Effect of alcohol-dependence on cognitive performance in middle-aged men: Preliminary results
Bibliographic record
Abstract
Objectives: The understanding of the relationship between alcohol-related neuropathology, cognitive impairment, and various factors such as alcohol consumption, thiamine levels, and age vulnerability is still poorly understood. Therefore, this study aims to examine the effect of alcohol dependence on cognitive performance in middle-aged men with psycho-biochemical evidence. Materials and Methods: A cross-sectional pilot study with a comparison group including 82 right-handed participants with and without alcohol dependence (n = 41 each). Alcohol dependence was diagnosed clinically by the International Classification of Disease Tenth Edition along with the use of alcohol use disorder identification test (AUDIT) and cognitive screening tests, that is, the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE). The serum levels of thiamine (Vitamin B1) were determined using an enzyme-linked immunosorbent assay. Results: The MoCA scores, MMSE scores, and serum thiamine levels were significantly low for alcohol-dependent men (1509.43 ± 898.63 pmol/L) versus non-alcohol-dependent men (1862.81 ± 741.30 pmol/L; P = 0.021). The cognitive sub-domains including orientation, execution, calculation, visuoconstructional skills, and recall functions were also significantly (P < 0.05) affected for the alcohol-dependent patients when compared to non-alcohol-dependent men. Serum thiamine levels showed a positive (P < 0.05) correlation with MoCA scores whereas serum thiamine levels showed a significant (P < 0.05) negative correlation with AUDIT scores. Conclusion: Based on the significant positive association between serum thiamine levels with MoCA scores; therefore, both may be used as a screening tool for the early detection of cognitive impairment in patients with alcohol dependence.
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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".