Dose omission to shorten methacholine challenge testing: clinical consequences of the use of a 10% fall in FEV1 threshold
Bibliographic record
Abstract
In methacholine challenge testing (MCT), skipping a methacholine dose is suggested if FEV 1 falls by < 5%. Using a larger threshold may further shorten test duration, but data supporting this hypothesis is lacking. We evaluated the safety and consequences of using a 10% FEV 1 fall as threshold to skip the next dose of methacholine in patients undergoing MCT. We reviewed MCTs performed in our center in 2017–2018. A ≤ 10% FEV 1 fall allowed the omission of the next methacholine dose. Patients of interest were those in which a dose was skipped after a previous FEV 1 fall outside the usual range (5–10%, termed “skip 5–10% ”). Adverse events [AE; mild: > 1 nebulized salbutamol dose (2.5 mg) to reach basal FEV 1 , palpitations; severe: hypoxemia and/or need for medical attention or intervention] were compared in the skip 5–10% group and others. Regression analysis was used to identify predictors of AE. 208 MCTs were analysed (135 males, age 52 ± 15 years). Skip 5–10% occurred 111 times in 90 tests. Prevalence of AE was 5% and all were mild. Patients who developed AEs had lower FEV 1 , FVC and FEV 1 /FVC ratio, and higher lung volume values (all p < 0.05), but similar prevalence of skip 5–10% (36 vs. 44%, p = 0.64). Overall, MCTs in which at least one skip 5–10% occurred had a lower mean number of doses (3.1 ± 0.6 vs. 3.5 ± 1.3 doses, p = 0.007). Baseline residual volume was independently related to the development of AEs (OR 1.05, 95% CI 1.01–1.10, p = 0.01), but not the presence of a skip 5–10% , even when the skipped dose directly led to the reaching of PC 20 (OR 5.40, 95% CI 0.73–39.22, p = 0.10). Omitting a methacholine dose based on a ≤ 10% fall in FEV 1 occurs frequently and has the potential to shorten test duration. AE are rare, but patients with worse baseline lung function and gas trapping are at increased risk of mild side effects.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| 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".