Effect of a clinical pathway on the hospitalisation rates of children with asthma: a prospective study
Bibliographic record
Abstract
AIM: To determine the effect of implementing a clinical pathway, using evidence-based clinical practice guidelines, for the emergency care of children and adolescents with asthma. METHODS: A prospective, before-after, controlled trial was conducted, which included patients aged 1-18 years who had acute exacerbations of asthma treated in a tertiary care paediatric emergency department. Data were collected for identical 2-month seasonal periods before and after implementation of the clinical pathway to determine hospitalisation rate and other outcomes. For 2 weeks after emergency visits, the rate at which patients returned to emergency care for worsening asthma was evaluated. A multidisciplinary panel, using national guidelines and a systematic review, developed the pathway. RESULTS: 267 patients were studied. The rate of hospitalisation was significantly lower in the post-implementation group (10/74; 13.5%) than in the pre-implementation control group (53/193; 27.5%; p = 0.02; number needed to treat 7.1). All reduction in hospitalisation occurred in children with moderate to severe asthma exacerbation. After implementation of the clinical pathway, the rate of administration of oral corticosteroids to patients with moderate or severe exacerbations increased from 71% to 92% (p = 0.01), and significantly more patients received beta2-agonists in the first hour (p = 0.02). No significant change in relapse to acute care occurred within 2 weeks (p = 0.19). CONCLUSIONS: An evidence-based clinical pathway for children and adolescents with moderate to severe exacerbations of acute asthma markedly decreases their rate of hospitalisation without increased return to emergency care.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".