Home Management of Childhood Asthma Exacerbations
Bibliographic record
Abstract
INTRODUCTION: Effective home management of childhood asthma by caregivers requires education along with a written asthma action plan (AAP), which should outline clear instructions for treatment during exacerbations. However, a large number of asthma exacerbations continue to be managed in the emergency department (ED) and in hospitals, particularly in Canada. The objective of this study was to assess caregiver management of acute asthma at home following the 2015 Global Initiative for Asthma (GINA) guidelines and to identify factors that may be associated with deviations from these guidelines. METHODS: 122 caregivers of children, aged 3-17 years, with physician diagnosed asthma, completed a paper-based questionnaire. Correct caregiver management (defined according to the GINA guidelines) of acute asthma as well as their use of an AAP were assessed. RESULTS: Out of all caregivers, 74.6% incorrectly treated their child's asthma exacerbation in a home setting. Among those who used an AAP, we observed significantly more ED visits (0.9 ± 1.2 versus 0.5 ± 0.9, p = 0.04) and hospitalizations (0.2 ± 0.4 versus 0.0 ± 0.0, p = 0.02) when compared to non-AAP users in the past 1 year. CONCLUSIONS: Caregivers of children with asthma in Canada may still lack skills for proper home management of asthma exacerbations. We found a higher number of ED visits and hospitalizations in those using an AAP compared to those who did not use an AAP. These data suggest that current AAPs may not be sufficient for home asthma management.
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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 | 0.000 | 0.002 |
| 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) | 0.002 | 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".