International Differences in Asthma Guidelines for Children
Bibliographic record
Abstract
BACKGROUND: Over the last decade, a number of clinical practice guidelines that include guidance for the management of pediatric asthma have been introduced. The consistency across pediatric asthma guidelines is unknown and the emphasis on establishing asthma control may vary. The objective of this paper was to depict the evolution of guidelines for pediatric asthma and to compare current international guidelines in terms of their organization, presentation of evidence and consideration of children, with special emphasis on definitions of asthma control and severity. METHODS: A systematic search to identify asthma guidelines was conducted, and guidelines were searched for pediatric terms. The approaches used by guidelines to define assessments of asthma severity and control were compared between the United States, the Global Initiative for Asthma, Canada, the United Kingdom and Australia. RESULTS: Pediatric considerations in the management of asthma have been integrated into the various guidelines to different degrees and through varied strategies. There were differences in the conceptual and operational approach used to assess asthma which emphasized either asthma severity or control. CONCLUSIONS: It will be important for future guidelines to clearly define whether the primary assessment parameter is asthma severity or control. Delineating the guideline development process and supporting evidence may improve transparency, consistency and guideline adherence.
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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 | 0.021 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".