• Keyvan Karkouti, Rachel O'Farrell, Terrence M Yau, W Scott Beattie, and Reducing Bleeding in Cardiac Surgery Research Group.
• University Health Network, Toronto General Hospital, Department of Anesthesia, EN 3-402, 200 Elizabeth Street, Toronto, Ontario M5G 2C4, Canada. keyvan.karkouti@uhn.on.ca
• Can J Anaesth. 2006 Aug 1;53(8):781-94.

PurposeIn cardiac surgery with cardiopulmonary bypass (CPB), excessive blood loss requiring the transfusion of multiple red blood cell (RBC) units is a common complication that is associated with significant morbidity and mortality. The objective of this study was to develop a prediction rule for massive blood transfusion (MBT) that could be used to optimize the management of, and research on, at-risk patients.MethodsData were collected prospectively over the period from 2000 to 2005, on patients who underwent surgery with CPB at one hospital. Patients who received > or = five units of RBC within one day of surgery were classified as MBT. Logistic regression was used to appropriately select and weigh perioperative variables in the prediction rule, which was developed on the initial 60% of the sample and validated on the remaining 40%.ResultsOf the 10,667 patients included, 925 (8.7%) had MBT. The clinical prediction rule included 12 variables (listed in order of predictive value: CPB duration, preoperative hemoglobin concentration, body surface area, nadir CPB hematocrit, previous sternotomy, preoperative shock, preoperative platelet count, urgency of surgery, age, surgeon, deep hypothermic circulatory arrest, and type of procedure) and was highly discriminative (c-index = 0.88). In the validation set, those classified as low-, moderate-, and high-risk by a simple risk score derived from the prediction rule had a 5%, 27%, and 58% chance of MBT, respectively.ConclusionA clinical prediction rule was developed that accurately identified patients at low-risk or high-risk for MBT. Studies are needed to determine the external generalizability and clinical utility of the prediction rule.

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