Missing airways, ventilation defects and conductive airway physiology in asthma.
Bibliographic record
Abstract
Aim: In asthma patients, excessive luminal narrowing or mucus plugs potentially generate a perturbation in bronchial asymmetry. Based on realistic models of asthma patients’ bronchial trees we hypothesized that in asthma, CT-derived total airway count (TAC) and hyperpolarized gas magnetic resonance imaging (MRI) derived ventilation defect percent (VDP) should be primarily related to the multiple breath washout (MBW) measure of conductive ventilation heterogeneity, irrespective of degree of acinar ventilation heterogeneity. Methods: We investigated associations between MBW derived indices of conductive and acinar ventilation heterogeneity (Sacin*, Scond*) and TAC and VDP, both post-bronchodilation. Results: Twenty-one asthma patients (52±12[SD]yrs) of widely varying degrees of asthma severity (GINA1-3 n=4, GINA4 n=3, GINA5 n=14), with mean[±SD] FEV1: 83 [+20]%pred, Sacin*: 188 [+146]%pred, Scond*: 197 [+106]%pred. Besides univariate relationships of TAC and VDP with Scond* (Figure 1), principal components analysis revealed a strong relationship between imaging-derived TAC and MBW-derived Scond*, but not Sacin*. In addition, VDP was also independently associated with Scond*. erj;64/suppl_68/PA3383/F1 F1 F1 Discussion: This imaging structure-function study is consistent with prior patient-specific modeling of ventilation distribution in asthma linking the asymmetry of bronchial airway ramification to the MBW measure of convective ventilation heterogeneity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".