B – 48 Understanding the relationship between cardiovascular health factors and neuropsychological test performance after traumatic brain injury
Bibliographic record
Abstract
Abstract Objective The Life’s Essential (LE8) score is a set of eight factors contributing to cardiovascular health including blood pressure, blood glucose, blood lipids, body mass index, diet, physical activity, smoking, and sleep. Research has suggested that higher LE8 scores correlates to fewer dementia events and better neurocognitive health. We explored the association of LE8 score and neuropsychological test performance in a sample of traumatic brain injury (TBI) patients. Method 28 outpatients (M age = 46.5, SD = 15.9; 60.7% females) with mild or moderate TBI underwent neuropsychological assessment in an academic medical setting after a sustaining a TBI. Data were analyzed using correlation and linear regression. The Verbal Comprehension Index (VCI), Perceptual Reasoning Index (PRI), Working Memory Index (WMI) and Full-Scale IQ (FSIQ) from the Wechsler Adult Intelligence Scale – (WAIS-IV), as well as Montreal Cognitive Assessment (MoCA) were examined. Results The mean LE8 score was 5.45 (SD = 1.26). LE8 was significantly correlated with the WMI (r = .48, p = .027), FSIQ (r = .50, p = .031) and MoCA (r = .76, p = .030). The association between WMI and LE8 remained significant after adjusting for age and sex. VCI and PRI were not associated with LE8. Conclusion This study provides novel insights into various health factors that may influence recovery after TBI. Higher LE8 scores appear to relate to higher scores in overall cognition but also working memory. Our research suggests that modifiable factors may be associated with cognitive performance, which demonstrates promising avenues for intervention in TBI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".