Late Breaking Abstract - Pharmacological and clinical management of severe asthma in 9 countries: An international survey of clinicians
Bibliographic record
Abstract
Objectives: Robust, system-level information on the diagnostic, prescribing and care practices in severe asthma (SA) is scarce. We aimed to: i) identify the available and relevant evidence on the clinical and pharmacological management of SA and ii) understand the opportunities for targeting new treatment pathways in SA. Methods: A framework of 44 indicators on SA diagnosis, treatment and care was built. An international web-survey of respiratory specialists captured information on national diagnostic and treatment pathways, and policies in SA care delivery. We performed a comparative analysis and benchmarking of performance in SA across 9 countries. Results: Twenty-six responses were received from Australia, Brazil, Canada, France, Germany, Italy, Japan, Spain and UK. Discrepancies existed across and within countries on whether specialist referral occurs before (69% of respondents) or after (31%) SA diagnosis. Referral times ranged from 1 to 24 months. Variation was more prominent in the diagnostic criteria and tests used, while only 30% of respondents reported using SA diagnostic pathway guidelines. Key reasons influencing biologic prescribing include the need for maintenance Oral Corticosteroid (OCS) therapy and/or excess of 2 OCS bursts in 12 months (96% and 70% of respondents respectively). Time of biologic initiation varied between 0-2 (15%), 3-6 (46%), 7-12 (30%) and more than 12 (9%) months after SA diagnosis respectively. Conclusion: Improved referral pathways and capacities in SA are needed. SA care could also benefit from measures to support increased understanding and incentivisation of guidelines in the prescribing of biologics and SA diagnostic criteria.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".