Alcohol use disorder with comorbid anxiety disorder: a case report and focused literature review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Alcohol use disorder (AUD) and anxiety disorders (AnxD) are prevalent health concerns in clinical practice which frequently co-occur (AUD-AnxD) and compound one another. Concurrent AUD-AnxD poses a challenge for clinical management as approaches to treatment of one disorder may be ineffective or potentially counterproductive for the other disorder. CASE PRESENTATION: We present the case of a middle-aged man with anxiety disorder, AUD, chronic pain, and gamma-hydroxybutyrate use in context of tapering prescribed benzodiazepines who experienced severe alcohol withdrawal episodes during a complicated course of repeated inpatient withdrawal management. After medical stabilization, the patient found significant improvement in symptoms and no return to alcohol use with a regimen of naltrexone targeting his AUD, gabapentin targeting both his AUD and AnxD, and engagement with integrated psychotherapy, Alcoholics Anonymous, and addictions medicine follow-up. CONCLUSION: Proper recognition and interventions for AUD and AnxD, ideally with overlapping efficacy, can benefit individuals with comorbid AUD-AnxD. Gabapentin, tobacco cessation, and integrated psychotherapy have preliminary evidence of synergistic effects in AUD-AnxD. Meta-analysis evidence does not support serotoninergic medications (e.g. selective serotonin reuptake inhibitors) which are commonly prescribed in AnxD and mood disorders as their use has not been associated with improved outcomes for AUD-AnxD. Additionally, several double-blind placebo-controlled randomized trials have suggested that serotonergic medications may worsen alcohol-related outcomes in some individuals with AUD. Areas for future investigation are highlighted.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it