OBJECTIVE: Although an extensive number of studies have attempted to identify predictors of new-onset atrial fibrillation (AFIB) after coronary artery bypass grafting (CABG), a strong predictive model does not exist. Prior studies have included patients recruited from multiple centers with variant AFIB prevalence rates and those who underwent CABG in combination with other surgical procedures. Also, most studies have focused on pre- and perioperative characteristics, with less attention given to the initial postoperative period. The purpose of this study was to comprehensively examine pre-, peri-, and postoperative characteristics that might predict new-onset AFIB in a large sample of patients undergoing isolated CABG in a single medical center, utilizing data readily available to clinicians in electronic data repositories. In addition, length of stay and selected postoperative complications and disposition were compared in patients with AFIB and no AFIB. DESIGN: Retrospective, comparative survey. SETTING: University-affiliated tertiary care hospital. PATIENTS: Patients with new-onset AFIB who underwent isolated standard CABG or minimally invasive direct vision coronary artery bypass were identified from an electronic clinical data repository. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The prevalence of AFIB in the total sample (n = 814) was 31.9%. Predictors of AFIB included age (p =.0004), number of vessels bypassed (p =.013), vessel location (diagonal [p <.003] or posterior descending artery [p <.001]), and net fluid balance on the operative day (p =.015). Forward stepwise regression analysis produced a model that correctly predicted AFIB in only 24% of cases, with age (14%) and body surface area (9%) providing the most prediction. The incidence of embolic stroke was higher in AFIB (n = 8) vs. no AFIB (n = 4) patients, but stroke preceded AFIB onset in seven of eight cases. Subjects with AFIB had a longer stay (p =.0004), more intensive care unit readmissions (p =.0004), and required more assistance at hospital discharge (p =.017). CONCLUSIONS: Despite attempts to examine comprehensively predictors of new-onset AFIB, we were unable to identify a robust predictive model. Our findings, in combination with prior work, imply that it may not be feasible to predict the development of new-onset AFIB after CABG using data readily available to the bedside clinician. In this sample, stroke was uncommon and, when it occurred, preceded AFIB in all but one case. As anticipated, AFIB increased length of stay, and patients with this complication required more assistance at discharge.
OBJECTIVE: Although an extensive number of studies have attempted to identify predictors of new-onset atrial fibrillation (AFIB) after coronary artery bypass grafting (CABG), a strong predictive model does not exist. Prior studies have included patients recruited from multiple centers with variant AFIB prevalence rates and those who underwent CABG in combination with other surgical procedures. Also, most studies have focused on pre- and perioperative characteristics, with less attention given to the initial postoperative period. The purpose of this study was to comprehensively examine pre-, peri-, and postoperative characteristics that might predict new-onset AFIB in a large sample of patients undergoing isolated CABG in a single medical center, utilizing data readily available to clinicians in electronic data repositories. In addition, length of stay and selected postoperative complications and disposition were compared in patients with AFIB and no AFIB. DESIGN: Retrospective, comparative survey. SETTING: University-affiliated tertiary care hospital. PATIENTS: Patients with new-onset AFIB who underwent isolated standard CABG or minimally invasive direct vision coronary artery bypass were identified from an electronic clinical data repository. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The prevalence of AFIB in the total sample (n = 814) was 31.9%. Predictors of AFIB included age (p =.0004), number of vessels bypassed (p =.013), vessel location (diagonal [p <.003] or posterior descending artery [p <.001]), and net fluid balance on the operative day (p =.015). Forward stepwise regression analysis produced a model that correctly predicted AFIB in only 24% of cases, with age (14%) and body surface area (9%) providing the most prediction. The incidence of embolic stroke was higher in AFIB (n = 8) vs. no AFIB (n = 4) patients, but stroke preceded AFIB onset in seven of eight cases. Subjects with AFIB had a longer stay (p =.0004), more intensive care unit readmissions (p =.0004), and required more assistance at hospital discharge (p =.017). CONCLUSIONS: Despite attempts to examine comprehensively predictors of new-onset AFIB, we were unable to identify a robust predictive model. Our findings, in combination with prior work, imply that it may not be feasible to predict the development of new-onset AFIB after CABG using data readily available to the bedside clinician. In this sample, stroke was uncommon and, when it occurred, preceded AFIB in all but one case. As anticipated, AFIB increased length of stay, and patients with this complication required more assistance at discharge.
Authors: G H Almassi; T Schowalter; A C Nicolosi; A Aggarwal; T E Moritz; W G Henderson; R Tarazi; A L Shroyer; G K Sethi; F L Grover; K E Hammermeister Journal: Ann Surg Date: 1997-10 Impact factor: 12.969
Authors: L A Mendes; G P Connelly; P A McKenney; P J Podrid; L A Cupples; R J Shemin; T J Ryan; R Davidoff Journal: J Am Coll Cardiol Date: 1995-01 Impact factor: 24.094
Authors: Benjamin A Steinberg; Yue Zhao; Xia He; Adrian F Hernandez; David A Fullerton; Kevin L Thomas; Roger Mills; Winslow Klaskala; Eric D Peterson; Jonathan P Piccini Journal: Clin Cardiol Date: 2013-12-18 Impact factor: 2.882
Authors: Mengalvio E Sleeswijk; Trudeke Van Noord; Jaap E Tulleken; Jack J M Ligtenberg; Armand R J Girbes; Jan G Zijlstra Journal: Crit Care Date: 2007 Impact factor: 9.097