Bronchodilator Responsiveness and Reported Respiratory Symptoms in an Adult Population
Bibliographic record
Abstract
BACKGROUND: The relationship between patient-reported symptoms and objective measures of lung function is poorly understood. AIM: To determine the association between responsiveness to bronchodilator and respiratory symptoms in random population samples. METHODS: 4669 people aged 40 years and older from 8 sites in Canada completed interviewer-administered respiratory questionnaires and performed spirometry before and after administration of 200 ug of inhaled salbutamol. The effect of anthropometric variables, smoking exposure and doctor-diagnosed asthma (DDA) on bronchodilator responsiveness in forced expiratory volume in 1 second (FEV1) and in forced vital capacity (FVC) were evaluated. Multiple logistic regression was used to test for association between quintiles of increasing changes in FEV1 and in FVC after bronchodilator and several respiratory symptoms. RESULTS: Determinants of bronchodilator change in FEV1 and FVC included age, DDA, smoking, respiratory drug use and female gender [p<0.005 to p<0.0001 ]. In subjects without doctor-diagnosed asthma or COPD, bronchodilator response in FEV1 was associated with wheezing [p for trend<0.0001], while bronchodilator response for FVC was associated with breathlessness. [p for trend <0.0001]. CONCLUSIONS: Bronchodilator responsiveness in FEV1 or FVC are associated with different respiratory symptoms in the community. Both flow and volume bronchodilator responses are useful parameters which together can be predictive of both wheezing and breathlessness in the general population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".