AASLD AST Practice Guideline on adult liver transplantation: Candidate evaluation
Abstract
Background and aims: Liver transplant is a specialized treatment for a spectrum of indications that use a scarce resource. Transplant is guided by principles of justice, equity, and benefit, with a constant conflict between competing interests. Organs are a national resource with a goal of equitable distribution across sites. An AASLD guideline for the evaluation and selection of appropriate candidates for transplant has been available since 2005.
Methods: A multidisciplinary writing group of liver transplant experts and a librarian convened over 24 months. The writing group reviewed the literature, generated guideline recommendations, and rated the level of evidence for each recommendation based on the Oxford Center for Evidence-Based Medicine. The group categorized the strength of recommendations based on the level of evidence, risk-benefit ratio, and patient preferences.
Conclusions: Liver transplant is a lifesaving procedure that should be offered to selected patients with clear indications and a reasonable prospect of benefit. The evaluation is designed to identify those in need, to outline hurdles to a successful outcome, and to develop an effective transplant plan. The goal of this document is to provide a template for this process.
Read the paper
Related studies
- Effectiveness of Bisphosphonates and Denosumab on Risk of Vertebral Fractures in Prostate Cancer Patients Under Androgen Deprivation Therapies: A Real-World Prospective Study
- Osteoporosis-related fractures after spinal cord injury: a retrospective study from Brazil
- Serum 25-hydroxyvitamin D, parathyroid hormone, and mortality in older men
- Lack of Association between Vitamin D Insufficiency and Cardiovascular or Fracture Risk: A UK Biobank Study
- Muscle strength and body composition are clinical indicators of osteoporosis
- Incidence of bone protection and associated fragility injuries in patients with proximal femur fractures
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.