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1 Institute for Cardiovascular Research, University of Leeds, Leeds LS2 9JT
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Abstract |
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(Received 13 November 2004;
accepted after revision 21 January 2005; first published online 21 January 2005)
Corresponding author G. Gulli: Institute for Cardiovascular Research, University of Leeds, Leeds LS2 9JT. Email: giosuegulli{at}yahoo.it
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Introduction |
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It should also be emphasized that in a closed loop condition, such as the cardiovascular system, input and output interact with each other and the output variable (i.e. R–R interval) may induce changes in the input variable (i.e. blood pressure), thereby transforming feedback mechanisms into feedforward ones (Taylor & Eckberg, 1996; Legramante et al. 1999). In humans, the presence of these feedforward, also called ‘non-baroreflex’, sequences, in which linearly correlated changes in heart period and systolic blood pressure are not likely to be linked by a baroreflex mechanism, has been reported (Blaber et al. 1995a; Legramante et al. 1999). However, only one study has focused on their pathophysiological significance in cardiovascular diseases (Legramante et al. 2001).
In this study we adapted a non-invasive method, based on the analysis of the spontaneous fluctuations in blood pressure and heart period (Blaber et al. 1995a; Panerai et al. 1997; Laude et al. 2004), to investigate the latency of the baroreflex response. Using this approach we tested the following hypotheses: (1) that the delay in the ‘spontaneous’ baroreflex response in humans is not constant; and (2) that patients with posturally related syncope, who are likely to have impaired blood pressure control, have a prolonged time delay in the baroreflex response. We also used the method to identify the presence of ‘non-baroreflex’ sequences in cardiovascular variability and to ascertain whether they may be of relevance in patients with posturally related syncope.
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Methods |
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Subjects
We studied 14 patients (6 male) aged 18–68 years (mean ±S.E.M. 37 ± 2.6 years) referred for an orthostatic stress test because of histories suggestive of posturally related syncope. All patients had previously been investigated with 12-lead ECG and Holter monitoring and some had also had cardiac echocardiograms and electroencephalograms when considered clinically appropriate. Results of all tests were normal. No patient included in the study was receiving any medication with cardiovascular effects. Six of them were smokers.
We also studied 16 healthy volunteers (9 male) aged 22–60 years (mean ±S.E.M. 35 ± 2.1 years) with no history of posturally related syncope. They did not display any clinical signs of cardiovascular, neurological or metabolic disorders and were not taking any medication. Six of them were smokers.
The studies were performed in the mornings, in a temperature-controlled (22–24°C) laboratory. Subjects were instructed to have only a light breakfast with no caffeine. Smoking was allowed up to 2 h before starting the test.
Orthostatic tolerance test
Subjects were investigated using a progressive orthostatic stress test of combined head-up tilt (HUT) and lower body negative pressure (LBNP). This has been described in detail previously (El-Bedawi & Hainsworth, 1994; Hainsworth & El-Bedawi, 1994). Briefly, subjects were positioned supine on the tilt table with an adjustable footboard positioned so that the iliac crest was aligned with the pivot of the table. A polypropylene cover was placed over the tilt table and was sealed airtight at the level of the iliac crest, using a wooden board lined with neoprene foam. The LBNP chamber was connected to a vacuum source. The pressure within the chamber was controlled by adjusting the suction with reference to a pressure gauge calibrated in millimetres of mercury below atmospheric.
The protocol included the following consecutive steps: 20 min supine rest; 20 min HUT at 60 deg alone (phase 1); then, while still tilted, 10 min of –20 mmHg LBNP (phase 2); followed by a further 10 min HUT with –40 mmHg LBNP (phase 3). The test was stopped when systolic blood pressure fell below 80 mmHg accompanied by symptoms of impending syncope. The time for this to occur from the start of HUT was taken as the measure of orthostatic tolerance. This test has been demonstrated to be both sensitive and specific, and is highly reproducible in terms of time required to induce presyncope (El-Bedawi & Hainsworth, 1994; Hainsworth & El-Bedawi, 1994). On the basis of previous age- and sex-related predicted values of time to presyncope in normal and syncopal subjects, we divided subjects into those with normal or poor orthostatic tolerance (Hainsworth & El-Bedawi, 1994). These values indicate the time and stage of the orthostatic stress test at which presyncope occurs in 20% of asymptomatic control subjects. The borderline lower limit of ‘normal’ orthostatic tolerance ranges between 28 and 31 min, with the lower orthostatic tolerance occurring in the young, in the elderly and in female subjects.
