Clarifying SABA overuse: Translating Canadian Thoracic Society guidelines into clinical practice
Bibliographic record
Abstract
Patients with asthma frequently over rely on short-acting beta-agonists (SABA) to treat acute symptoms. This can adversely impact quality of life and increase the risk of exacerbations. SABA overuse is also associated with an increased risk of mortality. In their 2021 update on the diagnosis and management of mild asthma, the Canadian Thoracic Society (CTS) newly recommended that a combination inhaled corticosteroid (ICS) and long-acting beta-agonist, specifically budesonide/formoterol, may be used as-needed (PRN) as an alternative reliever to SABA. The CTS developed an algorithm as a guide for deciding for whom PRN budesonide/formoterol versus PRN SABA is appropriate as a reliever. While the CTS algorithm provides necessary and precise guidance, the somewhat complicated requirements for determining control and exacerbation risk may still end up leaving some patients at-risk of SABA overreliance. This communication simplifies the reliever decision algorithm developed by the CTS for application in daily practice. A 30-s evaluation of 2 simple questions related to reliever use can usually accurately assess if a patient's asthma is controlled: How many SABA canisters do you use a year AND how many times do you use SABA a week? If the patient indicates use of > 2 SABA canisters per year or > 2 administrations of SABA per week for any reason, the patient does not have controlled asthma and PRN SABA is not an appropriate treatment regimen. Similarly, for patients using PRN ICS/formoterol, more than 2 administrations per week indicates a clinical review and reevaluation of their management, including augmentation. An education process is essential to inform patients, caregivers, and healthcare providers that overuse of any reliever is not acceptable and is potentially harmful.
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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 | 0.076 | 0.287 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".