Comparison of impulse oscillometry indices and FEV1 during methacholine challenge and bronchodilation tests
Bibliographic record
Abstract
Background: Spirometry is the most used technique in methacholine challenge test (MCT) and bronchodilation test (BDT), however impulse oscillometry (IOS) could also be used as an alternative method. Objective: To demonstrate that IOS can be a reliable alternative to spirometry in MCT and BDT. Methods: Study included 20 subjects with suspected asthma (12 males, 8 females, mean age 41.5 ± 15.1). All participants underwent MCT using dosimeter (ProvoX, Ganshorn, Germany). FEV1 (Spiroscout, Ganshorn, Germany) and IOS (Tremoflo C-100, Thorasys, Canada) parameters – airway resistance at 5 Hz (R5), 20 Hz (R20), 5–20 Hz (R5-20), reactance at 5 Hz (X5), reactance area at 5 Hz (AX5) were recorded at the beginning of the test and after each methacholine dose. In subjects for whom MCT was positive, bronchodilation using salbutamol was performed and FEV1 and IOS indices were re-recorded. Results: At baseline and after the last methacholine dose a significant correlation was observed between FEV1 and all IOS indices (p < 0.05), except R5-20 at baseline. ΔMCTFEV1 (difference between baseline and after the last methacholine dose) significantly correlated with ΔMCTR5, ΔMCTX5 and ΔMCTAX5 in all subjects (p < 0.05). Six subjects (30%) had a positive MCT for whom ΔBDTFEV1 (difference between the value before and after BDT) significantly correlated with ΔBDTX5 and ΔBDTR5-20 (p < 0.05). Conclusion: IOS may be a valuable alternative to spirometry in MCT and BDT. Our findings show that the most suitable IOS indices for MCT assessment are R5, X5 and AX5, and for BDT – X5 and R5-20.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".