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BACKGROUND: Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection.METHODS: A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases(70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30%(n=463) was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement.RESULTS: Extrahepatic procedure, major liver resection,hemoglobin level and platelets count were identified as independent predictors for transfusion requirement by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low,moderate and high risk, respectively. The prediction model appeared accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set.CONCLUSIONS: We have developed and validated an integerbased risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgicalcenter. This score allows identifying patients at a high risk and may alter transfusion practices.
BACKGROUND: Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection. METHODS: A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases (70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30% ( Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement .RESULTS: Extrahepatic procedure, major liver resection, hemoglobin level and platelets count were identified as independent predictors for transfusion requ A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low, moderate and high risk, respectively. The prediction model had accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set.CONCLUSIONS: We have developed and validated an integer based on risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgicalcenter. This score allows identifying patients at a high risk and may alter transfusion practices.