Linear and Nonlinear Analysis of Heart Rate Variability in Postoperative Myocardial Ischemic Patients: Time Domain Analysis versus Approximate Entropy / 대한마취과학회지

ABSTRACT

BACKGROUND: Postoperative myocardial ischemia has been regarded as one of the major predictors of adverse cardiac outcomes after noncardiac surgery in high risk patients. Many schemes have been proposed to stratify the potential risk of this patient group in more noninvasive and cost-effective ways and analysis of heart rate variability (HRV) is one of them. To uncover the underlying changes in HRV with postoperative myocardial ischemia five analytical methods were introduced; SDNN (standard deviation of normal to normal intervals), SDANN (standard deviation of the mean of normal RR intervals for each 5 min period of the entire electrocardiographic recording), RMSSD (root mean square successive difference, the squre root of the mean of the sum of the squares of differences between adjacent normal RR intervals over the entire electrocardiographic recording), PNN50 (percent of difference between adjacent normal RR intervals that are greater than 50 ms computed over the entire electrocardiographic recording) for linear time domain analysis and approximate entropy for nonlinear complexity analysis. METHODS: Sixteen vascular surgical patients were monitored by an ambulatory electrocardiogram preoperatively and during the first postoperative day (POD1). HRV values analyzed by five different measures were compared between a control group (C group) of eight patients with no postoperative ischemia and a postoperative ischemic group (PI group) of eight with ischemia on POD1. RESULTS: Approximate entropy was the only measure of HRV which was significantly lower in PI group than that of C group (P< 0.01) on POD1. CONCLUSIONS: Approximate entropy, a complexity measure could provide more sensitive information about the physiologic changes associated with postoperative ischemia which could not be obtained from the conventional HRV measures. Time domain analyses can be used as adjuvant measures providing information about the cardiac autonomic regulation.