Interventions for educating children who have attended the emergency room for asthma
Bibliographic record
Abstract
BACKGROUND: Asthma is one of the most common reasons for paediatric admissions to hospital, with substantial cost to the community. There is some evidence to suggest that many hospital admissions could be prevented with effective education about asthma and its management. OBJECTIVES: To conduct a systematic review of the literature in order to identify whether asthma education leads to improved health outcomes in children who have attended the emergency department for asthma. SEARCH STRATEGY: We searched the Cochrane Airways Group trials register, including Medline, Embase, and Cinahl databases, and reference lists of trials and review articles. SELECTION CRITERIA: Randomised controlled trials or controlled clinical trials of asthma education for children who had attended the emergency department for asthma, with or without hospitalisation, within the previous 12 months. DATA COLLECTION AND ANALYSIS: Two reviewers independently assessed trial quality and extracted data. Study authors were contacted for additional information. MAIN RESULTS: Eight trials involving 1407 patients were included, in all the education was provided by nurses or researchers. Compared to control (usual care or lower intensity education) education did not reduce subsequent emergency department (ED) visits [4 trials; relative risk (RR)= 0.87, 95% confidence interval (CI) 0.37 to 2.08], hospital admissions [5 trials; RR=0.74, 95% CI 0.38 to 1.46] and unscheduled doctor visits [5 trials; RR= 0.74, 95% CI 0.49 to 1.12). Each analysis showed evidence of heterogeneity among the studies (P<0.01). Subgroup analyses by the overall difference in scale of intervention between treatment and control groups (comprehensive programme versus information only) or the timing of the intervention/recruitment (early versus delayed) gave similar results to the main analysis and still revealed significant heterogeneity between trials. REVIEWER'S CONCLUSIONS: On the basis of the published trials, there is no firm evidence to support the use of asthma education for children who have attended the emergency department for asthma as a means of reducing subsequent ED visits, hospital admissions or unscheduled doctor visits. Some trials appeared to show clear evidence of benefit, but reasons for differences between these and the negative studies is not clear. More research is required
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".