Mild traumatic brain injury: The effect of age at trauma onset on brain structure integrity
Bibliographic record
Abstract
Mounting evidence suggests that mild traumatic brain injuries (mTBI) have long-term effects that interact with the aging process to precipitate cognitive decline. This line of research predicts that early exposure to brain trauma is particularly detrimental to long-term brain integrity. However, a second line of research into the effects of age at trauma onset predict that older brains are more vulnerable to the effects of mTBI than younger brains. We sought to determine whether patients who sustain a mTBI earlier in life fare better than patients who sustain a mTBI at an older age. We conducted a multi-cohort, case-control study, with participants randomly sampled from a population of patients with a history of mTBI. We recruited two cohorts of aging participants (N = 74, mean [SD] = 61.16 [6.41]) matched in age and education levels that differed in only one respect: age at mTBI onset. One cohort sustained their concussion in their early twenties (24.60 [6.34] y/o), the other in their early sixties (61.05 [4.90] y/o). Each mTBI cohort had its own matched control group. Participants underwent high-resolution MRI at 3 Tesla for T1 and diffusion-weighted images (DWI) acquisition. Images were processed and analyzed using Deformation-Based Morphometry and DWI Tract-Based Spatial Statistics to identify group differences in a 2 × 2 ANOVA design. Results showed a significant interaction on DWI measures of white matter integrity indicating larger anomalies in participants who sustained a mTBI at a younger age (F1,70, P < .05, FDR corrected). These findings suggest that mTBI initiates a lifelong neurodegeneration process that outweighs the risks associated with sustaining a mTBI at an older age. Implications are important for young athletes' populations exposed to the risk of mTBI in the practice of their sports and for retired athletes aging with a history of concussions sustained at a younger age.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".