Heart transplant ( HT) is the last resort for an increasing number of patients suffering from severe cardiac ailment. During the standard surgical procedure, the donor ’s and the recipient ’s atria are sutured together. The original SA node remains innervated, however, the electrical signal it generates cannot cross the suture line. On the other hand, the SA node of the transplanted heart, which actually determines the heart rate ( HR) , is fully denervated. This denervation spurs the development of compensatory control mechanisms. The main aim of this study was the non- invasive characterization of those mechanisms and their evolution over time.
We obtained 25 recordings from 13 male heart transplant patients. Time after Transplant ( TAT) was 0.5- 62.5 months. The control group included 14 healthy male subjects ( age: 28- 59) . ECG, continuous blood pressure ( BP) and respiration were recorded for 45 min, first supine, then during active change of posture ( CP) to standing. The signals were analyzed in both the time and frequency domains.
Our principal finding was the consistent pattern of evolution of the HR response to standing: from no response, via a slow response to a fast increase. HR response correlated with TAT ( p 0.001) . HR variability indices correlated with HR response to CP, indicating the gradual development of partial sympathetic reinnervation. An important new finding was the presence of Very High Frequency ( VHF) peaks in the power spectrum of HR and BP fluctuations. Extensive arrhythmias tended to appear at the TAT, which corresponds to the transition from slow to fast HR response to CP.
Our results indicate the existence of a biphasic evolution in cardiac control mechanisms from lack of control to a first order control loop, followed by partial sympathetic reinnervation and finally, the direct effect of the old SA node on the pacemaker cell of the new SA node. No indication of vagal reinnervation was observed.
We believe that the VHF peaks found in the HR and BP spectra of HT patients bear important physiological information. We analyzed those signals using the Higher Order Statistics approach. Specifically, third order statistics, the bispectrum and bicoherence were found useful. Applying the bispectrum and bicoherence on real data results in many noise- driven spurious peaks. Therefore, we developed statistical tests on the amplitude of the bicoherence to differentiate between real and spurious bispectral peaks. This method causes, on average, the deletion of 99% of those spurious peaks. However, the remaining 1% peaks still obscured the true peaks. Hence, we developed a new statistical test for the phase of the bispectrum, which eliminated over 99.99% of the spurious peaks. The combination of both kinds of tests provides a powerful tool for the characterization and understanding of complex nonlinear oscillatory systems. We applied these methods to the HR and BP traces of the HT patients. Our results indicate that the power spectrum of HR fluctuations in HT subjects consists of 3 types of spectral peaks: A) 22 recordings exhibited the well- known low and high frequency ( respiratory) peaks. B) VHF peaks, which are harmonics of the respiratory frequency were found in 8 recordings. C) In 5 recordings, the bicoherence revealed a set of VHF peaks, which are totally unrelated to the respiratory frequency. This third type of VHF peaks ( C) suggests the existence of unknown underlying mechanisms of cardiovascular control or interaction. We believe that the use of bicoherence can provide valuable information on the correlation between oscillations of different frequencies, as well as knowledge concerning the source of the oscillations and the functioning of the system.