Emergency Department Revisits Among Youth Compared With Adults in Sudbury, Ontario, Canada
Bibliographic record
Abstract
OBJECTIVE: Our objective was to compare the association between age and emergency department revisits by comparing youth and adults in Sudbury, Ontario, Canada. METHODS: The study is a retrospective observational cohort study using administrative data from all patients presenting with substance use disorder at Health Sciences North from January 1, 2018 to August 31, 2023. Patients were placed in 3 groups: under 18, 18 to 24 years old, and over 25 years old. The outcome was 30-day revisits from index date and total time to first revisit from index date. RESULTS: Kaplan-Meier survival analysis revealed significant differences in emergency department revisit probabilities across age groups (log-rank P < 0.0001), with youth under 18 showing a higher risk of 30-day revisits [adjusted hazard ratio (HR) = 1.25, 95% CI: 1.10-1.44] compared with adults, while transitional-aged youth showed no significant difference (adjusted HR = 1.01, 95% CI: 0.89-1.24). In contrast, both youth (adjusted HR = 0.73, 95% CI: 0.63-0.86) and transitional-aged youth (adjusted HR = 0.79, 95% CI: 0.72-0.87) had significantly lower risks of revisits beyond 30 days compared with adults. CONCLUSIONS: Youth under 18 with substance use disorder had a higher risk of 30-day ED revisits compared with adults, but a lower risk of revisits beyond 30 days, highlighting the need for targeted short-term interventions in this population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".