Background.: Adoption of machine perfusion (MP) technology has rapidly expanded in liver transplantation without real-world data on utilization and outcomes, which are critical to understand the appropriate application of MP technology. Methods.: The Organ Procurement and Transplant Network/Standard Transplant Analysis and Research database was used to identify all deceased donor livers procured with intent for transplant between October 27, 2015 (date of first recorded MP) and June 30, 2023 (n = 67 795). Liver allografts were cohorted by donation after brain death (DBD; n = 59 957) or circulatory death (DCD; n = 7873) and analyzed by static cold storage (SCS) or MP preservation method. Donor demographics, organ utilization, and graft survival were evaluated. Results.: By 2023, 12.5% of all livers and 37.2% of DCD livers underwent MP preservation (82.6% normothermic, 6.7% hypothermic, and 10.8% other/unknown). Compared with SCS, MP liver donors were older (DBD: 48 versus 40 y [P < 0.001]; DCD: 43 versus 38 y [P < 0.001]) with higher body mass index (DBD: 28.8 versus 26.9 kg/m² [P < 0.001]; DCD: 27.7 versus 26.9 kg/m² [P = 0.004]). Donor livers had similar levels of macrosteatosis (median 5%). Graft utilization was higher for MP than SCS after DBD (96.4% versus 93.0%, P < 0.001) and DCD (91.4% versus 70.3%, P < 0.001) donation. Graft survival was similar between MP and SCS livers from DBD donors (P = 0.516), whereas MP-preserved grafts had superior survival from DCD donors at 1 and 3 y posttransplant (P = 0.013 and 0.037). Patient survival was similar across all groups at 3 y (P = 0.322). Conclusions.: The use of MP in liver transplantation increased rates of liver utilization and improved graft survival after DCD. Further monitoring of MP outcomes is required to understand long-term benefits.

Background: Serum AFP-L3%, AFP, and DCP are useful biomarkers for HCC detection, but their utility in assessing treatment response remains unknown. We aim to evaluate the accuracy of a biomarker model in the detection of posttreatment viable tumors. Methods: For model derivation, recipients with HCC undergoing liver transplant from 2018 to 2022 who had biomarkers collected within 3 months before transplant were included. We developed a generalized linear model for detecting posttreatment viable tumors with the 3 biomarkers as covariates, which we termed the “LAD Score.” An independent cohort of 117 patients with HCC was used for external validation. Results: Among 205 recipients of transplant, 70.2% had evidence of viable tumor on explant. The median LAD score was higher among patients with viable versus nonviable tumors (1.06 vs. 0.465, p < 0.001). The LAD score had a sensitivity of 55.6% and a specificity of 85.1% at the cutoff of 0.927, which was more accurate than imaging for detecting posttreatment viable tumors (AUROC 0.736 vs. 0.643, respectively; p = 0.045). The superior performance of the LAD score over imaging is primarily driven by its greater accuracy in detecting tumors <2 cm in diameter (AUROC of the LAD score 0.721 vs. imaging 0.595, p = 0.02). In the validation data set, the LAD score had an AUROC of 0.832 (95% CI: 0.753, 0.911) with a sensitivity of 72.5% and a specificity of 89.4% at the cutoff of 0.927. Conclusions: Our findings suggest the utility of LAD score in treatment response assessment after locoregional therapy for HCC, particularly in detecting small tumors. A larger prospective study is in progress to validate its accuracy and evaluate its performance in recurrence monitoring.

Ischemia-reperfusion injury commonly causes delayed graft function (DGF) after kidney transplantation and is associated with poorer graft function and lower allograft survival. Activation of the lectin complement pathway is one mediator of ischemia-reperfusion injury. In this randomized double-blind placebo-controlled pilot study, we tested whether preimplantation intragraft administration of C1 esterase inhibitor (C1INH, a lectin/classical pathway inhibitor) into deceased donor organs improves graft function and/or reduces DGF. Forty patients were randomized 1:1 to receive allografts treated with 500 units C1INH or placebo (normal saline) into the transplant renal artery during back-table preparation. We observed no effect on DGF, but recipients of C1INH-treated allografts showed higher estimated glomerular filtration rate than recipients of placebo at 6 months (C1INH median: 55 mL/min/1.73 m², interquartile range [IQR]: 42-63; placebo median: 39 mL/min/1.73 m², IQR: 34-50; P = .02) and 30 months (C1INH median: 54 mL/min/1.73 m², IQR: 47-66; placebo median: 43 mL/min/1.73 m², IQR 38-51; P = .03), with no differences in adverse events. Analysis of postreperfusion biopsies showed positive intra-arterial C1INH staining and reduced C4d staining in C1INH-treated grafts compared with controls. Posttransplant serum mannose-binding lectin and classical pathway activity and bradykinin levels did not differ between study arms. We conclude that this treatment strategy improves allograft function independent of DGF, likely via local intragraft complement inhibition. Clinical trial registration number: NCT04696146.

Croome and Daneshmand offer a thoughtful piece on the complexities of joint DCD heart and liver procurements. The authors have provided important suggestions which, with greater experience, can be expanded and systematized to establish clear, standardized protocols.

Background: Non-ideal donors provide acceptable allografts and may expand the donor pool. This study evaluates donor utilization across solid organs over 15-years in the United States. Methods: We analyzed the OPTN STAR database to identify potential donors across three donor eras: 2005–2009, 2010–2014, and 2015–2019. Donors were analyzed by a composite Donor Utilization Score (DUS), comprised of donor age and comorbidities. Outcomes of interest were overall and organ-specific donor utilization. Descriptive analyses and multivariable logistic regression modeling were performed. p-values < 0.01 considered significant. Results: Of 132,465 donors, 32,710 (24.7%) were identified as non-ideal donors (NID), based on a DUS ≥ 3. Compared to ideal donors (ID), NID were older (median 56 years, IQR 51–64 years vs. 35 years, 22–48 years, p < 0.001) and more frequently female (44.3% vs. 39.1%, p < 0.001), Black (22.1% vs. 14.6%, p < 0.001) and obese (60.7% vs. 19.6%, p < 0.001). The likelihood of overall DBD utilization from NID increased from Era 1 to Era 2 (OR 1.227, 95% CI 1.123–1.341, p < 0.001) and Era 3 (OR 1.504, 1.376–1.643, p < 0.001), while DCD donor utilization in NID was not statistically different across Eras. Compared to Era 1, the likelihood of DBD utilization from NID for kidney transplantation was lower in Era 2 (OR 0.882, 0.822–0.946) and Era 3 (OR 0.938, 0.876–1.004, p = 0.002). The likelihood of NID utilization increased in Era 3 compared to Era 1 for livers (OR 1.511, 1.411–1.618, p < 0.001), hearts (OR 1.623, 1.415–1.862, p < 0.001), and lungs (OR 2.251, 2.011–2.520, p < 0.001). Conclusions: Using a universal definition of NID across organs, NID donor utilization is increasing; however, use of DUS may improve resource utilization in identifying donors at highest likelihood for multi-organ donation.