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

Transfusion. 2001 Oct;41(10):1193-203. doi: 10.1046/j.1537-2995.2001.41101193.x.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Aged
  • Algorithms
  • Artificial Intelligence
  • Blood Transfusion / economics
  • Blood Transfusion / statistics & numerical data*
  • Coronary Artery Bypass / economics
  • Coronary Artery Bypass / methods*
  • Coronary Artery Bypass / statistics & numerical data
  • Elective Surgical Procedures
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Cardiovascular*
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Factors
  • Sensitivity and Specificity
  • Sex Factors