CONTEXT: The ability to predict the use of blood components during surgery will improve the blood bank's ability to provide efficient service. OBJECTIVE: Develop prediction models using preoperative 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 elective CABG-only surgery. MAIN OUTCOMES MEASURES: The study endpoints included transfusion of fresh frozen plasma (FFP), platelets, and red blood cells (RBC). Multivariate logistic regression models 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 platelet 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 predicted by patient risk factors alone. CONCLUSIONS: Prediction models based on preoperative variables may facilitate blood component management for patients undergoing elective CABG. Algorithms are available 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.
CONTEXT: The ability to predict the use of blood components during surgery will improve the blood bank's ability to provide efficient service. OBJECTIVE: Develop prediction models using preoperative 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 elective CABG-only surgery. MAIN OUTCOMES MEASURES: The study endpoints included transfusion of fresh frozen plasma (FFP), platelets, and red blood cells (RBC). Multivariate logistic regression models 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 platelet 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 predicted by patient risk factors alone. CONCLUSIONS: Prediction models based on preoperative variables may facilitate blood component management for patients undergoing elective CABG. Algorithms are available 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 VApatients.
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