Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model.

Background: Several scores have been developed to stratify the risk of graft loss in controlled donation after circulatory death (cDCD). However, their performance is unsatisfactory in the Spanish population, where most cDCD livers are recovered using normothermic regional perfusion (NRP). Consequently, we explored the role of different machine learning-based classifiers as predictive models for graft survival.

Liver transplantation for primary and secondary liver tumors: Patient-level meta-analyses compared to UNOS conventional indications.

Background And Aims: Liver transplant (LT) for transplant oncology (TO) indications is being slowly adopted worldwide and has been recommended to be incorporated cautiously due to concerns about mid-long-term survival and its impact on the waiting list.

Approach And Results: We conducted 4 systematic reviews of all series on TO indications (intrahepatic cholangiocarcinoma and perihilar cholangiocarcinoma [phCC]) and liver metastases from neuroendocrine tumors (NETs) and colorectal cancer (CRLM) and compared them using patient-level meta-analyses to data obtained from the United Network for Organ Sharing (UNOS) database considering conventional daily-practice indications. Secondary analyses were done for specific selection criteria (Mayo-like protocols for phCC, SECA-2 for CRLM, and Milan criteria for NET).

Safety and feasibility of pure laparoscopic living donor right hepatectomy.

Pure laparoscopic living-donor right hepatectomy (PLDRH) has emerged as a significant advancement in liver transplantation, offering reduced donor morbidity and improved recovery times. However, PLDRH is still performed in only a limited number of centers. This retrospective study reports on the outcomes of 215 living donors who underwent PLDRH at Asan Medical Center in Seoul, Korea between November 2014 and December 2021.