Cognitive reserve among elderly patients with traumatic brain injury
Bibliographic record
Abstract
BACKGROUND: Traumatic brain injury (TBI) is damage to the brain caused by an external mechanical force, leading to temporary or permanent impairment of brain function and associated with deficits in information processing speed, attention, memory, speech, visuospatial perception, and executive functions. Cognitive reserve is defined as inherited or acquired mental skills that provide higher cognitive adaptability and protect against the effects of brain aging, diseases, or injuries; however, it remains insufficiently studied in patients with TBI. AIM: The work aimed to examine the characteristics of cognitive reserve in elderly patients with traumatic brain injury. METHODS: Fifty-seven individuals aged 60–74 years with TBI and 60 patients of the same age without brain injury were examined. Cognitive reserve was assessed using the Cognitive Reserve Index questionnaire, which includes questions on education, occupational activity, and leisure time. Mental status was evaluated using the MoCA and MMSE scales. RESULTS: Comparison between elderly TBI patients and age-matched controls showed that the overall cognitive reserve index was higher in the control group. Among 60–74-year-old TBI patients, the cognitive reserve index was significantly higher in those with mild TBI and lowest in those with severe TBI (p 0.001). Positive correlations were found between “driving a car” (r = 0.315, p 0.05) and “use of modern technologies” (r = 0.300, p 0.05) in elderly patients without trauma. At the same time, these characteristics were negatively correlated with moderate TBI (r = −0.273, p 0.05 and r = −0.404, p 0.05, respectively). CONCLUSION: Cognitive reserve makes a substantial contribution to the clinical profile of TBI in older age. The results demonstrated that cognitive reserve is associated with TBI severity, with more severe injuries corresponding to a lower cognitive reserve index.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".