Global Initiative for Asthma Strategy 2021
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Global Initiative for Asthma (GINA) Strategy Report provides clinicians with an annually updated evidence‐based strategy for asthma management and prevention, which can be adapted for local circumstances (e.g., medication availability). This article summarizes key recommendations from GINA 2021, and the evidence underpinning recent changes. GINA recommends that asthma in adults and adolescents should not be treated solely with short‐acting β 2 ‐agonist (SABA), because of the risks of SABA‐only treatment and SABA overuse, and evidence for benefit of inhaled corticosteroids (ICS). Large trials show that as‐needed combination ICS–formoterol reduces severe exacerbations by ≥60% in mild asthma compared with SABA alone, with similar exacerbation, symptom, lung function, and inflammatory outcomes as daily ICS plus as‐needed SABA. Key changes in GINA 2021 include division of the treatment figure for adults and adolescents into two tracks. Track 1 (preferred) has low‐dose ICS–formoterol as the reliever at all steps: as needed only in Steps 1–2 (mild asthma), and with daily maintenance ICS–formoterol (maintenance‐and‐reliever therapy, “MART”) in Steps 3–5. Track 2 (alternative) has as‐needed SABA across all steps, plus regular ICS (Step 2) or ICS–long‐acting β 2 ‐agonist (Steps 3–5). For adults with moderate‐to‐severe asthma, GINA makes additional recommendations in Step 5 for add‐on long‐acting muscarinic antagonists and azithromycin, with add‐on biologic therapies for severe asthma. For children 6–11 years, new treatment options are added at Steps 3–4. Across all age groups and levels of severity, regular personalized assessment, treatment of modifiable risk factors, self‐management education, skills training, appropriate medication adjustment, and review remain essential to optimize asthma outcomes.
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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) | 0.001 | 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 it