Ascorbic Acid Deficiency Prevalence and Associated Cognitive Impairment in Alcohol Detoxification Inpatients: A Pilot Study
Bibliographic record
Abstract
Malnutrition has been reported in alcohol use disorder patients as having a possible influence on cognitive function. The aim of this study was to analyse the prevalence of ascorbic acid (AA) deficiency in inpatients admitted for alcohol detoxification and the associated factors, including cognitive impairment in the early period of abstinence. A retrospective chart review was conducted. The AA level was categorised into three groups: deficiency (AAD) (<2 mg/L), insufficiency (AAI) (2–5 mg/L) and normal level. The cognitive impairment was screened using the Montreal Cognitive Assessment (MoCA). Ninety-six patients were included (74 men; mean age 49.1 years (±11.5)). Twenty-seven AAD (28.1%) and twenty-two AAI (22.9%) were observed. In multivariate analysis, risk factors for AAD versus normal AA level were men (OR 17.8, 95%CI (1.63–194)), compensated cirrhosis (OR 9.35, 95%CI (1.60–54.6)) and street homelessness (OR 5.76, 95%CI (1.24–26.8) versus personal housing). The MoCA score was available for 53 patients (mean MoCA score: 25.7 (±3.3)). In multivariate analysis, the natural logarithm of AA (β = 1.18, p = 0.037) and sedative use disorder (β = −2.77, p = 0.046) were associated with the MoCA score. AAD and AAI are frequent in inpatients admitted for alcohol detoxification. A low level of AA was associated with cognitive impairment in the early period of abstinence.
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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 | 0.001 | 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".