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Preoperative portal vein recanalization-transjugular intrahepatic portosystemic shunt for chronic obliterative portal vein thrombosis: Outcomes following liver transplantation.

Abhinav TalwarJeffrey VargheseGabriel M KnightNitin KatariyaJuan-Carlos CaicedoZach DietchDaniel Borja-CachoDaniela P LadnerDerrick ChristopherTalia BakerMichael AbecassisSamdeep MouliKush DesaiAhsun RiazBart ThornburgRiad Salem
Published in: Hepatology communications (2022)
High-grade portal vein thrombosis (PVT) is often considered to be a technically challenging scenario for liver transplantation (LT) and in some centers a relative contraindication. This study compares patients with chronic obliterative PVT who underwent portal vein recanalization-transjugular intrahepatic portosystemic shunt (PVR-TIPS) and subsequent LT to those with partial nonocclusive PVT who underwent LT without an intervention. This institutional review board-approved study analyzed 49 patients with cirrhosis with PVT from 2000 to 2020 at our institution. Patients were divided into two groups, those that received PVR-TIPS due to anticipated surgical challenges from chronic obliterative PVT and those who did not because of partial PVT. Demographic data and long-term outcomes were compared. A total of 35 patients received PVR-TIPS while 14 did not, with all receiving LT. Patients with PVR-TIPS had a higher Yerdel score and frequency of cavernoma than those that did not. PVR-TIPS was effective in decreasing portosystemic gradient (16 down to 8 mm HG; p < 0.05). Both groups allowed for end-to-end anastomoses in >90% of cases. However, veno-veno bypass was used significantly more in patients who did not receive PVR-TIPS. Additionally, patients without PVR-TIPS required significantly more intraoperative red blood cells. Overall survival was not different between groups. PVR-TIPS demonstrated efficacy in resolving PVT and allowed for end-to-end portal vein anastomoses. PVR-TIPS is a viable treatment option for chronic obliterative PVT with or without cavernoma that simplifies the surgical aspects of LT.
Keyphrases
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  • deep learning
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