BACKGROUND: It would be desirable to predict which patients are most likely to benefit from preoperative autologous blood donation. This aim of this study was to develop a point scoring system for predicting the need for blood transfusion in liver surgery. METHODS: The medical records of 480 consecutive patients who underwent hepatic resection were analysed. The data set was split randomly into a derivation set of two-thirds and a validation set of one-third. Univariable analysis was carried out to determine the association between clinicopathological factors and blood transfusion. Significant variables were entered into a multiple logistic regression model, and a transfusion risk score (TRS) was developed. The accuracy of the system was validated by calculating the area under the receiver-operator characteristic (ROC) curve. RESULTS: Factors associated with blood transfusion in multivariable analysis included preoperative haemoglobin concentration below 12.5 g/dl, largest tumour more than 4 cm, need for exposure of the vena cava, need for an associated procedure, and cirrhosis. Each variable was assigned one point, and the total score was compared with the transfusion status of each patient in the validation set. The TRS accurately predicted the likelihood of blood transfusion. In the validation set the area under the ROC curve was 0.89. CONCLUSION: Use of the TRS could lead to substantial saving by improving the cost-effectiveness of the autologous blood donation programme. Copyright (c) 2007 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.
RCT Entities:
BACKGROUND: It would be desirable to predict which patients are most likely to benefit from preoperative autologous blood donation. This aim of this study was to develop a point scoring system for predicting the need for blood transfusion in liver surgery. METHODS: The medical records of 480 consecutive patients who underwent hepatic resection were analysed. The data set was split randomly into a derivation set of two-thirds and a validation set of one-third. Univariable analysis was carried out to determine the association between clinicopathological factors and blood transfusion. Significant variables were entered into a multiple logistic regression model, and a transfusion risk score (TRS) was developed. The accuracy of the system was validated by calculating the area under the receiver-operator characteristic (ROC) curve. RESULTS: Factors associated with blood transfusion in multivariable analysis included preoperative haemoglobin concentration below 12.5 g/dl, largest tumour more than 4 cm, need for exposure of the vena cava, need for an associated procedure, and cirrhosis. Each variable was assigned one point, and the total score was compared with the transfusion status of each patient in the validation set. The TRS accurately predicted the likelihood of blood transfusion. In the validation set the area under the ROC curve was 0.89. CONCLUSION: Use of the TRS could lead to substantial saving by improving the cost-effectiveness of the autologous blood donation programme. Copyright (c) 2007 British Journal of Surgery Society Ltd. Published by John Wiley & Sons, Ltd.
Authors: Chad G Ball; Henry A Pitt; Molly E Kilbane; Elijah Dixon; Francis R Sutherland; Keith D Lillemoe Journal: HPB (Oxford) Date: 2010-09 Impact factor: 3.647