Bronchodilator Response in Patients with Persistent Allergic Asthma Could Not Predict Airway Hyperresponsiveness
Bibliographic record
Abstract
: Anticholinergics, or specific antimuscarinic agents, by inhibition of muscarinic receptors cause bronchodilatation, which might correlate with activation of these receptors by the muscarinic agonist methacholine. The aim of this study was to determine whether a positive bronchodilator response to the anticholinergic ipratropium bromide could predict airway hyperresponsiveness in patients with persistent allergic asthma. The study comprised 40 patients with mild and moderate persistent allergic asthma. Diagnosis was established by clinical and functional follow-up (skin-prick test, spirometry, bronchodilator tests with salbutamol and ipratropium bromide, and methacholine challenge testing). The bronchodilator response was positive to both bronchodilator drugs in all patients. After salbutamol inhalation, forced expiratory volume in 1 second (FEV1) increased by 18.39 +/- 6.18%, p < .01, whereas after ipratropium bromide, FEV1 increased by 19.14 +/- 6.74%, p < .01. The mean value of FEV1 decreased by 25.75 +/- 5.16%, p < .01 after methacholine (PC20 FEV1 [provocative concentration of methacholine that results in a 20% fall in FEV1] from 0.026 to 1.914 mg/mL). Using linear regression, between methacholine challenge testing and bronchodilator response to salbutamol, a positive, weak, and stastistically significant correlation for FEV1 was found (p < .05). Correlations between methacholine challenge testing and the bronchodilator response to ipratropium bromide were positive and weak but not statistically significant. The positive bronchodilator response to ipratropium bromide could not predict airway hyperresponsiveness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".