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A multivariable model for predicting the need for blood transfusion in patients undergoing first-time elective
K Karkouti1, M M Cohen, S A McCluskey
1Department of Anesthesia, University Health Network, Toronto General Hospital, Centre for Research in Women's Health, Ontario, Canada. keyvan.karkouti@uhn.on.ca
Background:
The incidence of blood transfusion in coronary artery bypass graft (CABG) surgery remains high. Preoperative identification of those at high risk for requiring blood will allow for the cost-effective use of some blood conservation modalities. Multivariable analysis techniques were used in this study to develop a prediction rule for such a purpose.
Study Design And Methods:
Data were prospectively collected for all patients undergoing elective first-time CABG surgery from January 1997 to September 1998 at a tertiary-care teaching hospital (n = 1007). The prediction rule was developed on the first two-thirds of the sample by using logistic regression methods to examine the relationship of patient demographics, comorbidities, and preoperative Hb with perioperative blood transfusion. The remaining one-third of the sample was used to validate the rule.
Results:
The transfusion rate was 29.4 percent. The prediction rule included preoperative Hb (g/dL, OR 0.928, p<0.0001), weight (kg, OR 0.938, p<0.0001), age (years, OR 1.037, p<0.01), and sex (male/female, OR 0.493, p<0.01); receiver operating characteristic = 0.86. When externally validated, the rule had a sensitivity of 82.1 percent and a specificity of 63.6 percent (at a selected probability cutoff).
Conclusion:
A simple and valid prediction rule is developed for predicting the risk of blood transfusion in patients undergoing first-time elective CABG surgery.