Assessment of cognitive functions in patients with alcohol dependence disorder and its implications for primary care: A cross-sectional study
Bibliographic record
Abstract
Introduction: Alcohol dependence disorder (ADD) significantly impacts public health, society, and the economy. It is characterized by chronic alcohol use, withdrawal symptoms, and cognitive impairments, particularly involving frontal lobe dysfunction. The cognitive impairments, often underexplored, are particularly relevant in primary care settings, where early detection and intervention can greatly influence outcomes. This study investigates the cognitive effects of ADD using neurocognitive tests in inpatients at a government hospital in Central India, highlighting implications for family medicine and primary care management. Materials and Methods: This cross-sectional study assessed cognitive dysfunction and its link to alcohol dependence severity in 90 inpatients at a tertiary care hospital in Central India. Participants, aged 18-65 and meeting ICD-10 criteria for alcohol dependence, underwent cognitive evaluations using the Montreal Cognitive Assessment (MoCA), Frontal Assessment Battery (FAB), and Severity of Alcohol Dependence Questionnaire (SAD-Q). Results and Discussion: Patients with severe dependence exhibited significantly lower MoCA and FAB scores, with 72.2% scoring below the MoCA cutoff and 33.3% below the FAB cutoff. Negative correlations between SAD-Q and MoCA (-0.509) and FAB (-0.324) scores indicated that higher dependence severity was associated with greater cognitive decline. These findings highlight the importance of integrating cognitive assessments and rehabilitation into primary care practices for effective management of alcohol-related impairments. Conclusion: The study confirms severe cognitive impairments in ADD, particularly frontal executive functions. Routine cognitive evaluations in primary care settings can enable early detection and comprehensive management, improving patient outcomes and reducing the healthcare burden associated with ADD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".