title: Characterizing the epidemiology of perioperative transfusion-associated circulatory overload.
abstract: BACKGROUND
  Transfusion-associated circulatory overload (TACO) is a leading cause of transfusion-related fatalities, but its incidence and associated patient and transfusion characteristics are poorly understood. To inform surgical transfusion practice and to begin mitigating perioperative TACO, the authors aimed to define its epidemiology.
  
  
  METHODS
  In this retrospective cohort study, the medical records of adult patients undergoing noncardiac surgery with general anesthesia during 2004 or 2011 and receiving intraoperative transfusions were screened using an electronic algorithm for identification of TACO. Those patients who were screened as high probability for TACO underwent rigorous manual review. Univariate and multivariate analyses evaluated associations between patient and transfusion characteristics with TACO rates in a before-and-after study design.
  
  
  RESULTS
  A total of 2,162 and 1,908 patients met study criteria for 2004 and 2011, respectively. The incidence of TACO was 5.5% (119 of 2,162) in 2004 versus 3.0% (57 of 1,908) in 2011 (P < 0.001), with comparable rates for men (4.8% [98 of 2,023]) and women (3.8% [78 of 2,047]) (P = 0.09). Overall, vascular (12.1% [60 of 497]), transplant (8.8% [17 of 193]), and thoracic surgeries (7.2% [10 of 138]) carried the highest TACO rates. Obstetric and gynecologic patients had the lowest rate (1.4% [4 of 295]). The incidence of TACO increased with volume transfused, advancing age, and total intraoperative fluid balance (all P < 0.001).
  
  
  CONCLUSIONS
  The incidence of perioperative TACO is similar to previous estimates in nonsurgical populations. There was a reduction in TACO rate between 2004 and 2011, with incidence patterns remaining comparable in subgroup analyses. Future efforts exploring risk factors for TACO may guide preventive or therapeutic interventions, helping to further mitigate this transfusion complication.
authors.affiliation: From the Department of Anesthesiology (L.C., Q.J., A.S., M.H.E., G.A.W., D.J.K.), Division of Pulmonary and Critical Care Medicine (H.Y.), Department of Information Technology (S.P.M.), and Division of Biomedical Statistics and Informatics (J.P., D.R.S.), Mayo Clinic, Rochester, Minnesota.
authors.forename: Leanne
authors.initials: L
authors.lastname: Clifford
authors.forename: Qing
authors.initials: Q
authors.lastname: Jia
authors.forename: Hemang
authors.initials: H
authors.lastname: Yadav
authors.forename: Arun
authors.initials: A
authors.lastname: Subramanian
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Wilson
authors.forename: Sean P
authors.initials: SP
authors.lastname: Murphy
authors.forename: Jyotishman
authors.initials: J
authors.lastname: Pathak
authors.forename: Darrell R
authors.initials: DR
authors.lastname: Schroeder
authors.forename: Mark H
authors.initials: MH
authors.lastname: Ereth
authors.forename: Daryl J
authors.initials: DJ
authors.lastname: Kor
mesh_terms: D000368:Aged; D001803:Blood Transfusion / Q000706:statistics & numerical data*; D001810:Blood Volume; D015331:Cohort Studies; D016208:Databases, Factual / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D015994:Incidence; D007430:Intraoperative Care / Q000009:adverse effects / Q000379:methods / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D008910:Minnesota / Q000453:epidemiology; D019990:Perioperative Care / Q000009:adverse effects / Q000379:methods / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D012307:Risk Factors; D017678:Sex Distribution; D012769:Shock; D065227:Transfusion Reaction / Q000453:epidemiology* / Q000209:etiology; D016896:Treatment Outcome