Preoperative nonlinear behavior in heart rate variability predicts morbidity and mortality after coronary artery bypass graft surgery.

Abstract

BACKGROUND: The aim was to demonstrate that a reduction in the nonlinear behavior of heart rate variability (HRV) in the preoperative period in patients undergoing coronary artery bypass graft (CABG) triggers higher morbidity and mortality rates in the postoperative stay. MATERIAL/METHOD: Seventy patients (59+/-10.3 years) were included. HRV was captured by a Polar Advanced S810 heart rate monitor and analyzed using the nonlinear variables detrended fluctuation analysis (DFA), autocorrelation (tau), Lyapunov exponent (LE), and the Poincaré plot (PP). Based on two scenarios, death vs. non-death (scenario 1) and events vs. their absence (scenario 2), the occurrence of neurological complications, infections, kidney failure, arrhythmia, and death were evaluated. Sensitivity, specificity, positive predictive value, negative predictive value, and odds ratio (95% CI) were recorded. RESULTS: In scenario 1, significant differences were found for DFA, alpha-2, LE, PP[SD1], and PP[SD2], with p-values of 0.0172, 0.0343, 0.0159, 0.0069, and 0.0287, respectively. In scenario 2, differences were found for alpha-1, alfa-2, tau, LE, PP[SD1], and PP[SD2], with p-values of 0.0066, 0.0426, 0.0188, 0.0108, 0.0005, and 0.0158, respectively. The best areas under ROC curve were seen in scenario 1, with values of 0.72 (tau), 0.77 (LE), and 0.78 (PP[SD1]). CONCLUSIONS: Analysis of HRV in the nonlinear domain in the preoperative period in patients undergoing elective CABG surgery may detect subgroups with a high risk for postoperative complications, at least with the assistance of some of the variables, and it can become a new prognostic tool for assessing patients scheduled to undergo other major surgeries.