Recorded variables
We recorded the ECG (lead II) with a standard apparatus (Hewlett Packard 78325C, Boebringen, Germany) and blood pressure with a photo-plethysmographic finger device (Finapres, Ohmeda, Madison, WI, USA) fitted to the right middle finger. Signals were continuously fed to a data acquisition system (Windaq, Dataq Instruments, sampling frequency 1000 Hz) and stored for later analysis. The Finapres readings were verified every 2 min by comparison with an automatic sphygmomanometer (Hewlett Packard 78325C, Boebringen, Germany) placed on the left arm.
Data analysis
We performed off-line beat-to-beat analyses of the stored signals by extracting the time series of successive values of R–R interval (RR), systolic (SAP), diastolic and mean arterial pressure. When present, we corrected for ectopic beats by substituting their values by linear interpolation of adjacent beats. The number of ectopic replacements was always well below 1% of the total number of beats. Time series of 15 min were recorded in the supine state and during 60 deg HUT and analysed. All the time series were stable and thus did not require filtering operations to be optimally analysable.
Spontaneous sequence analysis was inspired by the classical methods (Laude et al. 2004) and by the studies of Blaber et al. (1995a) and Panerai et al. (1997). Throughout the entire time series we fitted a five-beats moving window for the automatic identification of linearly correlated R–R interval and SAP changes. A ramp of at least three consecutive heartbeats in which SAP increased or decreased was considered for further analysis. Once the SAP ramp had been identified, we determined the optimal delay/advance at which the relationship with the following or preceding R–R interval changes occurred. For each sequence we calculated the correlation coefficient at lag 0, 1, 2, 3 and 4 by shifting the R–R time series stepwise by one heartbeat forwards. The same process but shifting the R–R time series backwards was performed to calculate the correlation coefficient at 1, 2, 3 and 4 beats prior to the SAP ramp.
We defined baroreflex sequences as those sequences where SAP changes were followed by linearly correlated R–R changes in the same direction with zero or more beats of delay. ‘Zero’ beats of delay is used here and throughout the manuscript to indicate that the R–R interval response occurs within one R–R interval (i.e. delayed by less than 1 beat). The lag from which the highest correlation coefficient between R–R and SAP changes was found was considered to be the optimal delay, expressed in beats, of the baroreflex response. Only coupled sequences with r > 0.85 were accepted.
We also examined those ‘non-baroreflex’ sequences in which the identified SAP ramp was correlated with preceding R–R interval changes or following R–R interval changes in the opposing direction. For these sequences, the number of beats of delay/advance was obtained by identifying the lag of delay/advance with the highest correlation coefficient between R–R and SAP changes.
To evaluate the effect of the length of R–R interval upon the estimation of the lag (Blaber et al. 1995b), we also report the results by transforming the estimated delay in heartbeats into delay in milliseconds. For each subject, this was estimated using the mean value of the R–R interval. Lag 0 was considered as a delay of one R–R interval (the reflex occurs within the first R–R interval); lag 1 as the delay of two times the mean R–R interval (the reflex occurs within the second R–R interval); lag 2 as the time delay of three times the mean R–R interval (the reflex occurs within the third R–R interval), etc.
The number of sequences analysed depends on the number of heartbeats and so on the mean R–R interval in the recorded time series. Since the mean R–R interval varies between subjects and from the supine to the head-up-tilt position, the numbers of baroreflex and ‘non-baroreflex’ sequences are reported as percentages of the overall number of analysed sequences and as percentages of those validated sequences which fulfilled the above-described criteria.
The slope of the regression line between SAP and R–R for the ‘baroreflex’ sequences was taken as an index of the baroreflex sensitivity (Laude et al. 2004).
Analysis was performed on the entire unfiltered time series and on the time series band-pass filtered for the LF frequencies (0.04–0.15 Hz). At this frequency, despite some controversies into its direct or indirect involvement, it is accepted that the baroreflex plays a key role in the genesis of the cardiovascular variability (deBoer et al. 1987; Bernardi et al. 1994; Cevese et al. 2001; Malpas, 2002). This filtering operation has also been performed so that correlations between arterial pressures and R–R intervals can be estimated independently of respiratory influences.
Statistical analysis
One-way analysis of variance (general linear model) for repeated measurements was applied to compare values obtained at different lags. When appropriate, post hoc multiple comparisons in the groups and between groups were made using a Student–Newman–Keuls test. P < 0.05 was considered statistically significant. All values are reported as means ±S.E.M.
