title: Predictors of transfusion of packed red blood cells in coronary artery bypass grafting surgery.
abstract: OBJECTIVE
  Finding predictors of blood transfusion may facilitate the most efficient approach for the use of blood bank services in coronary artery bypass grafting procedures. The aim of this retrospective study is to identify preoperative and intraoperative patient characteristics predicting the need for blood transfusion during or after CABG in our local cardiac surgical service.
  
  
  METHODS
  435 patients undergoing isolated first-time CABG were reviewed for their preoperative and intraoperative variables and analyzed postoperative data. Patients were 255 males and 180 females, with mean age 62.01 ± 10.13 years. Regression logistic analysis was used for identifying the strongest perioperative predictors of blood transfusion.
  
  
  RESULTS
  Blood transfusion was used in 263 patients (60.5%). The mean number of transfused blood products units per patient was 2.27 ± 3.07 (0-23) units. The total number of transfused units of blood products was 983. Univariate analysis identified age >65 years, weight <70 Kg, body mass index <25 Kg/m2, hemoglobin <13mg/dL, hematocrit < 40% and ejection fraction <50%, use of cardiopulmonary bypass (CPB), not using an internal thoracic artery as a bypass, and multiple bypasses as significant predictors. The strongest predictors using multivariate analysis were hematocrit < 40% (OR 2.58; CI 1.62-4.15; P<0.001), CPB use (OR 2.00; CI 1.27-3.17; P=0.003) and multiple bypasses (OR 2.31; CI 1.31-4.08; P=0.036).
  
  
  CONCLUSIONS
  The identification of these risk factors leads to better identification of patients with a greater probability of using blood, allocation blood bank resources and cost-effectiveness use of blood products.
authors.affiliation: Division of Cardiovascular Surgery of Pronto Socorro Cardiológico de Pernambuco – PROCAPE. University of Pernambuco – UPE, Brazil. michel_pompeu@yahoo.com.br
authors.forename: Michel Pompeu Barros de Oliveira
authors.initials: MP
authors.lastname: Sá
authors.forename: Evelyn Figueira
authors.initials: EF
authors.lastname: Soares
authors.forename: Cecília Andrade
authors.initials: CA
authors.lastname: Santos
authors.forename: Omar Jacobina
authors.initials: OJ
authors.lastname: Figueiredo
authors.forename: Renato Oliveira Albuquerque
authors.initials: RO
authors.lastname: Lima
authors.forename: Fábio Gonçalves de
authors.initials: FG
authors.lastname: Rueda
authors.forename: Rodrigo Renda de
authors.initials: RR
authors.lastname: Escobar
authors.forename: Alexandre Magno Macário Nunes
authors.initials: AM
authors.lastname: Soares
authors.forename: Ricardo de Carvalho
authors.initials: Rde C
authors.lastname: Lima
mesh_terms: D016063:Blood Loss, Surgical / Q000517:prevention & control*; D002315:Cardiopulmonary Bypass / Q000706:statistics & numerical data; D001026:Coronary Artery Bypass / Q000009:adverse effects* / Q000379:methods; D004812:Epidemiologic Methods; D017707:Erythrocyte Transfusion / Q000706:statistics & numerical data*; D005260:Female; D006400:Hematocrit; D006801:Humans; D007430:Intraoperative Care; D008297:Male; D008875:Middle Aged; D011300:Preoperative Care; D012016:Reference Values