Annual trends in follow-up visits for paediatricpediatric concussion in emergency departments and doctors’ offices in ontario, canada between 2003–2013
Bibliographic record
Abstract
Background Over the past ten years, ED and physician office visits for paediatric concussion have more than quadrupled. Current concussion management guidelines recommend follow-upand clearance by a physician prior to resumption of contact activities. However, compliance with recommended follow-up is not well documented in the literature. Objective To examine trends in follow-up visits in accordance with current recommended guidelines for children with concussion. Design Retrospective population-based study. Setting Children and youth presenting to emergency departments (EDs) and doctors’ offices with concussion over a 10-year time period (2003–2013) in Ontario, Canada. Outcome measures We examined the percentage of children and youth who were seen for follow-up visit post-concussion. Trends in the percent of children with a follow-up visit following an index visit to either a doctor’s office or an ED were reported. Main results The proportion of children and youth assessed for concussion follow-up (N=45,150) has increased significantly (p<0.0001). In 2003, only 1010 of 7170 (14.2%) patients with an index visit for concussion had follow-up assessment; in 2009, 2733 of 10,134 (27.0%) had a follow-up visit, and by 2013, 11,806 of 21,681 (54.5%) received follow-up care. Conclusions Despite increasing trends in the proportion of children being examined for concussion follow-up over a 10-year period, nearly half of all children with an index visit for concussion still do not receive follow-up assessment. This suggests that ongoing efforts to improve compliance with recommended guidelines will be important. Competing interests None.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".