Prediction of portal venous pressure in living donor liver transplantation: A retrospective study

Author:

Kurihara Takeshi,Itoh Shinji,Toshima Takeo,Toshida Katsuya,Tomiyama Takahiro,Kosai Yukiko,Tomino Takahiro,Yoshiya Shohei,Nagao Yoshihiro,Morita Kazutoyo,Ninomiya Mizuki,Harada Noboru,Yoshizumi Tomoharu

Abstract

Liver transplantation is the definitive treatment for advanced liver cirrhosis with portal hypertension. In Japan, the scarcity of deceased donors leads to reliance on living donors, often resulting in smaller grafts. Managing portal venous pressure (PVP) is critical to prevent fatal posttransplant complications. This study explored the possibility of predicting intraoperative PVP. We analyzed 475 living donor liver transplant cases from 2006 to 2023, excluding those with acute liver failure or prior splenectomy or splenic artery embolization. Patients were divided into a training group (n = 425) and a test group (n = 50). We evaluated the correlation between preoperative factors and PVP at laparotomy to predict PVP at laparotomy and closure. The predictive model was validated with the test group data. PVP at laparotomy could be predicted using correlated preoperative factors: prothrombin time (p < 0.001), predicted splenic volume (p < 0.001), and presence of a portosystemic shunt (p = 0.002), as follows: predicted PVP at laparotomy (mm Hg)=25.818 − 0.077 × (prothrombin time [%]) + 0.004 × (predicted splenic volume [mL]) − 2.067 × (1: with a portosystemic shunt) (p < 0.001; R = 0.346). In addition, PVP at closure could be predicted using correlated operative factors, including measured PVP at laparotomy, as follows: predicted PVP at closure (mm Hg)=14.268 + 0.149 × (measured PVP at laparotomy [mm Hg]) − 0.040 × (GV/SLV [%]) − 0.862 × (1: splenectomy [if yes]) − 3.511 × (1: splenic artery ligation without splenectomy [if yes]) (p < 0.001; R = 0.339). This study demonstrated the feasibility of predicting intraoperative PVP using preoperative factors in patients with decompensated cirrhosis undergoing liver transplant. This predictive approach could refine surgical planning, potentially improving patient outcomes.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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