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Results |
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Heart rate and blood pressure response
Mean values of R–R interval and systolic, diastolic and mean arterial blood pressures in the supine posture and in HUT are reported in Table 1. There was no significant difference in the R–R interval between control subjects and patients with poor orthostatic tolerance, although R–R interval during HUT tended to be smaller in patients with poor orthostatic tolerance. Arterial blood pressures were also not significantly different between groups, but tended to be lower both in the supine posture and during HUT in patients with poor orthostatic tolerance, particularly with respect to SAP.
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Unfiltered time series. In control subjests, baroreflex sequences represented approximately 10% of the overall analysed sequences both in the supine phase (10.1 ± 2.2%) and during HUT (10.5 ± 1.7%). Similarly, patients with poor orthostatic tolerance showed 11.7 ± 1.7% of baroreflex sequences in the supine posture, but these decreased significantly to 5.6 ± 1.1% in HUT and were significantly less than in control subjects. In control subjects, ‘non-baroreflex’ sequences were present in approximately 7.7 ± 2.4% of the overall analysed sequences in the supine posture and 6.8 ± 1.3% during HUT. In patients with poor orthostatic tolerance these were 10 ± 2.2% of the overall analysed sequences in the supine phase and around 7.7 ± 1.9% during HUT.
Figure 1A shows the percentage distribution of the accepted baroreflex sequences for each beat of delay considered. The baroreflex response did not occur with constant lag. On average, in the supine posture it occurred after 0.53 ± 0.11 beats in control subjects and after 0.84 ± 0.17 beats in patients (P= 0.07) This means that it occurred mostly with zero beats of delay. However, there were also some baroreflex responses occurring with one or more beats of delay. HUT induced a shift of the latency towards greater delay. On average it occurred after 0.95 ± 0.18 beats in control subjects and after 1.53 ± 0.14 beats in patients (P < 0.01). No correlation between subjects' age and mean latency was found.
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Table 2 reports the percentage distribution of the ‘non-baroreflex’ sequences. In both groups, we found that the majority of the ‘non-baroreflex’ sequences occurred with two beats in advance. This pattern did not change significantly in HUT, and there was no significant difference between control subjects and patients.
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Spontaneous sequence analysis
Time series filtered for the LF band (0.04–0.15 Hz). The baroreflex sequences corresponded to 37.4 ± 1.8% of the overall analysed sequences in control subjects and 34 ± 1.8% in patients. There was a small but significant increase in the percentage of baroreflex sequences with HUT in both groups (42.3 ± 2.4% in control subjects; 38.7 ± 1.8% in patients). Control subjects tended to show more baroreflex sequences than patients in both supine and HUT conditions but this did not reach statistical significance.
‘Non-baroreflex’ sequences represented 36.8 ± 1.9% of the overall analysed sequences in the supine posture in both control subjects and patients. HUT tended to induce (P= 0.07) a small reduction in the percentage of ‘non-baroreflex’ sequences in control subjects (32.5 ± 2.4%) and no significant changes in patients (33.9 ± 2.2%).
Figure 1B shows the distribution of the baroreflex sequences at the different delays considered. In supine subjects the baroreflex response occurred on average after 1.42 ± 0.13 beats in control subjects and after 1.85 ± 0.22 beats in patients (P= 0.06). During HUT the response occurred on average after 1.6 ± 0.22 beats in control subjects and after 2.4 ± 0.2 beats in patients. Again, no correlation between subjects' age and mean latency was found. As Fig. 1B shows, in patients with poor orthostatic tolerance there was a more variable delay in the baroreflex response during the supine phase, with no clear predominance of reflex delay. In these patients, the broad distribution in the baroreflex delay was more pronounced in HUT.
Baroreflex latency expressed in time
Figure 2 shows the cumulative baroreflex response plotted against time for the unfiltered time series. Time was extrapolated by transforming the delay in heartbeats into delay in milliseconds. In control subjects 75% of the baroreflex response occurred within 1 s, whereas in patients with poor orthostatic tolerance the same percentage of response took over 2 s to occur. Interestingly, the ‘non-baroreflex’ sequences maintained the same characteristics in patients and control subjects in both conditions.
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Table 3 reports mean values of baroreflex sensitivity obtained from baroreflex sequences identified at variable delay. Note the within-group difference in the mean values when different time lag is considered. Generally, patients show smaller baroreflex sensitivity values in both supine and HUT conditions.
