Neuropsychiatric Sequelae of Brain Injury is Significant, Regardless of Injury Severity
Bibliographic record
Abstract
ABSTRACT Objective Brain Injury is the leading cause of death and disability for Canadians under 40 years old. To better understand chronic neuropsychiatric sequelae within our local brain injury population, a retrospective chart review was carried out for all Acquired Brain Injury (ABI) physiatry clinic attendees between November 2014 and December 2021 (n=220) at our public rehabilitation hospital in Southeastern Ontario. Methods All cases were classified into four subgroups: multiple mild, mild, moderate-severe traumatic brain injury (TBI), and non-TBI. Comparison of depression, anxiety and concussion symptoms were made between subgroups using scores from the Patient Health Questionnaire-9 (PHQ-9), General Anxiety Disorder-7 (GAD-7) and Rivermead Post-Concussion Symptoms Questionnaire, (RPQ), self-reported physical symptoms, sleep disturbance and medications were also investigated. Analysis was repeated with six subgroups, created by further separating cases into moderate and severe TBI where possible. Results Almost all brain-injury subgroups had moderately severe depression, anxiety and post-concussion symptoms but multiple mild-TBI most frequently self-reported cognitive, neuropsychiatric and sleep disturbance issues. Moderately severe TBI most frequently self-reported physical complaints and sleep disturbance (60%, n=9), although none (0%, n=0) were prescribed sleep medication. Mild TBI (n=60) reported sleep disturbance less frequently (42%, n=25) than moderately severe TBI but 22% (n=13) were prescribed sleep medication. Conclusion All brain injury subgroups had similar levels of moderately severe neuropsychiatric sequelae; including depression, anxiety and post-concussion symptoms. Multiple mild-TBI had the most self-reported symptoms; while moderately severe TBI were most likely to report physical complaints and sleep disturbance.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".