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Predicting and preventing alcohol relapse in alcohol-related liver disease.
British Journal of Nursing : BJN 2018 Februrary 23
BACKGROUND: despite a 450% increase in UK alcohol-related liver disease mortality over the past 30 years, little evidence-based guidance exists regarding preventing recidivism post-liver transplant for alcohol-related liver disease.
METHOD: a systematic literature review was conducted to identify demographic variables predictive of alcohol relapse and effective psychosocial interventions for alcohol-related liver disease patients post-liver transplant.
RESULTS: variables most significantly predictive of alcohol relapse post-transplant were-less than 12 months pre-liver transplant abstinence; patients with children; poor pre-liver transplant psychosomatic evaluation; non-compliance with post-liver transplant treatment plan; and patients with active insurance policies. Structured management was the most effective psychosocial intervention in preventing alcohol relapse.
CONCLUSION: findings should be interpreted cautiously, due to limited and poor-quality evidence. Rigorously designed further research of the psychosocial interventions targeting predictive demographic variables is recommended.
METHOD: a systematic literature review was conducted to identify demographic variables predictive of alcohol relapse and effective psychosocial interventions for alcohol-related liver disease patients post-liver transplant.
RESULTS: variables most significantly predictive of alcohol relapse post-transplant were-less than 12 months pre-liver transplant abstinence; patients with children; poor pre-liver transplant psychosomatic evaluation; non-compliance with post-liver transplant treatment plan; and patients with active insurance policies. Structured management was the most effective psychosocial intervention in preventing alcohol relapse.
CONCLUSION: findings should be interpreted cautiously, due to limited and poor-quality evidence. Rigorously designed further research of the psychosocial interventions targeting predictive demographic variables is recommended.
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