A review of behavioral alcohol interventions for transplant candidates and recipients with alcohol-related liver disease
Bibliographic record
Abstract
Alcohol-related liver disease (ALD) is a common indication for liver transplantation. Reflecting growing consensus that early transplant (ie, prior to sustained abstinence) can be a viable option for acute alcoholic hepatitis, access to liver transplantation for ALD patients has increased. Prevention of alcohol relapse is critical to pretransplant stabilization and posttransplant survival. Behavioral interventions are a fundamental component of alcohol use disorder treatment, but have rarely been studied in the transplant context. This scoping review summarizes published reports of behavioral and psychosocial alcohol interventions conducted with ALD patients who were liver transplant candidates and/or recipients. A structured review identified 11 eligible reports (3 original research studies, 8 descriptive papers). Intervention characteristics and clinical outcomes were summarized. Interventions varied significantly in orientation, content, delivery format, and timing/duration. Observational findings illustrate the importance of situating alcohol interventions within a multidisciplinary treatment context, and suggest the potential efficacy of cognitive-behavioral and motivational enhancement interventions. However, given extremely limited research evaluating behavioral alcohol interventions among ALD patients, the efficacy of behavioral interventions for pre- and posttransplant alcohol relapse remains to be established.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".