Assessment of Airway Distensibility by the Forced Oscillation Technique: Reproducible and Potentially Simplifiable
Bibliographic record
Abstract
). To become useful clinically, this method has to be reproducible and easy to perform. The series of breathing maneuvers required to measure distensibility would be greatly facilitated if the difficulty of breathing below functional residual capacity (FRC) could be precluded and the number of maneuvers could be reduced. The distensibility at lung volumes below FRC is also reduced by several confounders, suggesting that excluding data points below FRC should provide a better surrogate for airway remodeling. The objectives of this study were to investigate the reproducibility of airway distensibility measured by FOT and to assess whether the method could be simplified to increase feasibility. Distensibility was measured at three separate occasions in 13 healthy volunteers. At each visit, three deflationary maneuvers were performed, each consisting of tidal breathing from total lung capacity (TLC) to residual volume by slowly decreasing the end-expiratory volume on each subsequent breath. Distensibility was calculated by using either all data points from TLC to residual volume (RV) or only data points from TLC to FRC for either all three or only the first two deflationary maneuvers. Intra-class correlation coefficients (ICC) were used to assess reproducibility and Bland-Altman analyses were used to assess the level of agreement between the differently calculated values of distensibility. The results indicate that distensibility calculated using all data points is reproducible (ICC = 0.64). Using data points from TLC to FRC slightly improved reproducibility (ICC = 0.68) and increased distensibility by 19.4%, which was expected as distensibility above FRC should not be affected by confounders. Using only data points within the first two maneuvers did not affect reproducibility when tested between TLC and FRC (ICC = 0.66). We conclude that a valuable measure of airway distensibility could potentially be obtained with only two deflationary maneuvers that do not require breathing below FRC. This simplified method would increase feasibility without compromising reproducibility.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".