsis and airflow limitation in a population-based sample. <b>Methods</b> The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study performed spirometry, lung CT, and assessed traditional COPD risk factors including primary and secondary smoke exposures, prior asthma diagnosis, occupational exposures, and the MESA Air Study quantified long-term individual-level air pollution exposure. Airflow limitation was quantified as FEV1/FVC, and COPD as a post-bronchodilator FEV1/FVC<0.70. Airway tree dimensions and lung volume were quantified from CT (VIDA). Dysanapsis for each airway was quantified as the deviation of observed airway lumen diameter from that predicted by lung volume and traditional COPD risk factors. Adjusted R2 quantified the variation in FEV1/FVC explained by dysanapsis vs traditional COPD risk factors (bootstrap). <b>Results</b> Among 2,523 participants (age 69±9 yr, 47% male, 39% white, 48% non-smoker, FEV1/FVC 0.74±0.08), the mean dysanapsis was 0.0±10.5% of predicted airway lumen diameter. Dysanapsis explained 17.7% of FEV1/FVC, whereas traditional COPD risk factors explained 9.6% of FEV1/FVC (p<0.0001). Dysanapsis had a greater area under the receiver-operator characteristic curve for COPD when compared with traditional COPD risk factors (p<0.0001). Results adjusted for age, height, gender, and race were similar. <b>Conclusion</b> In a population-based sample of older adults, dysanapsis explains more airflow limitation than traditional COPD risk factors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".