Bibliographic record
Abstract
Background: Bronchial challenge testing (BCT) measures airway hyperresponsiveness; asthma guidelines recommend using BCT when symptoms manifest despite normal spirometry. Improper application of these guidelines commonly results in the misdiagnosis of asthma. Yet, statistics concerning BCT remain largely obscure. The current paper addresses this gap and explores how various health variables may elucidate adherence to asthma guidelines and patterns of BCT across Canadian provinces. Methods: Using the Access to Information Act, medical financial claims for BCT (or equivalent procedures) were requested from each of the Canadian provinces and territories. Based on the available information (from provinces only), correlations between frequency of BCT claims and medical demographics (e.g., prevalence of respirologists, health expenditures) are reported. Results: Controlling for population or for people with asthma, physicians from Qubec claim four times more BCT per year than those in other provinces; physicians from Alberta close to eight-fold fewer. The number of respirologists per capita and BCT per capita correlated moderately, r(132) = 0.582, p < 0.001, [95% CI 0.421, 0.716]. Excluding "outliers" (i.e., British Columbia, Alberta, and Saskatchewan) greatly strengthened this correlation, r(87) = 0.930, p < 0.001, [95% CI 0.883, 0.958]. Discussion: These findings demonstrate that provinces vary in their use of BCT. This result seems to stem, at least in part, from differences in the prevalence of respirologists. Interestingly, geographic region appears to wield a strong influence; in the correlation between number of tests and number of respirologists, physicians from Western provinces (i.e., Alberta, Saskatchewan, and British Columbia) administered fewer tests than their Eastern colleagues. Given the association between inadequate application of BCT and misdiagnosis of asthma, physicians should pay special attention to the Canadian guidelines when considering an asthma diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".