Risk factors of delayed extubation, prolonged length of stay in the intensive care unit, and mortality in patients undergoing coronary artery bypass graft with fast-track cardiac anesthesia - A new cardiac risk score

Background: Risk factors of delayed extubation, prolonged intensive care un it (ICU) length of stay (LOS), and mortality have not been studied for pati ents administered fast-track cardiac anesthesia (FTCA), The authors' goals were to determine risk factors of outcomes and cardiac risk scores (CRS) fo r CABG patients undergoing FTCA. Methods: Consecutive CABG patients undergoing FTCA were prospectively studi ed. Outcome variables were delayed extubation > 10 h, prolonged ICU LOS > 4 8 h, and mortality. Univariate analysis were performed followed by multiple logistic regression to derive risk factors of the three outcomes. Simplifi ed integer-based CRS were derived from logistic models. Bootstrap validatio n was performed to assess and compare the predictive abilities of CRS and l ogistic models for the three outcomes. Results: The authors studied 885 patients. Twenty-five percent had delayed extubation, 17% had prolonged ICU LOS, and 2.6% died Risk factors of delaye d extubation were increased age, female gender, postoperative use of intraa ortic balloon pump, inotropes, bleeding, and atrial arrhythmia, Risk factor s of prolonged ICU LOS were those of delayed extubation plus preoperative m yocardial infarction and postoperative renal insufficiency. Risk factors of mortality were female gender, emergency surgery, and poor left ventricular function. CRSs were modeled for the three outcomes. The area under the rec eiver operating characteristic curve for the CRS-logistic models was not si gnificantly different: 0.707/0.702 for delayed extubation, 0.851/0.855 for prolonged ICU LOS, and 0.657/0.699 for mortality. Conclusion: In CABG patients undergoing FTCA, the authors derived and valid ated risk factors of delayed extubation, prolonged ICU LOS, and mortality. Furthermore, they developed a simplified CRS system with similar predictive abilities as the logistic models.