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Record W4391873496 · doi:10.1093/jcag/gwad061.288

A288 ALCOHOL RELAPSE AND ADVERSE OUTCOMES IN EARLY VERSUS ROUTINE LIVER TRANSPLANT FOR ALCOHOL-ASSOCIATED LIVER DISEASE IN THE PROVINCE OF BRITISH COLUMBIA

2024· article· en· W4391873496 on OpenAlexaffabout
Alexander Hemy, Andrew Fetz, Saumya Jayakumar

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAlcoholLiver diseaseMedicineAdverse effectLiver transplantationInternal medicineDiseaseAlcoholic liver diseaseTransplantationBiologyCirrhosis

Abstract

fetched live from OpenAlex

Abstract Background Liver transplant is a life-saving treatment for patients with alcohol-associated liver disease (ALD) resulting in decompensated cirrhosis or severe alcoholic hepatitis, significantly reducing mortality compared to supportive treatment. Despite its previous wide acceptance, there is a lack of strong evidence to justify a 6-month abstinence period. In 2019, BC Transplant policies were updated to allow liver transplant within 6-months of alcohol use in carefully selected patients with limited life expectancy and favorable multidisciplinary psychosocial assessment. Aims This study aims to assess alcohol relapse rates and adverse outcomes in patients who received an early liver transplant for ALD. Methods A retrospective chart review was performed on all adult patients who underwent liver transplant in the province of British Columbia between January 1, 2020, and December 31, 2022. Follow up data was extracted until May 31, 2023. Patients were included if they had alcohol documented as a contributing factor to their liver disease prior to transplant. Early transplant was defined as alcohol abstinence of 179-days or less and routine transplant as 180-days or more. Alcohol use and time to alcohol use were determined by patient history, random biochemical testing, and health-care utilization for an alcohol-associated complication. Graft dysfunction or rejection resulting in a change in therapeutic management, noncompliance determined by clinician documentation, rehospitalization, and death were recorded as adverse events. Results 278 patients underwent liver transplant during the study period. 81 patients were classified as alcohol-related, and 15 received early transplant. The mean follow-up period was 20.5 months. Early transplant recipients were more likely to be younger (median 45 vs. 58 years, p = 0.003) and have a higher MELD score at the time of transplant (median 37 vs. 17, p ampersand:003C 0.001). There was no significant difference in post-transplant alcohol relapse (13 vs. 15%, hazard ratio = 0.78, 95% CI [0.17, 3.55], p = 0.74). Graft dysfunction was increased in patients who received early transplant (53 vs. 25%, relative risk = 2.17, 95% CI [1.15, 4.10]). There was no significant difference between rates of noncompliance (0 vs. 9%), rehospitalization (53 vs. 56%), or death (0 vs. 2%). Conclusions Alcohol relapse is similar between early and routine liver transplant. Graft dysfunction is increased in early transplant, although other adverse events including medication noncompliance, rehospitalization, and death are not significant different. These results are favorable for the continued use of early liver transplant for ALD, providing an effective treatment for ALD and significantly reducing mortality in patients with a limited life expectancy. Funding Agencies None

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.237
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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