Recommendations from a Canadian Delphi consensus study on best practice for optimal referral and appropriate management of severe asthma
Bibliographic record
Abstract
BACKGROUND: In Canada, severe asthma affects an estimated 5-10% of people with asthma and is associated with frequent exacerbations, poor symptom control and significant morbidity from the disease itself, as well as the high dose inhaled, and systemic steroids used to treat it. Significant heterogeneity exists in service structure and patient access to severe asthma care, including access to biologic treatments. There appears to be over-reliance on short-acting beta agonists and frequent oral corticosteroid use, two indicators of uncontrolled asthma which can indicate undiagnosed or suboptimally treated severe asthma. The objective of this modified Delphi consensus project was to define standards of care for severe asthma in Canada, in areas where the evidence is lacking through patient and healthcare professional consensus, to complement forthcoming guidelines. METHODS: The steering group of asthma experts identified 43 statements formed from eight key themes. An online 4-point Likert scale questionnaire was sent to healthcare professionals working in asthma across Canada to assess agreement (consensus) with these statements. Consensus was defined as high if ≥ 75% and very high if ≥ 90% of respondents agreed with a statement. RESULTS: A total of 150 responses were received from HCPs including certified respiratory educators, respirologists, allergists, general practitioners/family physicians, nurses, pharmacists, and respiratory therapists. Consensus amongst respondents was very high in 37 (86%) statements, high in 4 (9%) statements and was not achieved in 2 (5%) statements. Based on the consensus scores, ten key recommendations were proposed. These focus on referrals from primary and secondary care, accessing specialist asthma services, homecare provision for severe asthma patients and outcome measures. CONCLUSIONS: Implementation of these recommendations across the severe asthma care pathway in Canada has the potential to improve outcomes for patients through earlier detection of undiagnosed severe asthma, reduction in time to severe asthma diagnosis, and initiation of advanced phenotype specific therapies.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".