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Discussion |
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The control group
The forward analysis allowed us to quantify the baroreflex latency by measuring the delay in heartbeats between spontaneous changes in SAP and the following correlated changes in R–R interval occurring in the same direction. The majority of baroreflex sequences during the supine condition occur at lag 0, while during HUT they occur at lag 1. This finding is consistent with the observation of Blaber and co-workers, and as they and other authors suggested, the most likely explanation is the shortening of the mean R–R interval occurring in HUT (Pickering & Davies, 1973; Blaber et al. 1995b). The authors suggested that when the R–R interval is shorter than a critical value (< 850 ms) the baroreflex response occurs with one or more beats of delay. Previous studies in humans using pharmacological blood pressure changes, electrical nerve stimulation, or abrupt neck suction stimuli reported a baroreflex latency of 500–600 ms (Pickering & Davies, 1973; Eckberg, 1976; Baskerville et al. 1979; Borst & Karemaker, 1983). Similar values, based on frequency domain methods, have also recently been reported (Keyl et al. 2001). Our results are compatible with the above-cited studies. As Fig. 2 displays, by transforming the delay in beats into delay in time, 75% of the baroreflex responses in control subjects occurred within 1 s. This delay is kept practically constant in HUT, confirming the previously mentioned hypothesis of Blaber et al. (1995b) and Pickering & Davies (1973).
However, we also found that a few of the spontaneous baroreflex sequences were coupled with up to four heartbeats of delay. Such a delay may not be dependent on the prevailing R–R interval, because only R–R interval series of 250–300 ms may explain such delays. We think that baroreflex sequences with three or four beats of delay are due to a non-constant latency of the baroreflex response. Ferrari et al. (1987) also showed similar results in the baroreflex-mediated response of R–R interval to drug-induced changes in SAP. It has also been shown that sinoaortic denervation in cats is able to abolish the SAP–R–R interval sequences coupled from zero to three beats of lag (Di Rienzo et al. 2001). Therefore, we believe that our observations are pertinent and do not derive from mathematical causality.
One possible reason that the latency in the baroreflex response is not constant and why the response may take up to three to four beats to occur may be the fact that the baroreflex modulation of the R–R interval depends on the phase of respiration and on the phase of the cardiac cycle in which the baroreceptors are stimulated (Eckberg, 1976; Seidel et al. 1997). The baroreflex modulation of the R–R interval is most effective in the late phase of inspiration and early expiration. It might be that a faster baroreflex response occurs during this respiration phase, accounting for the lag 0 baroreflex sequences. The fact that the analysis in the LF band alone shows fewer lag 0 sequences may strengthen this supposition.
Patients with posturally related syncope
In these patients we found more sequences coupled with three and four beats of delay resulting in an increased mean latency particularly during HUT. Figure 2 substantiates the assumption of a prolonged latency in syncopal patients, showing that 75% of the baroreflex responses take more than 2 s to occur.
This investigation supports our earlier hypothesis, based on previous studies (Gulli et al. 2001, 2003) in which we found that patients with poor orthostatic tolerance had an increased phase shift between the SAP and R–R interval fluctuations in the LF range. This parameter is assumed to represent an index of the baroreflex latency. The same patients also showed a slower central oscillating frequency of the LF variability. In accordance with a mathematical model of cardiovascular variability proposed by Ringwood & Malpas (2001) we suggested that the shift towards lower frequencies of the LF variability could be due to an increased time delay of the baroreflex response.
We can only speculate on the mechanisms of the prolonged delay in the baroreflex response. Several factors are known to influence the sinoatrial node response to an arterial pulse, including the timing of the pulse within the breathing cycle (Seidel et al. 1997), the amount of acetylcholine released in response to the pulse (Levy et al. 1981), the magnitude of opposing sympathetic stimulation (Levy et al. 1981), and the timing of the arrival of the bolus of acetylcholine within the cardiac cycle (Eckberg, 1976). These factors may account for some of the variations in the baroreflex latency and may be more or less effective in relation to the length of the R–R interval. However, they do not explain the differences of more than 1 s found in our patients (Fig. 2) even considering that in our patients there is a trend towards shorter R–R interval values. Furthermore, analysis of the LF band alone shows that it is unlikely that respiration plays a role.
