Evaluation of the implementation and clinical effects of an intervention to improve medical follow-up and health outcomes for Aboriginal children hospitalised with chest infections
Bibliographic record
Abstract
Background: Aboriginal children hospitalised with acute lower respiratory infections (ALRIs) are at-risk of developing bronchiectasis, which can progress from untreated protracted bacterial bronchitis, often evidenced by a chronic (>4 weeks) wet cough following discharge. We aimed to facilitate follow-up for Aboriginal children hospitalised with ALRIs to provide optimal management and improve their respiratory health outcomes. Methods: We implemented an intervention to facilitate medical follow-up four weeks after hospital discharge from a paediatric hospital in Western Australia. The intervention included six-core components that focused on parents, hospital staff and hospital processes. Both health and implementation outcomes were measured for children grouped by three distinct temporal periods of recruitment: (i) nil-intervention, recruited after hospital admission; (ii) health-information only, received during recruitment at hospital admission, pre-intervention; (iii) post-intervention. The primary outcome was the cough-specific quality-of-life score (PC-QoL) in children with a chronic wet cough following discharge. Findings: Of the 214 patients that were recruited, 181 completed the study. Follow-up rates one-month post-discharge were higher in the post-intervention (50.7%) than the nil-intervention (13.6%) and health-information (17.1%) groups. PC-QoL in children with a chronic wet cough was also improved in the post-intervention group compared the health information and nil-intervention groups (difference in means between nil-intervention and post-intervention groups = 1.83, 95% CI: 0.75, 2.92, p = 0.002), aligning with an increase in the percentage who received evidence-based treatment, namely antibiotics at one-month post-discharge (57.9% versus 13.3%). Interpretation: Implementation of our co-designed intervention to facilitate effective and timely medical follow-up for Aboriginal children hospitalised with ALRIs improved their respiratory health outcomes. Funding: State, national grants and fellowships.
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How this classification was reachedexpand
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 | 0.006 | 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) | 0.000 | 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 teacher head, 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".