Pharmacotherapy of Alcohol Use Disorders and Concurrent Psychiatric Disorders: A Review
Bibliographic record
Abstract
Alcohol use disorders (AUDs) are among the most prevalent psychiatric disorders. Epidemiologic studies have shown a high prevalence of concurrent psychiatric disorders among people with AUDs as well as a higher prevalence of AUDs in people with psychiatric disorders than in the general population. Though psychiatric patients with concurrent AUDs are at increased risk for morbidity and mortality, they are commonly undertreated for their alcohol-related disorders. The efficacy of pharmacotherapy for AUDs is well documented. Our paper reviews the common pharmacotherapies available for AUDs and focuses on the available research regarding treatment of AUDs among psychiatric populations with mood, anxiety, and psychotic disorders. Despite the high prevalence of concurrent AUDs and psychiatric disorders, very limited information has been collected using a randomized controlled trial design targeting those concurrent conditions. Several prevalent psychiatric disorders have not been studied when co-occurring with AUDs. Further research of pharmacological treatments for concurrent AUDs and psychiatric diagnoses is urgently needed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".