Neck Injury Comorbidity in Concussion-Related Emergency Department Visits: A Population-Based Study of Sex Differences Across the Life Span
Bibliographic record
Abstract
BACKGROUND: The cervical spine region can be especially vulnerable to concurrent injury in concussion, with research suggesting that females may be at greater risk due to their weaker and anatomically distinct necks. The main objective of our research was to study sex differences in the rate of neck injury comorbidity across the life span among patients with a concussion diagnosis in the emergency department (ED) setting, by cause of injury (motor vehicle collisions [MVC] and sports). MATERIALS AND METHODS: All patients with a first concussion-related ED visit between fiscal years 2002/2003 and 2011/2012 (inclusive) in Ontario were identified in population-based health administrative data using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Canada (ICD-10-CA) codes. Age-dependent odds ratios of comorbid neck injury for sex were estimated using polynomial multivariable logistic regression models, adjusting for sociodemographic characteristics. RESULTS: Females with a concussion had significantly higher odds of sustaining a comorbid neck injury between the ages of 5-49 years for all concussion-related ED visits, 15-49 years for MVC-related concussion ED visits, and 10-39 years for sports-related concussion ED visits, holding all other covariates in the model constant. CONCLUSIONS: These results support the consideration of increased screening for comorbid neck injuries, particularly for females, to allow for early intervention. Furthermore, the increased risk of comorbid neck injury in females with a concussion-related ED visit was age-dependent, with the interaction between sex and age following a nonlinear trend. As such, future studies on concussions should consider linear and nonlinear sex and age interactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".