Predictive Variables Affecting Transfusion Requirements in Orthotopic Liver Transplantation

Abstract

Introduction and aims. Adult orthotopic liver transplantation (OLT) is associated with considerable blood product requirements. The aim of this study was to assess the ability of preoperative information to predict intraoperative red blood cell (RBC) transfusion requirements among adult liver recipients. Methods. Preoperative variables with previously demonstrated relationships to intraoperative RBC transfusion were identified from the literature: sex, age, pathology, prothrombin time (PT), factor V, hemoglobin (Hb), and platelet count (plt). These variables were then retrospectively collected from 758 consecutive adult patients undergoing OLT from 1997 to 2007. Relationships between these variables and intraoperative blood transfusion requirements were examined by both univariate analysis and multiple linear regression analysis. Results. Univariate analysis confirmed significant associations between RBC transfusion and PT, factor V, Hb, Plt, pathology, and age (P values all Ͻ .001). However, stepwise backward multivariate analysis excluded variables Plt and factor V from the multiple regression linear model. The variables included in the final predictive model were PT, Hb, age, and pathology. Patients suffering from liver carcinoma required more blood products than those suffering from other pathologies. Yet, the overall predictive power of the final model was limited (R 2 ϭ .308; adjusted R 2 ϭ .30). Conclusion. Preoperative variables have limited predictive power for intraoperative RBC transfusion requirements even when significant statistical associations exist, identifying only a small portion of the observed total transfusion variability. Preoperative PT, Hb, age, and liver pathology seem to be the most significant predictive factors but other factors like severity of liver disease, surgical technique, medical experience in liver transplantation, and other noncontrollable human variables may play important roles to determine the final transfusion requirements.

Perioperative bleeding in patients undergoing liver transplantation

“…Amongst the general patient factors, the recipient's age and body surface area were identified as an independent predictors of the amount of RBCs transfused, the latter being proved in patients receiving a living donor transplant [18,19]. In addition, the impact of the severity of the disease assessed with the Child-Pugh score and Model of End-Stage Liver Disease (MELD) score was frequently studied, yielding inconsistent results.…”

Untitled

“…1 Blood transfusions are an expensive but necessary component of OLT because this surgery has historically been characterized by significant and sometimes unpredictable blood loss. [1][2][3][4][5] When the blood bank at our institution is notified that an OLT will occur, they immediately prepare 10 U of packed red blood cells (PRBCs) for the transplant recipient. 6 Although preparation of 10 U of PRBCs is a common approach in liver transplant centers, there is no standard for blood product preparation, and many centers have developed alternative approaches to massive tranfusion.…”

“…14 Many studies have investigated potential preoperative characteristics that are associated with massive blood loss and therefore necessitate massive blood transfusions in OLT. 1,[4][5][6]9,[12][13][14][16][17][18][19] Factors investigated vary by study and institution but include laboratory values of the recipient and donor, medical history of the organ donor, and recipient preoperative characteristics. Mondanlou and associates found that a transplant recipient's preoperative creatinine level of greater than 1.3 mg/dL positively correlated with massive blood transfusion.…”

“…They determined that statistical associations exist between certain variables and a need for PRBC transfusion, but the predictive power was minimal due to limited sensitivity. 4 An algorithm that is able to accurately predict the likelihood of low-volume intraoperative blood loss has yet to be developed. 6,18,19 Such a tool would enable the tailoring of blood product crossmatching, allocation, and administration to each individual patient.…”

“…6,8,9,16,17,19 Accurate prediction of intraoperative bleeding would not only benefit patients but would also enable better use and coordination of valuable resources, including crossmatching, PRBC allocation, and decreased transfusion department labor. 4,6,9,12,13,[17][18][19] …”