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General Discussion cooperation. Variation in ABP can also be provoked e.g. by respiration 8, 30, squat-stand maneuvers 4, 7, 40 or in- and deflating leg cuffs 1, 14, 36. With in- and expiration lung volume in- and decreases resulting in de- and increasing stroke volume of the heart, leading to cyclic variation in blood pressure. Asking a subject to perform these respiration maneuvers at a fixed rate results in ABP variation at the same rate which is also known as respiratory sinus arrhythmia. More powerful oscillations further challenge dCA and therefore enhance clinical significance of autoregulation tests. Single or repetitive squatting followed by standing (squat-stand) elicits transient changes in central blood volume and peripheral vascular resistance, leading to large changes in arterial pressure and heart rate. Although leading to less powerful blood pressure variations than squat-stand, sit-stand maneuvers may also be used. Van Beek et al 38 showed that this method was well tolerated to study dCA in elderly. In patients undergoing cardiopulmonary bypass surgery hardly any spontaneous oscillations of blood pressure occur. This since autonomic control cannot influence heart rate when the heart is not beating. So, for studying dCA in these circumstances evoked blood pressure changes are needed. Using cyclic variation of pump flow we could induce variations in ABP leading to variations in CBFV (chapter 6). For these evoked ABP oscillations power spectral densities at 0.1 Hz are higher than for sit-stand maneuvers but lower than for squat-stand maneuvers. The high coherence between ABP and CBFV for the oscillations evoked during cardiopulmonary bypass cannot be explained by the high power oscillations alone. Possibly the lack of other sources of variation and so the lack of noise, may have also contributed to this. Not all studies on dCA evaluation using transfer function analysis report both power spectral density of ABP and CBFV and their coherence, but from the available data it seems that coherence increases with magnitude of ABP variations. A small pilot study (unpublished results) we performed in healthy volunteers seems to confirm this relation, but needs further investigation. Possibly there might also be a relation between the magnitude of ABP variations and dCA results. Transfer function analysis In chapter 2 different settings for transfer function analysis (TFA) were implemented and dCA results were compared. Transfer function analysis starts with estimating the auto spectra of and cross spectra between ABP and CBFV. However, before estimating the spectra first the offset, respectively low 125


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