Correlation properties and complexity of perioperative RR-interval dynamics in coronary artery bypass surgery patients.
BACKGROUND
Dynamic measures of heart rate variability (HRV) may uncover abnormalities that are not easily detectable with traditional time and frequency domain measures. The purpose of this study was to characterize changes in RR-interval dynamics in the immediate postoperative phase of coronary artery bypass graft (CABG) surgery using traditional and selected newer dynamic measures of HRV.


METHODS
Continuous 24-h electrocardiograph recordings were performed in 40 elective CABG surgery patients up to 72 h postoperatively. In one half of the patients, Holter recordings were initiated 12-40 h before the surgery. Time and frequency domain measures of HRV were assessed. The dynamic measures included a quantitative and visual analysis of Poincaré plots, measurement of short- and intermediate-term fractal-like scaling exponents (alpha1 and alpha2), the slope (beta) of the power-law regression line of RR-interval dynamics, and approximate entropy.


RESULTS
The SD of RR intervals (P < 0.001) and the ultra-low-, very-low-, low-, and high-frequency power (P < 0.01, P < 0.001, P < 0.001, P < 0.01, respectively) measures in the first postoperative 24 h decreased from the preoperative values. Analysis of Poincaré plots revealed increased randomness in beat-to-beat heart rate behavior demonstrated by an increase in the ratio between short-term and long-term HRV (P < 0.001) after CABG. Average scaling exponent alpha1 of the 3 postoperative days decreased significantly after CABG (from 1.22 +/- 0.15 to 0.85 +/- 0.20, P < 0.001), indicating increased randomness of short-term heart rate dynamics (i.e., loss of fractal-like heart rate dynamics). Reduced scaling exponent alpha1 of the first postoperative 24 h was the best HRV measure in differentiating between the patients that had normal (</= 48 h, n = 33) or prolonged (> 48 h, n = 7) intensive care unit stay (0.85 +/- 0.17 vs. 0.68 +/- 0.18; P < 0.05). In stepwise multivariate logistic regression analysis including typical clinical predictors, alpha1 was the most significant independent predictor (P < 0.05) of long intensive care unit stay. None of the preoperative HRV measures were able to predict prolonged intensive care unit stays.


CONCLUSIONS
In the selected group of patients studied, a decrease in overall HRV was associated with altered nonlinear heart rate dynamics after CABG surgery. Current results suggest that a more random short-term heart rate behavior may be associated with a complicated clinical course. Analysis of fractal-like dynamics of heart rate may provide new perspectives in detecting abnormal cardiovascular function after CABG.