40 research outputs found

    Is the liver kinetic growth rate in ALPPS unprecedented when compared with PVE and living donor liver transplant? A multicentre analysis

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    AbstractBackgroundThe clinical perspective on hepatic growth is limited. The goal of the present study was to compare hepatic hypertrophy and the kinetic growth rate(KGR) in patients after the ALPPS (Associating Liver Partition with Portal Vein Ligation for Staged Hepatectomy) procedure, portal vein embolization (PVE) and living donor liver transplantation.MethodsVolumetry and KGR of the future liver remnant (FLR) were compared from (15) patients undergoing ALPPS, (53) patients undergoing PVE, (90) recipients of living donor liver grafts and (93) donors of living donor liver grafts.ResultsThe degree of hypertrophy was significantly greater after ALPPS (84.3 Ā± 7.8%) than after PVE (36.0 Ā± 27.2%) (P < 0.001). The KGR was also significantly greater for ALPPS [32.7 Ā± 13.6 cubic centimetres (cc)/day] (10.8 Ā± 4.5%/day) compared with PVE (4.4 Ā± 3.2 cc/day) (0.98 Ā± 0.75%/day) (P < 0.001). The FLR of living donor donors had the greatest degree of hypertrophy (107.5 Ā± 39.2%) and was greater than after ALPPS (P = 0.02), PVE (P < 0.001) and in living donorā€recipient grafts (P < 0.001). KGR (cc/day) was greater in FLR of living donor donors compared with both ALPPS (P < 0.001) and PVE (P < 0.001). The KGR in patients undergoing ALPPS and living donor liver transplantation had a linear relationship with the size of FLR.ConclusionFLR hypertrophy and KGR were greater after ALPPS than PVE. However, the degree of hypertrophy after ALPPS is not unprecedented, as KGR in the FLR from living donor donors is equal to or greater than after ALPPS. The KGR of the FLR in patients after ALPPS and living donor donors correlates directly with the size of the FLR

    Introducing Machine Perfusion into Routine Clinical Practice for Liver Transplantation in the United States: The Moment Has Finally Come

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    While adoption of machine perfusion technologies into clinical practice in the United States has been much slower than in Europe, recent changes in the transplant landscape as well as device availability following FDA approval have paved the way for rapid growth. Machine perfusion may provide one mechanism to maximize the utilization of potential donor liver grafts. Indeed, multiple studies have shown increased organ utilization with the implementation of technologies such as ex-situ normothermic machine perfusion (NMP), ex-situ hypothermic machine perfusion (HMP) and in-situ normothermic regional perfusion (NRP). The current review describes the history and development of machine perfusion utilization in the Unites States along with future directions. It also describes the differences in landscape between Europe and the United States and how this has shaped clinical application of these technologies

    Effects of the Share 35 Rule on Waitlist and Liver Transplantation Outcomes for Patients with Hepatocellular Carcinoma.

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    Several studies have investigated the effects following the implementation of the "Share 35" policy; however none have investigated what effect this policy change has had on waitlist and liver transplantation (LT) outcomes for hepatocellular carcinoma(HCC).Data were obtained from the UNOS database and a comparison of the 2 years post-Share 35 with data from the 2 years pre-Share 35 was performed.In the pre-Share35 era, 23% of LT were performed for HCC exceptions compared to 22% of LT in the post-Share35 era (p = 0.21). No difference in wait-time for HCC patients was seen in any of the UNOS regions between the 2 eras. Competing risk analysis demonstrated that HCC candidates in post-Share 35 era were more likely to die or be delisted for "too sick" while waiting (7.2% vs. 5.3%; p = 0.005) within 15 months. A higher proportion of ECD (p<0.001) and DCD (p<0.001) livers were used for patients transplanted for HCC, while lower DRI organs were used for those patients transplanted with a MELDā‰„35 between the 2 eras (p = 0.007).No significant change to wait-time for patients listed for HCC was seen following implementation of "Share 35". Transplant program behavior has changed resulting use of higher proportion of ECD and DCD liver grafts for patients with HCC. A higher rate of wait list mortality was observed in patients with HCC in the post-Share 35 era

    Bias-corrected estimates of reduction of post-surgery length of stay and corresponding cost savings through the widespread national implementation of fast-tracking after liver transplantation: a quasi-experimental study

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    Background: Fast-tracking is an approach adopted by Mayo Clinic in Floridaā€™s (MCF) liver transplant (LT) program, which consists of early tracheal extubation and transfer of patients to surgical ward, eliminating a stay in the intensive care unit in select patients. Since adopting this approach in 2002, MCF has successfully fast-tracked 54.3% of patients undergoing LT. Objectives: This study evaluated the reduction in post-operative length of stay (LOS) that resulted from the fast-tracking protocol and assessed the potential cost saving in the case of nationwide implementation. Methods: A propensity score for fast-tracking was generated based on MCF liver transplant databases during 2011ā€“2013. Various propensity score matching algorithms were used to form control groups from the United Network of Organ Sharing Standard Analysis and Research (STAR) file that had comparable demographic characteristics and health status to the treatment group identified in MCF. Multiple regression and matching estimators were employed for evaluation of the post-surgery LOS. The algorithm generated from the analysis was also applied to the STAR data to determine the proportion of patients in the US who could potentially be candidates for fast-tracking, and the potential savings. Results: The effect of the fast-tracking on the post-transplant LOS was estimated at approximately from 2.5 (p-value = 0.001) to 3.2 (p-value \u3c 0.001) days based on various matching algorithms. The cost saving from a nationwide implementation of fast-tracking of liver transplant patients was estimated to be at least $78 million during the 2-year period. Conclusion: The fast-track program was found to be effective in reducing post-transplant LOS, although the reduction appeared to be less than previously reported. Nationwide implementation of fast-tracking could result in substantial cost savings without compromising the patient outcome

    Patterns and Outcomes Associated with Patient Migration for Liver Transplantation in the United States.

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    Traveling to seek specialized care such as liver transplantation (LT) is a reality in the United States. Patient migration has been attributed to organ availability. The aims of this study were to delineate patterns of patient migration and outcomes after LT.All deceased donor LT between 2008-2013 were extracted from UNOS data. Migrated patients were defined as those patients who underwent LT at a center in a different UNOS region from the region in which they resided and traveled a distance > 100 miles.Migrated patients comprised 8.2% of 28,700 LT performed. Efflux and influx of patients were observed in all 11 UNOS regions. Regions 1, 5, 6, and 9 had a net efflux, while regions 2, 3, 4, 7, 10, and 11 had a net influx of patients. After multivariate adjustment for donor and recipient factors, graft (p = 0.68) and patient survival (p = 0.52) were similar between migrated and non-migrated patients.A significant number of patients migrated in patterns that could not be explained alone by regional variations in MELD score and wait time. Migration may be a complex interplay of factors including referral patterns, specialized services at centers of excellence and patient preference

    Wait list outcomes in patients undergoing liver transplantation for hepatocellular carcinoma in Era 1 (Pre-Share 35) and Era 2 (Post-Share 35).

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    <p>Candidates in Era 2 were more likely to die while waiting (7.2% vs. 5.3%; p = 0.005) within 15 months, while there was no difference in the overall likelihood of getting transplanted (75% vs. 74%; p = 0.42).</p
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