Liver transplantation (LT) is a surgery with risk of bleeding. Several risk factors have been identified: complex dissection, portal hypertension, history of ascites fluid infections, history of surgical procedures, pre-existing complex hemostatic disorders and those acquired during the procedure. Diffuse bleeding can occur at any time during the 3 phases of surgery: dissection, anhepatic and neohepatic. However, intraoperative bleeding and transfusion requirements remain difficult to predict. Current predictive models are based in particular on preoperative characteristics and do not take into account the course and different phases of the operation. The need for transfusions has largely decreased over the last 20 years, and currently around 20-25% of patients are transfused (transfusion of at least 1 blood product during LT). However, massive transfusion is necessary in 10% of LT. The European Society of Anaesthesiology (ESA) has issued recommendations on the management of severe bleeding during surgery. However, these recommendations are not specific to LT. Moreover, transfusion strategies vary widely from one center to another. The implementation of protocols within teams dedicated to LT has led to a reduction in bleeding and transfusion, with or without the use of viscoelastic testing. Intraoperative bleeding and transfusion requirements, as well as postoperative thromboembolic complications, remain difficult to predict. Predictive models of bleeding risk have been developed, but they are based solely on preoperative characteristics and do not take into account the course and various phases of the operation. In addition, new methods such as Bayesian inference or machine learning have been developed, and seem capable of providing different information from that obtained by conventional models. The overall aim of this prospective multicenter observational study is to investigate the risk factors for bleeding and thrombosis in per- and post-operative LT using different predictive methods, and to describe the management of bleeding and post-operative anticoagulation in metropolitan France.
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Determine factors that predict the number of red blood cells packed (pRBCs) transfused intraoperatively in LT
Timeframe: number of pRBCs transfused during surgery