Subtle long-term cognitive effects of a single mild traumatic brain injury and the impact of a three-month aerobic exercise intervention
Bibliographic record
Abstract
BACKGROUND: Although there is a growing body of literature on the impact of multiple concussions on cognitive function with aging, less is known about the long-term impact of sustaining a single mild traumatic brain injury (mTBI). Additionally, very few interventions exist to treat mTBI patients and prevent a possible accelerated cognitive decline. This study aimed to: 1) examine the long-term effects of a single mTBI on cognition in patients aged between 55 and 70 years old; and 2) evaluate the cognitive effects of an aerobic exercise program for these patients. METHODS: Thirty-five participants (average age: 58.89, SD=4.14) were assessed using neuropsychological tests. Among them, 18 hadsustained a mTBI two to seven years earlier. Significant differences in information processing speed, executive function and visual memory were found between controls and mTBI patients. Sixteen of the mTBI patients then engaged in a 12-week physical exercise program. They were divided into equivalent groups: 1) aerobic training (cycle ergometers); or 2) stretching exercises. The participants' cardiopulmonary fitness (VO2max) was evaluated pre- and postintervention and neuropsychological tests were re-administered postintervention. RESULTS: Participants from the aerobic group significantly improved their fitness compared to the stretching group. However, no between-group difference was found on neuropsychological measures postintervention. CONCLUSIONS: In summary, this study shows long-term cognitive effects of mTBI in late adulthood patients. Moreover, the controlled, 12-week aerobic exercise program did not lead to cognitive improvements in our small mTBI sample. Lastly, future directions in optimizing mTBI intervention are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".