Pediatric Secondary Transfer Percentages: A Retrospective Observational Study
Bibliographic record
Abstract
INTRODUCTION: Certain adult conditions treated by paramedics, such as myocardial infarction or stroke, have better outcomes if transported to a specialty centre, bypassing local generalist facilities when necessary. Little evidence exists to inform guidelines to identify pediatric patients who would benefit from direct transport to a pediatric centre. This study describes the characteristics of children brought to community emergency departments (ED) who subsequently required transfer to pediatric specialty care. METHODS: A retrospective observational cohort study was performed in a metropolitan area with one tertiary pediatric specialty centre and four community EDs. The patient care record database was queried for patients under 16 years old transported by paramedics to a community ED during a five-year period. Secondary transfer to the pediatric specialty centre within 24 hours was identified. The primary outcome was percentage of transfers to specialty care. Descriptive statistics were used to characterize the whole group as well as stratified by age category, chief complaint and Canadian Triage Acuity Scale (CTAS). RESULTS: A total of 872 pediatric patients were transported to community EDs with 95 (10.9%) requiring secondary transfer to the pediatric specialty centre. CTAS 1 and 2 were associated with increased secondary transfer (p<0.001). There were also differences in transfer proportion by chief complaint. There was no association between age or gender and transfer to pediatric specialty care. CONCLUSIONS: This retrospective study shows an association between acuity and certain chief complaints and percentage of secondary transfer to pediatric specialty 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".