Association Between Burn Injury and Mental Illness among Burn Survivors: A Population-Based, Self-Matched, Longitudinal Cohort Study
Bibliographic record
Abstract
BACKGROUND: Mental health disorders are prevalent before and after burn injury. However, the impact of burn injury on risk of subsequent mental health disorders is unknown. STUDY DESIGN: We conducted a population-based, self-matched longitudinal cohort study using administrative data in Ontario, Canada between 2003 and 2011. All adults who survived to discharge after major burn injury were included, and all mental health-related emergency department visits were identified. Rate ratios (RRs) for mental health visits in the 3 years after burn, compared with the 3 years before, were estimated using negative binomial generalized estimating equations. RESULTS: Among 1,530 patients with major burn injury, mental health visits were common both before (141 per 1,000 person years) and after (154 per 1,000 person years) injury. Mental health visits were most common in the 12 weeks immediately preceding injury. No significant difference in the overall visit rate was observed after burn (RR 0.97; 95% CI 0.78 to 1.20), although among patients with less than 1 pre-injury visit, mental health visits tripled (RR 3.72; 95% CI 2.70 to 5.14). Self-harm emergencies increased 2-fold (RR 1.95; 95% CI 1.15 to 3.33). CONCLUSIONS: Mental health emergencies are prevalent among burn-injured patients. Although the overall rate of mental health visits is not increased after burn, the rate increases significantly among patients with one or fewer visits pre-injury. Self-harm risk increases significantly after burn injury, underscoring the need for screening and targeted interventions after discharge. An increased rate immediately before burn suggests an opportunity for injury prevention through mental healthcare.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".