Characterization of cognitive impairment and contributing factors in patients with substance use disorders: Influence of primary alcohol or cocaine use
Bibliographic record
Abstract
Substance use disorders (SUDs) are frequently associated with cognitive impairment, but the specific clinical and sociodemographic factors that contribute to these deficits remain insufficiently characterized. This study aimed to examine cognitive performance in a sample of treatment-seeking patients with SUDs and to identify predictors of impairment. Eighty abstinent outpatients were consecutively recruited and underwent clinical and neuropsychological evaluation. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), which evaluate attention, executive function, memory, language, visuoconstructional skills and orientation and the Complutense Verbal Learning Test (Test de Aprendizaje Verbal España-Complutense; TAVEC) to measure learning and memory. Overall, patients showed deterioration in several cognitive domains. Educational attainment and the duration of problematic substance use emerged as the strongest predictors of performance, particularly in attention, identification, and language. Age and abstinence length were also associated with selected domains, highlighting their role in the trajectory of cognitive recovery. Exploratory analyses suggested that the primary substance reported (alcohol or cocaine) may influence memory outcomes, although interpretation is limited by the high prevalence of polysubstance use. These findings emphasize the relevance of considering educational background, clinical history, and abstinence when assessing cognitive function in SUD populations, and suggest that strengthening cognitive reserve could mitigate neuropsychological deficits and improve treatment outcomes.
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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".