Small Airways or Big Lungs? Investigating the Structural Components of Dysanapsis and Their Associations With Obstructive Lung Physiology at Rest and During Exercise
Bibliographic record
Abstract
Abstract Introduction: Dysanapsis refers to a developmental mismatch between airway tree caliber and lung size. Smaller airway tree caliber relative to total lung volume (TLV) assessed by computed tomography (CT) is associated with obstructive lung physiology, but whether this association is related to smaller airways, larger lungs or both, is uncertain. This study investigated the association of CT-assessed airway-to-lung ratio (ALR) and its structural components-airway tree caliber and TLV- with indices of obstructive lung physiology at rest and peak exercise. Methods: CanCOLD is a population-based cohort of adult non-smokers and smokers with or without COPD that underwent full-lung CT, spirometry, plethysmography, and symptom-limited incremental cardiopulmonary exercise testing to assess peak rate of oxygen uptake (V'O2peak), with inspiratory capacity (IC) maneuvers, and ratio of exertional dyspnea (Borg 0-10)-to-minute ventilation (V'E).Mean airway tree caliber, TLV, and ALR were quantified by CT (VIDA Diagnostics). Spirometric airflow obstruction severity was quantified using forced expiratory volume in 1-second (FEV1). ERS/ATS spirometry-defined dysanapsis required a pre-bronchodilator FEV1:forced vital capacity LLN. Dynamic hyperinflation (DH) required an IC decrement from rest-to-peak exercise>0.15L. Regression models adjusted for sex, age, age2, height and height2. Results: Among 161 non-smoking non-asthmatic participants with airflow obstruction (pre-bronchodilator FEV1/FVC<0.7 (mean±SD age: 69±10 years, 34% female), smaller ALR was associated with smaller airway tree caliber (p<0.001) and larger TLV (p<0.001, Table). When partitioning smaller ALR into its components, smaller airway tree caliber was associated with lower FEV1 (p=0.001), greater dyspnea:V'E (p=0.015), and more DH (p=0.016), but not lower V'O2peak (p=0.234); whereas, larger TLV was associated with higher FEV1 (p<0.001), and higher V'O2peak (p=0.002), but not DH (p=0.882) or dyspnea:V'E (p=0.079). ERS/ATS-defined spirometric dysanapsis was associated with the larger TLV (p=0.003) but not smaller airway tree caliber (p=0.264) etiotype of dysanapsis. Results tended to remain consistent when restricting to those with a post-bronchodilator FEV1/FVC<0.7 (n=114) or pre-bronchodilator FEV1/FVC
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".