A multivariable model for predicting the need for blood transfusion in patients undergoing first-time elective coronary bypass graft surgery

• Published in: Transfusion (Philadelphia, Pa.) Vol. 41; no. 10; pp. 1193 - 1203
• Main Authors: Karkouti, Keyvan, Cohen, Marsha M., McCluskey, Stuart A., Sher, Graham D.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Science Inc 01.10.2001; Blackwell Publishing
• Subjects: Aged; Algorithms; Artificial Intelligence; Biological and medical sciences; Blood Transfusion - economics; Blood Transfusion - statistics & numerical data; CABG = coronary artery bypass graft; Coronary Artery Bypass - economics; Coronary Artery Bypass - methods; Coronary Artery Bypass - statistics & numerical data; CPB = cardiopulmonary bypass; Elective Surgical Procedures; Female; Humans; ICU= intensive care unit; Male; Medical sciences; Middle Aged; Models, Cardiovascular; PABD = preoperative autologous blood donation; Predictive Value of Tests; Prospective Studies; Risk Factors; ROC = receiver operating charactistic; Sensitivity and Specificity; Sex Factors; Surgery (general aspects). Transplantations, organ and tissue grafts. Graft diseases; Surgery of the heart; Human; Transfusion; Aortocoronary; Bypass; Indication; Surgery; Surgical anastomosis; Models; Multivariate analysis; Predictive factor; Incidence
• ISSN: 0041-1132; 1537-2995
• DOI: 10.1046/j.1537-2995.2001.41101193.x

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.