Context - The ability to predict the use of blood com- ponents during surgery will imp rove the blood bank’s abil- ity to provide efficient service.

Objective - Develop prediction models using preopera- tive risk factors to assess blood component usage during elective coronary artery bypass graft surgery (CABG).

Design - Eighty-three preoperative, multidimensional risk variables were evaluated for patients undergoing elec- tive CABG-only surgery.

Main Outcome Measures - The study endpoints includ- ed transfusion of fresh frozen plasma (FFP), platelets, and red blood cells (RBC). Multivariate logistic regression mod- els were built to assess the predictors related to each of these endpoints.

Setting - Department of Veterans Affairs (VA) health care system.

Patients - Records for 3034 patients undergoing elective CABG-only procedures; 1033 patients received a blood component transfusion during CABG.

Results - Previous heart surgery and decreased ejection fraction were significant predictors of transfusion for all blood components. Platelet count was predictive of plate- let transfusion and FFP utilization. Baseline hemoglobin was a predictive factor for more than 2 units of RBC. Some significant hospital variation was noted beyond that pre- dicted by patient risk factors alone.

Conclusions - Prediction models based on preoperative variables may facilitate blood component management for patients undergoing elective CABG. Algorithms are avail- able to predict transfusion resources to assist blood banks in improving responsiveness to clinical needs. Predictors for use of each blood component may be identified prior to elective CABG for VA patients.