Clinical Values of Serum Uric Acid Levels in the Occurrence of Cognitive Impairment in AlcoholDependent Patients
Bibliographic record
Abstract
Objective: Studies have confirmed that uric acid is involved in the regulation of cognitive function. This study aimed to investigate the expression of serum uric acid in alcohol-dependent patients and evaluate its clinical diagnostic value for cognitive impairment. Methods: Blood sample was collected for assessment of serum uric acid levels. Montreal Cognitive Assessment Scale scores were obtained to assess cognitive function. Anxiety and depression scores on the Symptom Check List 90 scale were used to assess mental health status. The alcohol-dependent patients were divided into non-cognitive impairment and cognitive impairment groups according to Montreal Cognitive Assessment Scale score, and the serum uric acid levels of these groups were analyzed. The receiver operating characteristic curve evaluated the diagnostic value of serum uric acid in cognitive impairment patients. Pearson correlation coefficient evaluated the correlation between uric acid and Montreal Cognitive Assessment Scale score, anxiety score, and depression score. Multivariate logistic regression analyzed the association between each index and cognitive impairment in patients. Results: < .05). Conclusion: The abnormal expression of uric acid has a high diagnostic accuracy for distinguishing cognitive impairment from non-cognitive impairment.
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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 | 0.002 |
| 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".