A short period (1–2 h) of hypothermic oxygenated machine perfusion (HOPE) after static cold storage is safe and reduces ischemia‐reperfusion injury‐related complications after liver transplantation. Machine perfusion time is occasionally prolonged for logistical reasons, but it is unknown if prolonged HOPE is safe and compromises outcomes. We conducted a multicenter, observational cohort study of patients transplanted with a liver preserved by prolonged (≥4 h) HOPE. Postoperative biochemistry, complications, and survival were evaluated. The cohort included 93 recipients from 12 European transplant centers between 2014–2021. The most common reason to prolong HOPE was the lack of an available operating room to start the transplant procedure. Grafts underwent HOPE for a median (range) of 4:42 h (4:00–8:35 h) with a total preservation time of 10:50 h (5:50–20:50 h). Postoperative peak ALT was 675 IU/L (interquartile range 419–1378 IU/L). The incidence of postoperative complications was low, and 1‐year graft and patient survival were 94% and 88%, respectively. To conclude, good outcomes are achieved after transplantation of donor livers preserved with prolonged (median 4:42 h) HOPE, leading to a total preservation time of almost 21 h. These results suggest that simple, end‐ischemic HOPE may be utilized for safe extension of the preservation time to ease transplantation logistics.

Background: While 4 randomized controlled clinical trials confirmed the early benefits of hypothermic oxygenated machine perfusion (HOPE), high-level evidence regarding long-term clinical outcomes is lacking. The aim of this follow-up study from the HOPE-ECD-DBD trial was to compare long-term outcomes in patients who underwent liver transplantation using extended criteria donor allografts from donation after brain death (ECD-DBD), randomized to either HOPE or static cold storage (SCS). Methods: Between September 2017 and September 2020, recipients of liver transplantation from 4 European centers receiving extended criteria donor-donation after brain death allografts were randomly assigned to HOPE or SCS (1:1). Follow-up data were available for all patients. Analyzed endpoints included the incidence of late-onset complications (occurring later than 6 months and graded according to the Clavien-Dindo Classification and the Comprehensive Complication Index) and long-term graft survival and patient survival. Results: A total of 46 patients were randomized, 23 in both arms. The median follow-up was 48 months (95% CI: 41–55). After excluding early perioperative morbidity, a significant reduction in late-onset morbidity was observed in the HOPE group (median reduction of 23 Comprehensive Complication Index-points [p=0.003] and lower incidence of major complications [Clavien-Dindo ≥3, 43% vs. 85%, p=0.009]). Primary graft loss occurred in 13 patients (HOPE n=3 vs. SCS n=10), resulting in a significantly lower overall graft survival (p=0.029) and adverse 1-, 3-, and 5-year survival probabilities in the SCS group, which did not reach the level of significance (HOPE 0.913, 0.869, 0.869 vs. SCS 0.783, 0.606, 0.519, respectively). Conclusions: Our exploratory findings indicate that HOPE reduces late-onset morbidity and improves long-term graft survival providing clinical evidence to further support the broad implementation of HOPE in human liver transplantation.

(1) Background: Post-reperfusion syndrome (PRS) and electrolyte shifts (ES) represent considerable challenges during liver transplantation (LT) being associated with significant morbidity. We aimed to investigate the impact of hypothermic oxygenated machine perfusion (HOPE) on PRS and ES in LT. (2) Methods: In this retrospective study, we compared intraoperative parameters of 100 LTs, with 50 HOPE preconditioned liver grafts and 50 grafts stored in static cold storage (SCS). During reperfusion phase, prospectively registered serum parameters and vasopressor administration were analyzed. (3) Results: Twelve percent of patients developed PRS in the HOPE cohort vs. 42% in the SCS group (p = 0.0013). Total vasopressor demand in the first hour after reperfusion was lower after HOPE pretreatment, with reduced usage of norepinephrine (−26%; p = 0.122) and significant reduction of epinephrine consumption (−52%; p = 0.018). Serum potassium concentration dropped by a mean of 14.1% in transplantations after HOPE, compared to a slight decrease of 1% (p < 0.001) after SCS. The overall incidence of early allograft dysfunction (EAD) was reduced by 44% in the HOPE group (p = 0.04). (4) Conclusions: Pre-transplant graft preconditioning with HOPE results in higher hemodynamic stability during reperfusion and lower incidence of PRS and EAD. HOPE has the potential to mitigate ES by preventing hyperpotassemic complications that need to be addressed in LT with HOPE-pre-treated grafts.

