ArticleTherapeutic advances in drug safety2025
Drug interactions in patients with alcohol use disorder: results from a real-world study on an addiction-specific ward.
Article in Therapeutic advances in drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Ethanol as a Modifier of Drug Toxicity in Humans: Pathways of Toxicity and Organ-Level Consequences.International journal of molecular sciences · 2026Review
- Lifestyle Habits and Comorbidities as Determinants of Quality of Life in Coronary Artery Disease: A Single-Center Prospective Study.Journal of clinical medicine · 2026Article
- Real-World Pharmacological Management of Alcohol Dependence in a Nepalese Rehabilitation Center: Prospective Cohort Study.Public health challenges · 2026Article
- Case Report: Four cases for cariprazine and alcohol use disorder.Frontiers in psychiatry · 2026Article
- Relevant Criteria for Improving Quality of Schizophrenia Spectrum Disorders Treatment: A Delphi Study.Healthcare (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The majority of patients with alcohol use disorder (AUD) regularly take medication. Alcohol interacts negatively with many commonly prescribed drugs. However, little is known about the characteristics and frequency of potential alcohol-medication and drug-drug interactions in patients with AUD. Objectives: This study aimed to determine the prevalence and characteristics of drug interactions in patients with AUD during withdrawal therapy on an addiction-specific ward. Design: Retrospective cohort study. Methods: Medication charts were analyzed and screened for potential alcohol-medication and drug-drug interactions. For the screening of potential alcohol-medication interactions, the drugs.com classification was utilized and potential drug-drug interactions were identified using the mediQ electronic interaction program. Results: In our study, almost two-thirds (66.3%; 1089/1643) of all patient cases were prescribed at least one drug that could potentially interact with alcohol. Four percent of all alcohol-medication interactions were classified as severe, 91.8% as moderate, and 4.3% as mild. Drug classes commonly involved in serious interactions with alcohol were analgesics and drugs used in diabetes. A total of 811 potential drug-drug interactions were identified, of which 3.3% were classified as severe and 96.5% as moderate. Psychoanaleptics (ATC N06) and psycholeptics (ATC N05) were most frequently associated with moderate to severe interactions. Conclusion: Potential alcohol-medication and drug-drug interactions are common in hospitalized patients with AUD. Improvements in the quality of prescribing should focus on the use of psychotropic drugs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.