Optimization of surgical evaluation algorithms for living donor liver transplantation
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Le résumé fourni par la source
BACKGROUND: Living donor liver transplantation (LDLT) is an established and endorsed alternative for deceased donor liver transplantation with better recipient outcomes. Nevertheless, while extensive evaluation of potential donors is crucial, evaluation algorithms differ between transplant centres and guidelines. METHODS: We included 317 individuals evaluated for LDLT between 07/2007-07/2022 in a retrospective analysis. The evaluation process was analysed to identify the key reasons for declining 77 potential donors. Additionally, 146 donors that underwent LDLT were analysed regarding risk factors for complications. RESULTS: The main reasons for donor refusal were liver volumetry (40.3 %) and metabolic factors including obesity or steatotic liver disease (20.8 %). Contrast-enhanced computed tomography (CECT) identified 63.6 % of all declined donors; CECT combined with assessment of medical history, physical examination, blood testing and ultrasonography, identified 87.0 % of declined potential donors. Associated with this selection, complication rates in donors were low (≥II in 17.1 %; none with ≥IVb). Notably, higher age was a risk factor for developing a complication ≥II after hemi-hepatectomy (p = 0.0373). CONCLUSIONS: We propose a progressive 4-step evaluation algorithm that begins with a very basic assessment combined with up-front CECT. This early phase of testing is expected to identify nearly 90 % of ineligible donors, thereby conserving critical resources, time and money, as well as minimising burden for potential donors. FUNDING: J.M.W. received funding by grant We-4675/6-1 from the Deutsche Forschungsgemeinschaft (DFG) in Bonn, Germany.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Optimization of surgical evaluation algorithms for living donor liver transplantation
- Date Crossref
- 01/03/2025
- Éditeur
- Elsevier BV
- Type
- journal-article
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