Background: heart rate variability (HRV) is a noninvasive diagnostic method used in the assessment of the autonomic modulation of the heart. The assessment of HRV using nonlinear dynamics methods in the preoperative period of surgical myocardial revascularization could be predictive of morbidity such as pulmonary infections in the postoperative period.
Objective: to evaluate the behavior of HRV using nonlinear dynamics in the preoperative period of surgical myocardial revascularization and its relation to the occurrence of pulmonary infections in the in-hospital postoperative period.
Methods: a total of 69 patients with coronary artery disease (mean age of 58.6 ± 10.4 years) and indication for elective surgical myocardial revascularization were studied. In order to quantify the nonlinear dynamics of HRV, the following procedures were performed: detrended fluctuation analysis (DFA); analysis of the short (α1) and long-term (α2) components of DFA; approximate entropy (ApEn); Lyapunov exponent (LE); and Hurst exponent (HE) of time series of RR intervals of the ECG, as captured by the Polar S810i instrument on the day before surgery.
Results: at the cut-off levels set by the ROC curve, there was a significant difference between the groups with and without pulmonary infections in the postoperative period of myocardial revascularization for total DFA, approximate entropy and Lyapunov exponent with p = 0. 0309, p = 0.0307 and p = 0.0006, respectively.
Conclusion: the nonlinear dynamics methods, at their respective cut-off levels, allowed for the identification of patients developing pulmonary infection in the postoperative period of surgical myocardial revascularization, thus suggesting that these methods may have a prognostic value for this group of patients.