title: A risk score for predicting perioperative blood transfusion in liver surgery.
abstract: 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.
  
  
  CONCLUSIONS
  Use of the TRS could lead to substantial saving by improving the cost-effectiveness of the autologous blood donation programme.
authors: Department of Surgery-Liver Unit, Scientific Institute San Raffaele, Vita-Salute San Raffaele University, Milan, Italy.
authors: C
authors: C
authors: Pulitanò
authors: M
authors: M
authors: Arru
authors: L
authors: L
authors: Bellio
authors: S
authors: S
authors: Rossini
authors: G
authors: G
authors: Ferla
authors: L
authors: L
authors: Aldrighetti
mesh_terms: D000368:Aged; D001804:Blood Transfusion, Autologous / Q000191:economics / Q000706:statistics & numerical data*; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D017558:Elective Surgical Procedures; D005260:Female; D006801:Humans; D008107:Liver Diseases / Q000191:economics / Q000601:surgery*; D008297:Male; D011300:Preoperative Care / Q000191:economics / Q000379:methods*; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors