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Egi, Akiko*; Kawamoto, Masashi*; Kurita, Shigeaki*; Yuge, Osafumi

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doi: 10.1097/shk.0b013e318054dfe3
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Coyle et al. (1) reported that systolic pressure variation (SPV), defined as the difference between the maximum and minimum values of systolic arterial pressure (SAP) during one mechanical respiratory cycle, is an indicator of hypovolemia, whereas Perel et al. (2) demonstrated that SPV reflects the degree of blood loss during graded hemorrhaging and predicts fluid responsiveness to volume loading under mechanical ventilation (3). However, Michard et al. (4) noted that pulse pressure (PP) variation is a more accurate predictor of fluid responsiveness than SPV and also speculated that SAP is affected by changes in aortic transmural pressure, mainly related to changes in stroke volume and extramural pressure (i.e., from changes in pleural pressure), whereas PP, which is the difference between SAP and diastolic arterial pressure, is dependent only on changes in transmural pressure. The SPV and PP variation (PPV) are considered to be noninvasive and more sensitive parameters than conventional volume status markers, such as central venous pressure (CVP) and pulmonary arterial occlusion pressure.

Power spectrum analyses of SAP variability (PSSAPV) and heart rate variability (PSHRV) are useful tools to represent cardiovascular autonomic nervous system activity (5). It has been suggested that the high-frequency component (HF) of PSSAPV, which is synchronous with respiration, reflects circulating blood volume (CBV) in a manner similar to SPV, as it has been reported to be increased during graded hemorrhaging in animals (6, 7). Furthermore, the HF of PSSAPV has been shown to be comparable with %SPV mean, which is the difference between maximum and minimum SAP during one respiratory cycle divided by the mean of two values (defined in detail later by the formula presented in the "Data Analysis" section), as an indicator of graded hemorrhaging (8). To our knowledge, no study has been conducted to determine the best parameter among PSSAPV, PSHRV, SPV, and PPV to reflect CBV by actually measuring CBV. In the present experiments, we induced hemorrhagic shock and changed CBV by fluid resuscitation using a 6% hydroxyethyl starch (HES) solution to evaluate the accuracy of those parameters and CVP and mean arterial pressure (MAP).


Animal preparation

This study was approved by the Institutional Animal Care Committee of our university. Japanese male white rabbits weighing 2.5 to 3.0 kg were randomly divided into two groups. Those in group S (n = 6) had hemorrhaging induced, and those in group H (n = 10) had hemorrhaging induced followed by fluid resuscitation. The animals were housed in a room with a 12-h light/dark cycle and allowed access to food and water ad libitum before the study. They were moved to the operating room at least 30 min before starting anesthesia, and the surgical procedure was started at 9:00 AM. A continuous infusion of lactated Ringer's solution was given at 5 mL·kg−1·h−1. The animals were anesthetized with an intravenous injection of pentobarbital (30 mg·kg−1) via an auricular vein and placed in a supine position. After a tracheostomy was performed, a 3.5-mm (internal diameter) endotracheal tube was inserted midway along the trachea. Controlled mechanical ventilation was executed with a ventilator (Servo 900B; Siemens-Elema, Solna, Sweden) using zero end-expiratory pressure with a frequency of 60 cycles/min and an inspiratory-pause-expiratory ratio of 25:10:65. General anesthesia was maintained with an end-expiratory isoflurane concentration of 1.0% in humidified oxygen, with the fractional concentration of oxygen at 0.36. The end-expiratory isoflurane concentration was measured using a multigas monitor (Multicap; Datex, Helsinki, Finland) and maintained at 1.0% throughout the study. The minute ventilation volume was adjusted to achieve end-tidal CO2 between 35 and 40 mmHg, and this setting was maintained throughout the study. Muscular paralysis was achieved with a bolus injection of 0.2 mL·kg−1 vecuronium, followed by continuous infusion at a rate of 0.2 mL·kg−1·h−1.

For the purpose of good animal care, anesthesia quality was assessed to measure the 90% spectral edge frequency (SEF90) by monitoring the processed electroencephalogram (Drägel Medical, Lübeck, Germany). Chest wall lead electrocardiogram (ECG) and heart rate (HR) were monitored. The right femoral artery and left internal jugular vein were cannulated with 22- and 20-gauge polyethylene catheters, respectively, to monitor both arterial pressure and CVP. Arterial pressure, CVP, and airway pressure were measured using transducers (Uniflow; Baxter, Salt Lake, Utah) and recorded with a polygraph (RM6000; Nihon Kohden, Tokyo, Japan). Zeroing of the pressure transducers was made at the level of the operation table. To obtain blood samplings and induce hemorrhagic shock, the left femoral artery was cannulated with a 22-gauge polyethylene catheter, followed by a continuous infusion of 0.9% NaCl with added heparin at 1.0 mL·h−1. A 6-Fr catheter was placed into the bladder via the urethra to measure urine volume. A far-infrared heating mat (COMETII; Okamoto, Saitama, Japan) was used to maintain rectal temperature, which was monitored with a thermistor (MGA-III; Nihon Kohden), and kept between 38°C and 39°C throughout the procedure.

Experimental protocol

The experimental procedure was carried out according to the protocol shown in Figure 1. After collecting baseline data (HR, SAP, MAP, diastolic arterial pressure, CVP, peak airway pressure, end-tidal CO2, SEF90, and rectal temperature) at S1, HR and arterial pressure were recorded digitally using a magnetic optical disc for 5 min. Arterial blood was analyzed to determine pH, PaCO2, PaO2, base excess, glucose, and lactate levels using an ABL600 (Radiometer, Copenhagen, Denmark). The CBV and urine volume were also measured. Blood was withdrawn at a rate of 1 mL·kg−1·min−1 for 25 min via the left femoral artery in both groups. Five min after the start of the postbleeding period (S2), data collection and digital recording were performed in the same manner as at S1. In group H, HES (Kyorin Pharmaceutical, Tokyo, Japan), prewarmed to 38°C, was continuously infused with a mechanical pump at a rate of 1 mL·kg−1·min−1 for 25 min via an auricular vein. Simultaneously, digital recordings were performed throughout the infusion period and for 60 min during the postinfusion period. Data were collected at 5 (S3) and 60 (S4) min after fluid resuscitation. After completion of the experiments, all animals in both groups were euthanized by an excessive dose of intravenous pentobarbital.

Fig. 1
Fig. 1:
Experimental procedures. Timings for data sampling were as follows: S1, baseline; S2, 5 min after bleeding; S3, 5 min after termination of HES infusion; and S4, 60 min after termination of HES infusion. *The HES infusion was performed in group H. †A total of 4.5 mL of blood was drawn for mixing carbon monoxide (CO) gas for CBV measurement. The measured variables were HR, SAP, MAP, diastolic arterial pressure, CVP, peak airway pressure, and SEF90. Blood gas analysis included pH, PaCO2, PaO2, base excess, glucose, lactate, and hemoglobin (Hb). SEF indicates spectral edge frequency; UV, urine volume.

Measurement of CBV

We measured CBV using a carbon monoxide-labeled Hb (COHb) dilution method (9). Briefly, 4.5 mL of blood was drawn from the left femoral artery, which was repeated at the end of preparation, the beginning of graded bleeding, just after the infusion of HES, and 60 min after HES infusion. The samples were labeled by mixing CO gas for 5 to 10 min in a syringe with a heparin sodium solution added until the average concentration of COHb reached at least 90%. Simultaneously, the Hb concentrations in the CO-labeled blood samples were measured twice using a CO-oximeter (OSM3; Radiometer), with the animal mode set for rabbit. After obtaining two 0.3-mL samples for measurement of the baseline concentrations of COHb and Hb, 3 mL of a CO-labeled sample was injected via the internal jugular vein, followed by 1.5 mL of physiological saline over 50 s. Thereafter, samples were drawn at 4, 8, and 12 min after injection of the CO-labeled sample to measure the COHb concentration. The mean COHb concentrations were plotted on a semilogarithmic graph against time in min, and the zero time value was extrapolated. In a preliminary experiment, COHb levels were found to be measurable at 4, 8, and 12 min after injection of CO-labeled blood. In the present study, the concentration of Hb was substituted for hematocrit (10). The CBV was calculated using the following equation:

where Vi (mL) is the injected volume of CO-labeled blood; Hbi (g/dL) and COHbi (%) are the concentrations of Hb and COHb in CO-labeled blood, respectively; Hbb (g/dL) and COHbb (%) are the concentrations of Hb and COHb in circulating blood, respectively, before the injection of CO-labeled blood; and COHbe (%) is the extrapolated COHb concentration.

Data analysis

The recorded ECG was played back off-line to digitize the samples at 2 kHz using a digital bandpass filter between 14 and 40 Hz. There were no sings of arrhythmia in the ECG and SAP waveforms and no evidence of spontaneous respiration in the airway pressure waveform for any of the animals. Computations were performed using custom software that we developed, and R-R interval tachograms were made every 256 s. By resampling at 4 Hz, a 1,024-point instantaneous HR was made from the tachograms and subjected to a fast Fourier transformation using a Hanning window to obtain the power spectra. Spectra of less than 2.00 Hz were normalized by the square of the mean of HR. Spectral accuracy was confirmed by testing a sequence of simulated R-R intervals generated by an integral pulse frequency modulation model.

The power spectrum was calculated by integration of the spectral components of the total (TP, 0.04-2.00 Hz), low (LF, 0.04-0.40 Hz), and high (HF, 0.75-1.40 Hz) frequency band areas (11). These parameters and the LF/HF ratio were computed as a natural logarithm. The SAP data corresponding to each preceding R wave were used for SAP variability (SAPV) analysis in the same analytical manner as for the HR variability (HRV) analysis.

The respiratory variations in arterial pressure, including SPV, percentage SPV mean, and PPV, were calculated using the following formulas:

where SAPmax and SAPmin represent the maximum and minimum, respectively, SAP values during one respiratory cycle, and PPmax and PPmin represent the maximum and minimum, respectively, PP values during one respiratory cycle. The final SPV, percentage SPV mean, and PPV values were determined from the average of five values for each obtained during five consecutive respiratory cycles.

Statistical analysis

Data are presented as the mean ± SD. An unpaired Student t test was used to compare the groups, and repeated-measures analysis of variance followed by a Dunnett test were then used for intragroup alterations. Correlations between CBV/body weight (BW) and the parameters (PSSAPV, PSHRV, SPV, percentage SPV mean, PPV, CVP, and MAP) were analyzed using simple regression analysis. To appropriately evaluate the best regression model, an Akaike information criterion (AIC) (12) was used by adopting the lowest value as the best regression equation. Statistical significance was determined when P was less than 0.05.


All animals survived throughout the experimental procedures. There were no significant intergroup differences for the variables at S1 (Table 1). Hemorrhaging led to the development of bradycardia, hypotension, and metabolic acidosis in both groups at S2, with no significant intergroup differences observed. The HR was gradually restored, although hypotension and acidosis remained throughout in group S. The HES infusion recovered HR, SAP, and metabolic acidosis and also maintained CBV/BW until at least 1 h at S4 in group H.

Table 1
Table 1:
Serial changes of observed variables in groups S and H

The HF, LF, and TP of PSSAPV and percentage SPV mean and PPV changed similarly (Fig. 2). The HF of PSHRV was decreased after S3 in group S and after S2 in group H; however, there were no intergroup differences. The LF of PSHRV did not change throughout the study in both groups.

Fig. 2
Fig. 2:
Serial changes in spectral components of PSSAPV, PSHRV, SPV, %SPVmean, and PPV. Data are presented as the mean ± SD. *P < 0.05, †P< 0.001 vs. baseline (S1), ‡P < 0.05, §P < 0.001 between groups. PSSAPV; power spectrum analyses of systolic arterial pressure variability, PSHRV; power spectrum analyses of heart rate variability, SPV; systolic pressure variation, PPV; pulse pressure variation. S1, baseline; S2, 5 min after bleeding; S3, 5 min after termination of HES infusion; and S4, 60 min after termination of HES infusion. The power spectrum was calculated by integration of the spectral components of the total (TP, 0.04-2.00 Hz), low (LF, 0.04-0.40 Hz), and high (HF, 0.75-1.40 Hz) frequency band areas.

Correlations between CBV/BW and the parameters are shown in Figure 3. There were significant correlations between CBV/BW and TP (R2 = 0.491; P < 0.0001), HF (R2 = 0.428; P < 0.0001), and LF (R2 = 0.401; P < 0.0001) of PSSAPV, as compared with SPV (R2 = 0.119; P = 0.0056), percentage SPV mean (R2 = 0.383; P < 0.0001), and PPV (R2 = 0.333; P < 0.0001). In both groups, none of the components of PSHRV showed a correlation with CBV. The TP of PSSAPV was the most sensitive parameter of CBV, as AIC indicated the best value (Fig. 3).

Fig. 3
Fig. 3:
Simple regression analyses between CBV (in milliliters)/BW (in kilograms) and parameters and application of AIC.


This is the first known report of CBV being measured and then evaluated for its relationships with PSSAPV, PSHRV, SPV, and PPV, with AIC then applied. Our results demonstrated that TP, HF, and LF of PSSAPV reflected CBV more sensitively than SPV, percentage SPV mean, and PPV in rabbits under general anesthesia and mechanical ventilation. None of the parameters of PSHRV had a correlation with CBV.

Power spectrum analyses of systolic arterial pressure variability

This is the first report that TP of PSSAPV is the most sensitive parameter for reflecting CBV, although no study has yet evaluated the relationship between TP of PSSAPV and CBV. The HF of PSSAPV, which accounts for most of TP of PSSAPV, is reported to be affected by the respiratory pumping mechanism, including tidal volume, intrathoracic pressure, respiratory frequency, and positive end-expiratory pressure (13-15). The HF of PSSAPV is increased by an α-blocker (16), although it is decreased by a β-blocker (17) or angiotensin-converting enzyme-inhibitor (5). The effects of cholinergic blockage on HF of PSSAPV are controversial (5, 16, 18); however, the coherence between lung volume and HF of PSSAPV is unaffected by α-, β-, and cholinergic-blockers or a bilateral vagotomy. It is therefore suggested that the HF of PSSAPV is mainly generated by the respiratory pumping mechanism being subjected to a modulating action by the autonomic nervous system (13). The HF of PSSAPV is known to reflect CBV because it increases in parallel with graded hemorrhaging (6, 7). The HF of PSSAPV and SPV are similar in that they receive the respiratory effect strongly, although only a few studies have compared HF of PSSAPV with percentage SPV mean. It is also reported that percentage SPV mean more sensitively responds to graded hemorrhaging than HF of PSSAPV. In addition, administrations of α- and β-blockers suppress the response of percentage SPV mean and HF of PSSAPV in the presence of hemorrhage, whereas a cholinergic blockade has no effect on their response. Therefore, it is suggested that percentage SPV mean and HF of PSSAPV are unreliable indices of CBV when autonomic nervous activities, especially sympathetic activity, are unstable and fluctuating (8). The SPV and PPV also may not reflect CBV when peripheral resistance is changing because nitroprusside-induced hypotension increases SPV in normal volume status (19), whereas norepinephrine administration decreases SPV and PPV in hemorrhagic shock (20). In the present study, SPV was computed using 5-s signals, and PSSAPV was analyzed within 5 min. Although the TP of PSSAPV was considered appropriate, it should be noted that incorporation of arrhythmia and noise could easily affect the arterial pressure wave and subsequent SAPV analysis.

We found that LF of PSSAPV reflected the changes of CBV. The LF of PSSAPV is reported to be a better indicator of hypovolemia than HF of PSSAPV (21). In a previous study, hemorrhaging increased both LF and HF of PSSAPV, then isoflurane anesthesia depressed the LF of PSSAPV, whereas HF of PSSAPV responded poorly (22). Therefore, they concluded that autonomic nervous activity suppressed by isoflurane has a greater influence on LF of PSSAPV than HF of PSSAPV. Because LF of PSSAPV is influenced by sympathetic nervous activity (5), it seems unlikely to be an indicator of CBV.

Arterial pressure wave form distortion, determined according to the resonance frequency of the instrument applied to measure the wave, is another point of interest for analyzing the arterial pressure wave. However, in the present study, we measured the peak values of the waves, which were linearly augmented according to the proper resonance frequency of the instrument. The instrument used is commonly used in clinical practice, and the resonance frequency was considered admissible. We concluded that the spectral values obtained were appropriate because we normalized the data using a power spectral computation process.

SPV, percentage SPV mean, and PPV

Findings after application of AIC showed that the accuracy of SPV for reflecting CBV was the lowest, even when compared with CVP and MAP. The SPV is the sum of delta down (dDown) and delta up (dUp). The dDown has been reported to reflect hypovolemia better than SPV and was the difference between SAPmin during one cycle of mechanical ventilation and SAP during short apnea (19). In contrast, dUp reflecting hypervolemia (23) and acute ventricular failure (24) was shown to be the difference between SAPmax and SAP during short apnea. The SPV is inferior for reflecting CBV as compared with other arterial pressure variations, as both dDown and dUp may influence SPV.

We did not induce apnea in the animals because it is a complicated procedure. Apnea makes the venous return full; thus, dDown and other respiratory variations in arterial pressure derived during apnea are considered to be more reliable indicators of volume states than SPV (19). Recent studies have indicated that PPV is the best indicator of fluid responsiveness in respiratory variations of arterial pressure (4, 25); however, hemorrhage volume and that of fluid resuscitation in those studies were smaller than in the present study. When severe hypovolemia progresses, PPV gradually and significantly overestimates hypovolemia and PPV apnea, which is calculated using PP during apnea as a denominator. However, the range of this overestimation is not thought to have important clinical consequences (26). Therefore, in the present study, percentage SPV mean was substituted for percentage SPV derived during apnea (4, 8), and our findings indicated that percentage SPV mean was a more accurate indicator of volume status than PPV and SPV during severe hemorrhaging.

