Return to the Emergency Department Within 3 Months Following Pediatric Acute Concussion
Bibliographic record
Abstract
OBJECTIVE: To determine the proportion of concussed children returning to the emergency department (ED) for a concussion-related reason within 3 months of initial presentation and to determine which clinical composite score (5P or Post-Concussion Symptom Inventory) best predicts a return visit. SETTING, DESIGN, AND PARTICIPANTS: We combined a secondary analysis of data from the prospectively collected 5P study with a retrospective medical record review of children aged 5 to 18 years who returned to the Children's Hospital of Eastern Ontario (CHEO) ED for a concussion-related reason within 3 months of an acutely diagnosed concussion. Among 770 eligible participants, 632 children (median age: 11.8 [interquartile range (IQR), 9.0-14.5] years; 58.9% male) were included in the study. MAIN MEASURES: The primary outcome was the number of patients who returned to CHEO ED for a concussion-related reason within 3 months of an acute concussion diagnosed at CHEO ED. The secondary outcome was number of patients who returned within 14 days. RESULTS: Forty-seven children (7.4%; 95% confidence interval [CI]: 5.6-9.7) had a concussion-related return to the ED within 3 months, the majority of which occurred in the first 14 days (29/47; 61.7%; 95% CI: 47.4-74.2). History of migraines (21.3% vs 9.7%; P = .03) were more common in those with a return visit. Headache was the most frequently reported symptom (87.2%) on revisit. Females aged 13 to 18 years had the highest return rate (survival rate: 85.8% [95% CI: 79.8-92.3]) compared with males and younger age groups. In multivariable Cox hazards regression modeling, inclusion of risk scores improved prognostication (pseudo R2 = 8%). The difference in pseudo R2 between 5P and Post-Concussion Symptom Inventory is small. CONCLUSION: Most children and adolescents do not return to the ED following an acute concussion. Female youth with medium to high 5P scores at the index concussion visit may benefit from early referral to interdisciplinary specialty concussion care to guide treatment in anticipation of prolonged symptoms. By identifying these risk factors at the initial ED visit, healthcare and patient burden may be reduced.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".