History of Concussion and Risk of Serious Maternal Mental Illness: A Population-based Retrospective Cohort Study
Bibliographic record
Abstract
Objective: To evaluate the association between history of concussion and serious maternal mental illness. Methods: This population-based cohort study using administrative data from Ontario, Canada comprised women with a singleton livebirth in hospital between 2007-2017, with follow-up to 2021. Women with and without a pre-delivery history of concussion were compared on their risk for serious mental illness outcomes (emergency department visit for mental illness, hospital admission for mental illness, self-harm/suicide) after delivery, using Cox proportional hazards regression, with additional analyses stratified by mental illness history. Results: The cohort comprised 18,064 women with a pre-delivery history of concussion and 736,689 without. Concussion was associated with an elevated adjusted hazard of serious mental illness outcomes (aHR 1.25, 95% CI 1.20-1.31). The association was strongest in those with no mental illness history. Conclusion: A history of concussion was associated with increased risk of serious maternal mental illness, with implications for prevention and intervention.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".