Non-alcoholic fatty liver disease (NAFLD) is a spectrum of liver disease, ranging from simple steatosis to hepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Liver fibrosis, which portends a poor prognosis in NAFLD, is characterized by the excessive accumulation of extracellular matrix (ECM) proteins resulting from abnormal wound repair response and metabolic disorders. Various metabolic factors play crucial roles in the progression of NAFLD, including abnormal lipid, bile acid, and endotoxin metabolism, leading to chronic inflammation and hepatic stellate cell (HSC) activation. Autophagy is a conserved process within cells that removes unnecessary or dysfunctional components through a lysosome-dependent regulated mechanism. Accumulating evidence has shown the importance of autophagy in NAFLD and its close relation to NAFLD progression. Thus, regulation of autophagy appears to be beneficial in treating NAFLD and could become an important therapeutic target.

Hepatocellular Carcinoma (HCC) still is one of the most detrimental malignant diseases in the world. As two curative surgical therapies exist, the discussion whether to opt for liver resection (LR) or transplantation (LT) is ongoing, especially as novel techniques to improve outcome have emerged for both. The aim of the study was to investigate how the utilization and outcome of the respective modalities changed through time. We searched Medline and PubMed for relevant publications comparing LT and LR in HCC patients during the time period from 1990 to 2022, prior to March 31, 2023. A total of 63 studies involving 19,804 patients - of whom 8178 patients received a liver graft and 11,626 underwent partial hepatectomy - were included in this meta-analysis. LT is associated with significantly better 5-year overall survival (OS) (64.83%) and recurrence-free survival (RFS) (70.20%) than LR (OS: 50.83%, OR: 1.79, p < 0.001; RFS: 34.46%, OR: 5.32, p < 0.001). However, these differences are not as evident in short-term intervals. Older cohorts showed comparable disparities between the outcome of the respective modalities, as did newer cohorts after 2005. This might be due to the similar improvement in survival rates that were observed for both, LT (15-23%) and LR (12-20%) during the last 30 years. LT still outperforms LR in the therapy of HCC in terms of long-term survival rates. Yet, LR outcome has remarkably improved which is of major importance in reference to the well-known limitations that occur in LT.

Background: The “digital era” in the field of medicine is the new “here and now”. Artificial intelligence has entered many fields of medicine and is recently emerging in the field of organ transplantation. Solid organs remain a scarce resource. Being able to predict the outcome after liver transplantation promises to solve one of the long-standing problems within organ transplantation. What is the perfect donor recipient match? Within this work we developed and validated a novel deep-learning-based donor–recipient allocation system for liver transplantation. Method: In this study we used data collected from all liver transplant patients between 2004 and 2019 at the university transplantation centre in Munich. We aimed to design a transparent and interpretable deep learning framework to predict the outcome after liver transplantation. An individually designed neural network was developed to meet the unique requirements of transplantation data. The metrics used to determine the model quality and its level of performance are accuracy, cross-entropy loss, and F1 score as well as AUC score. Results: A total of 529 transplantations with a total of 1058 matching donor and recipient observations were added into the database. The combined prediction of all outcome parameters was 95.8% accurate (cross-entropy loss of 0.042). The prediction of death within the hospital was 94.3% accurate (cross-entropy loss of 0.057). The overall F1 score was 0.899 on average, whereas the overall AUC score was 0.940. Conclusion: With the achieved results, the network serves as a reliable tool to predict survival. It adds new insight into the potential of deep learning to assist medical decisions. Especially in the field of transplantation, an AUC Score of 94% is very valuable. This neuronal network is unique as it utilizes transparent and easily interpretable data to predict the outcome after liver transplantation. Further validation must be performed prior to utilization in a clinical context.