Clinical profile and comorbidity of traumatic brain injury among younger and older men and women: a brief research notes
Bibliographic record
Abstract
OBJECTIVE: Comorbid disorders influence the course and outcomes of rehabilitation following traumatic brain injury (TBI), yet sex- and age-related disparities in the frequency distribution of these disorders remain poorly understood. We aimed to describe comorbid disorders by the International Classification of Diseases in patients with TBI undergoing inpatient rehabilitation in Ontario, Canada over a 3-year period, by sex and age, and discuss their potential impact on rehabilitation outcomes. RESULTS: The percentage of TBI patients with one or more comorbid disorder is higher among older (≥65 years) men and women than among those who are younger or middle-aged (<65 years). Among younger and middle-aged patients, multiple injuries and trauma, mental health conditions, and nervous system disorders were the most prevalent comorbidities. In older patients, circulatory, endocrine, nutritional, metabolic, and immune disorders were the most prevalent comorbidities. Our results suggest that a multisystem view of rehabilitation of men and women with TBI across age categories is needed to reflect the complex clinical profile of TBI patients undergoing rehabilitation.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".