Delineating the Effects of Alcohol Use on Cognition in Individuals With Neurocognitive Disorders
Bibliographic record
Abstract
Excessive alcohol use is a recognized modifiable risk factor for the development of dementia; however, the neuropsychological profile of cognitive impairment seen with alcohol use is heterogeneous. We studied cognitive characteristics associated with alcohol use in a "real-world" memory clinic cohort of patients with neurocognitive disorders. We used the Toronto Dementia Research Alliance memory clinic research database to generate an age, sex, and education matched sample of individuals with alcohol-related cognitive impairment (ARCI group; n=51) and twice as many individuals without such history (Comparator group; n=102). We compared cognitive domain and subdomain Toronto Cognitive Assessment scores between the two groups using linear regression.while controlling for age, sex, education, concurrent psychiatric disorders, global cognition, and traumatic brain injury. =.018). Our study suggests that ARCI results in specific deficits involving cognitive control during delayed recall task. This may help advance development of markers to delineate ARCI from other causes of cognitive impairment. Future work may test these findings in larger, well-characterized samples.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".