Oscillometry with or without spirometry for methacholine testing
Bibliographic record
Abstract
Abstract Oscillometry is proposed as a complementary technique to spirometry for methacholine testing. Yet, before being prescribed in conjunction with spirometry, the extent by which the oscillometric readouts are influenced by spirometric maneuvers, especially the deep inspirations, will need to be determined. Herein, 16 very mild‐to‐mild asthmatics underwent two methacholine challenges on separate visits. On visit 1, the response was tracked by both oscillometry and spirometry, and the challenge was stopped at the provocative concentration causing a decline in forced expiratory volume in 1 s of at least 20%. The same concentration regimen was used on visit 2, but the response was tracked by oscillometry only. The results demonstrated that, except for resistance at 19 Hz, the changes in all oscillometric readouts were greater in the challenge without spirometry (p ≤ 0.02). The maximal change in reactance at 5 Hz (Xrs5), for example, was on average 75.8% greater in the challenge without than with spirometry (p = 0.025). The number of doubling concentrations of methacholine that was needed to reach an equivalent change in Xrs5 was also lower without concomitant spirometry (p = 0.0078). It is concluded that the deep inspirations that are required in spirometry to monitor the response to methacholine decrease the oscillometric response.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".