Power spectrum analyses of heart rate variability

We did not find any correlations between HRV parameters and CBV, which was considered because of a compensatory mechanism that became activated with 25 mL·kg−1 of bleeding during the experimental protocol. The effects of acute blood loss in nonanesthetized rabbits are similar to those seen in conscious humans (27), and it has been shown that reversible hypovolemic shock is associated with bradycardia in humans, whereas the irreversible stage of hypovolemic shock is associated with subsequent tachycardia (28). In the present study, hemorrhaging induced bradycardia and increased LF of PSSAPV from S2 to S4 in group S. Therefore, we considered that the blood loss in the animals represented a reversible stage of hemorrhagic shock.

It is important to note that analysis of HRV is an indirect means of evaluating cardiac autonomic nervous activity. The present results suggest that 25 mL·kg−1 of bleeding decreased vagal activity and had no effect on cardiac sympathetic activity because HF of PSHRV decreased, and LF/HF and LF of PSHRV had no significant changes after hemorrhage induction (5, 29).

A few other studies have analyzed HRV after severe hemorrhaging in manners similar to our study, although different results were obtained because the methods of hemorrhage induction, anesthesia, and timing for measuring HRV were different, as were the kinds of animals tested (30, 31). Nevertheless, those results suggest that fatal hemorrhaging decreases both cardiac sympathetic and vagal activities. It was previously demonstrated that LF of PSHRV, which decreases immediately after severe hemorrhaging, increases back toward normovolemic levels within 30 min (30). Therefore, a compensatory mechanism including peripheral vasoconstriction may attenuate the ischemic influence of the cerebral autonomic nervous center and efferent sympathetic cardiac activity.

To our knowledge, this is the first reported evaluation of the relationship of HRV analysis and fluid resuscitation with hemorrhaging. Cardiac parasympathetic activity, which decreased after severe hemorrhaging, showed an insignificant amount of change, whereas fluid resuscitation using HES restored CBV.


The SEF90 showed insignificant changes in both groups, suggesting that some compensatory mechanism maintained its level throughout the experiment because cerebral autoregulation maintained during hemorrhage-induced hypotension has been identified by SEF95 levels in dogs with isoflurane anesthesia (32). When hemorrhagic shock is compensated, hypovolemia does not alter the electroencephalographic effect of isoflurane assessed by SEF95, in contrast to several intravenous anesthetics (33). Therefore, as identified by SEF90 monitoring, the quality of anesthesia and cerebral autoregulation seemed to be maintained during the present experiments.


Respiratory variations in arterial pressure, including SPV and PPV, have limitations for application in clinical usage because they can only be assessed in mechanically ventilated and deeply sedated patients. In contrast, the representations of PSHRV and PSSAPV may be influenced by anesthesia, mechanical ventilation, and surgery. We anesthetized the animals because severe hemorrhagic shock induced in conscious animals would create an ethical problem, although this point is considered to be the maximum limitation in the present study for assessing the HRV and SAPV analyses. In a previous comparison of nonanesthetized rabbits, isoflurane anesthesia induced a marked decrease in LF and HF of PSHRV of 80% and 90%, respectively, independent of isoflurane concentrations at 0.5, 1.0, and 1.5 minimum alveolar concentrations (34). To minimize the effects of anesthesia and surgery, the isoflurane concentration was fixed, and SEF90 was continuously measured during the present experiments. Most patients in intensive care are sedated and mechanically ventilated, and LF and very low frequency of PSHRV and PSSAPV may predict the severity of illness and outcome in them (35). We speculated that evaluations of PSHRV and PSSAPV are useful in patients receiving anesthetics and mechanical ventilation.

In conclusion, we demonstrated that TP of PSSAPV more sensitively reflected changes of CBV than SPV, percentage SPV mean, and PPV in rabbits under anesthesia and mechanical ventilation. Furthermore, power spectral analysis of SAPV was considered useful to evaluate volume status as compared with conventional circulatory parameters, whereas none of the parameters associated with PSHRV and SEF90 had a correlation with CBV.


The authors thank the staff of the animal experiment facilities of Hiroshima University for their kind assistance.


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Power spectral analysis; heart rate variability; systolic pressure variation; pulse pressure variation; fluid resuscitation

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