Factors associated with follow-up care after pediatric concussion: A longitudinal population-based study in Alberta, Canada
Bibliographic record
Abstract
Background: Concussion is a common injury in children and adolescents. Current best practice guidelines indicate that recovery should be supervised through recurrent follow-up visits. A more detailed understanding of the system-level and individual factors that are associated with follow-up care is a critical step towards increasing evidence-based practice. The objective of this study was to identify predisposing, enabling, and need-based factors associated with follow-up care after pediatric concussion. Materials and methods: A retrospective population-based cohort study was conducted using linked, province-wide administrative health data for all patients <18 years of age with a diagnosis of concussion, other specified injuries of the head, unspecified injury of head, or post-concussion syndrome (PCS) between April 1, 2004 and March 31, 2018 in Alberta, Canada. The association between predisposing, enabling, and need-based factors and the receipt of follow-up care within a defined episode of care (EOC) was analyzed using logistic regression models for the entire cohort and for EOC that began with a concussion diagnosis. Predisposing factors included age and sex. Enabling factors included the community type of patient residence, area-based socioeconomic status (SES), and visit year. Need-based factors included where the EOC began (outpatient vs. emergency settings) and history of previous concussion-related EOC. Results: = 25,461). Males and adolescents were more likely to receive follow-up care. Follow-up was less likely among patients who lived in remote communities or in areas of lower SES, while EOCs beginning in 2011 or later were more likely to involve follow-up care. Patients whose EOC began in outpatient settings, had more than one EOC, or a diagnosis of concussion were more likely to receive follow-up care. Conclusion: Follow-up care for pediatric concussion has increased over time and is associated with patient age and sex, history of concussion-related EOC, where a patient lives (community type and area-based SES), and when and where the index visit occurs. A better understanding of which children are more likely to receive follow-up care, as well as how and when they do, is an important step in aligning practice with follow-up guidelines.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".