It has been shown that withdrawal of vagal drive to the heart by high doses of atropine and stimulation of the sympathetic activity by head-up tilt induce a prolongation of the baroreflex latency (Keyl et al. 2001). We have previously reported (Gulli et al. 2001, 2003) that patients with poor orthostatic tolerance do not show any sign of decreased vagal activity or increased sympathetic activity, so we think it unlikely that this may account for the prolonged baroreflex latency found in our patients.
The LF band
The use of the so-called ‘spontaneous indices’ for the assessment of baroreflex function has been recently criticized by Lipman et al. (2003). Taylor & Eckberg (1996) also reached similar conclusions, showing that in supine conditions R–R interval fluctuations may not reflect baroreflex buffering of arterial pressure. This is particularly evident when the respiratory fluctuations are analysed (Eckberg, 2003). It is well known that the respiratory activity plays a crucial role in the vagal modulation of the heart and may be responsible for SAP–R–R interval oscillations that are not linked by a baroreflex mechanism. For this reason we also examined that part of SAP–R–R interval interaction believed to be independent of respiratory influences. The analysis of the LF variability alone showed qualitatively the same results.
Non-baroreflex sequences
Consistent with the previous observations of Blaber and co-workers the majority of ‘non-baroreflex’ sequences are characterized by R–R interval changes preceding SAP changes with two to three heartbeats in advance (Blaber et al. 1995a). Blaber and co-workers suggested that these ‘non-baroreflex’ sequences reflect chance interaction between R–R interval and SAP and are in fact mathematical artefacts of baroreflex sequences. Our results do not entirely support this notion, because if this were true, the number of baroreflex and ‘non-baroreflex’ sequences should be the same. For this reason, we suggest that at least some of the ‘non-baroreflex’ sequences derive from R–R interval changes of different origin (i.e. baroreflex mediated, respiratory sinus arrhythmia, mechanical, humoral or chaotic), which elicit SAP changes with two to three heartbeats of delay.
In the analysis of the pure time series, we have also found ‘non-baroreflex’ sequences in which R–R interval changes follow SAP changes in the opposite direction (Table 2). These sequences were described by Legramante et al. (1999, 2001) and reflect only a small amount of the cardiovascular variability, and are believed to reflect the feedforward autonomic regulation of the cardiovascular system. Their importance in cardiovascular regulation is unclear.
Methodological aspects
The consistency of ‘spontaneous indices’ is a florid matter of debate (Parati et al. 2004) but, if the aim is merely to derive an index that quantifies baroreflex function, we think that the use of ‘spontaneous’ techniques has physiological rationale. Moreover, the matter of debate is related more to the measurement of the baroreflex gain rather than its latency.
The inaccuracy of the ‘spontaneous’ indices of baroreflex gain obtained in the study of Lipman et al. (2003) could perhaps be explained by the results of the present study. The majority of spontaneous sequence analysis techniques have been reviewed recently (Laude et al. 2004). They frequently use constant values of lag in both supine and HUT conditions and do not take the variable baroreflex latency into consideration. We have shown evidence that the lag in the baroreflex response is not constant and that, as Table 3 shows, indices of baroreflex gain are not constant in relation to the lag considered. Ferrari et al. (1987) showed similar results in ‘open loop’ conditions, using intravenous bolus injections of phenylephrine or glyceryl trinitrate.
Proposed mechanism of fainting
It is well known that in a closed loop oscillating feedback system a delayed response in the output signal may lead to system instability (Mackey & Glass, 1977; Cavalcanti & Belardinelli, 1996). In fact, under these circumstances the response in the output variable (i.e. R–R interval) may fall into the next oscillation of the input variable (i.e. SAP), when an opposite reflex response would be required to buffer it. The result is a resonance condition with amplified oscillations of both variables. Of note, this scenario, whereby blood pressure and R–R interval show large oscillations, has been described by our group in the 2–3 min preceding vasovagal syncope (Julu et al. 2003). The presence of relatively more ‘non-baroreflex’ sequences in patients with poor orthostatic tolerance during HUT may reflect the tendency to SAP–R–R relationship instability in these subjects.
Conclusion
So far, most attention has been focused to a part of the baroreflex function, namely the baroreflex gain/sensitivity of the baroreflex response, and little clinical attention has been given to the baroreflex latency. In this study we proposed a simple non-invasive method to investigate this aspect. We believe that our findings in control subjects and in patients with posturally related syncope are of methodological and of physiological significance and they emphasize the importance of studying the baroreflex function in all its properties.
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References |
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