Is Age Associated With the Severity of Post–Mild Traumatic Brain Injury Symptoms?
Bibliographic record
Abstract
BACKGROUND: Mild traumatic brain injury (mTBI) is a significant public health concern. Research has shown that mTBI is associated with persistent physical, cognitive, and behavioural symptoms, leading to significant direct and indirect medical costs. Our objective was to determine if age impacts the type and severity of post-mTBI symptoms experienced. METHODS: Retrospective analysis of prospectively collected data at a level 1 tertiary care outpatient head injury clinic. Participants (N=167) were patients seen at the clinic following an mTBI. The Rivermead Post-Concussion Symptoms Questionnaire was used to assess symptom severity. RESULTS: In our sample, the mean age was 44±16 years with 51% males. Compared with other age groups, patients >66 years of age were significantly more likely to report an mTBI between 6 AM to 12 PM (69%). Middle-aged patients (36-55 years) were more likely to report higher severity of certain post-mTBI symptoms (headache, nausea and vomiting, irritability, poor concentration, sleep disturbance, blurry vision, light sensitivity, and taking longer to think) compared with patients >66 years of age. CONCLUSIONS: In general, middle-aged patients reported higher severity of post-mTBI symptoms compared with the oldest patients. Thus, there was a significant association between age and the severity of specific mTBI symptoms, which highlights the need for targeted management. Additional research is needed to understand the mechanisms that could be contributing to the higher symptom severity experienced by the middle-aged group.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".