title: A Predictive Model and Risk Score for Unplanned Cardiac Surgery Intensive Care Unit Readmissions.
abstract: BACKGROUND
  Readmissions or "bounce back" to the intensive care unit (ICU) following cardiac surgery is associated with an increased risk of morbidity and mortality. We sought to identify clinical and system-based factors associated with ICU bounce backs in order to generate a Bounce Back After Transfer (BATS) prediction score.
  
  
  METHODS
  We prospectively collected the clinical and financial records of all patients undergoing coronary artery bypass grafting (CABG) or surgical aortic valve replacement (AVR) between May 2013 and March 2014. Multivariable logistic regression was used to identify independent predictors of bounce backs to the ICU which served as the basis for our BATS score.
  
  
  RESULTS
  Of the 532 patients that underwent CABG or AVR during the study period, 35 (6.6%) were readmitted to the ICU. After risk adjustment, female sex, NYHA class III/IV, urgent or emergent operative status, and postoperative renal failure were the predictors of ICU bounce backs utilized to create the BATS score. Patients in the low (<5), moderate (5-10), and high-risk (>10) score cohorts experienced bounce back rates of 3.0%, 10.4%, and 42%, respectively. After adjusting for preoperative patient risk, ICU bounce back resulted in an increase in $68,030 to a patient's total hospital charges.
  
  
  CONCLUSIONS
  A predictive model (BATS) can determine the risk of a bounce back to the ICU after transfer to the floor. We speculate that determination of a patient's BATS upon ICU transfer would allow targeted floor care and decrease bounce back rates, along with postoperative morbidity, mortality, and cost of care.
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: J Trent
authors.initials: JT
authors.lastname: Magruder
authors.affiliation: Division of Pulmonary and Critical Care Medicine, Virginia Commonwealth University, Richmond, VA.
authors.forename: Markos
authors.initials: M
authors.lastname: Kashiouris
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Grimm
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Damon
authors.initials: D
authors.lastname: Duquaine
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Barbara
authors.initials: B
authors.lastname: McGuinness
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Sara
authors.initials: S
authors.lastname: Russell
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Megan
authors.initials: M
authors.lastname: Orlando
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Marc
authors.initials: M
authors.lastname: Sussman
authors.affiliation: Division of Cardiac Surgery, The Johns Hopkins Hospital, Baltimore, MD; Division of Cardiology, The Johns Hopkins Hospital, Baltimore, MD.
authors.forename: Glenn J R
authors.initials: GJ
authors.lastname: Whitman
mesh_terms: D000368:Aged; D001021:Aortic Valve / Q000601:surgery*; D015331:Cohort Studies; D001026:Coronary Artery Bypass / Q000401:mortality; D005260:Female; D005544:Forecasting; D019918:Heart Valve Prosthesis Implantation / Q000401:mortality; D017722:Hospital Charges; D006801:Humans; D007362:Intensive Care Units / Q000191:economics / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D010359:Patient Readmission / Q000191:economics / Q000706:statistics & numerical data; D010360:Patient Transfer / Q000191:economics / Q000706:statistics & numerical data; D011183:Postoperative Complications; D011446:Prospective Studies; D051437:Renal Insufficiency; D012306:Risk; D013997:Time Factors