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Anesthesia & Analgesia:
doi: 10.1213/01.ANE.0000053237.29264.01
CARDIOVASCULAR ANESTHESIA: Research Report

Stroke Volume Variation as an Indicator of Fluid Responsiveness Using Pulse Contour Analysis in Mechanically Ventilated Patients

Wiesenack, Christoph MD; Prasser, Christopher MD; Rödig, Gabriele MD; Keyl, and Cornelius MD

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Author Information

Department of Anesthesia, University Hospital, Regensburg, Germany

December 3, 2002.

Address correspondence and reprint requests to Christoph Wiesenack, MD, University Hospital, Department of Anesthesia, Franz-Josef-Strauss Allee 11, 93052 Regensburg, Germany. Address e-mail to christoph.wiesenack@klinik.uni-regensburg.de.

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Abstract

Assessment of cardiac performance and adequate fluid replacement of a critically ill patient are important goals of a clinician. We designed this study to evaluate the ability of stroke volume variation (SVV), derived from pulse contour analysis, and frequently used preload variables (central venous pressure and pulmonary capillary wedge pressure) to predict the response of stroke volume index and cardiac index to volume replacement in normoventilated cardiac surgical patients. We studied 20 patients undergoing elective coronary artery bypass grafting. After the induction of anesthesia, hemodynamic measurements were performed before (T1) and subsequent to volume replacement by infusion of 6% hydroxyethyl starch 200/0.5 (7 mL/kg) with a rate of 1 mL · kg−1 · min−1. Except for heart rate, all hemodynamic variables changed significantly (P < 0.01) after volume loading. Linear regression analysis between SVV at baseline (T1) and ΔSVV after volume application showed a significant correlation (r = −0.97;P < 0.01), whereas linear regression analysis between SVV (T1) and percentage changes of stroke volume index (r = 0.19) and cardiac index (r = 0.17) did not reveal a significant relationship between variables. The results of our study suggest that SVV derived from pulse contour analysis cannot serve as an indicator of fluid responsiveness in normoventilated cardiac surgical patients.

Assessment of cardiac performance and adequate fluid replacement of a critically ill patient are important goals of a clinician. Usually, a pulmonary artery catheter is placed for assessment of cardiac index (CI) and the estimation of intravascular volume status. Although cardiac filling pressures as central venous pressure (CVP) and pulmonary capillary wedge pressure (PCWP) are frequently used in clinical practice, they are often misleading in the assessment of fluid responsiveness. Measuring left ventricular end-diastolic area index by transesophageal echocardiography (1) or assessment of intrathoracic blood volume index (2) should provide an accurate estimation of existing hypovolemia; however, these techniques cannot be used routinely with most patients.

Systolic pressure variation (SPV), the difference between the maximal and minimal values of the systolic blood pressure during one mechanical breath, has been shown to be a valuable variable of cardiac preload in several clinical studies (3–5). SPV was considered to be a sensitive indicator of hypovolemia and to correlate with the response of CI to volume loading (6–10).

Pulse pressure variation (PPV), defined as the maximal pulse pressure less the minimum pulse pressure divided by the average of these two pressures, rather than SPV would more accurately reflect changes in left ventricular stroke volume (LVSV) because it is not influenced by the intrathoracic pressure-induced changes in arterial pulse (6–8).

A similar method for continuous assessment of fluid responsiveness is offered by the recently introduced PiCCO system (Pulsion Medical System, Munich, Germany). Arterial pulse contour analysis continuously calculates stroke volume index (SVI) and displays stroke volume variation (SVV), which is the change in percentage of SV calculated over the last 30 s. Comparable to SPV and PPV, SVV should reflect the ventilation-induced changes in LVSV and may serve as an indicator of fluid responsiveness, but until now, there has been only limited information about the value of this new variable (11–15).

This study was designed to evaluate the ability of SVV and frequently used preload variables (CVP and PCWP) to predict the response of SVI and CI to volume replacement in normoventilated cardiac surgical patients.

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Methods

After obtaining approval of the local Ethic Committee and with written informed consent, we studied 20 patients (16 men), aged 43–73 yr (mean, 60 yr), undergoing elective coronary artery bypass grafting. Patients with valvular heart disease, intracardiac shunts, peripheral vascular disease, preoperative dysrhythmias, and an ejection fraction of <50% were excluded from the study.

Anesthesia was induced with fentanyl 5 μg/kg followed by etomidate until loss of consciousness and pancuronium 100 μg/kg and maintained using 0.5% isoflurane, supplemented with bolus doses of fentanyl up to 20 μg/kg and pancuronium 50 μg/kg. Mechanical ventilation without positive end-expiratory pressure with a constant tidal volume of 10 mL/kg to an end-tidal Pco2 of 30–35 mm Hg was maintained at a fraction of inspired oxygen of 0.5 throughout the study. Peak airway pressures ranged from 14 to 22 mm Hg (mean, 17.6 mm Hg), whereas mean airway pressure ranged from 10 to 18 mm Hg (mean, 14.1 mm Hg).

A 4F arterial thermodilution catheter (PiCCO) was inserted via the femoral artery for monitoring of arterial blood pressure (MAP), SVI and SVV assessment derived from arterial pulse contour analysis, and for intermittent transpulmonary thermodilution CI mea-surements. After the induction of anesthesia, a 7.5F pulmonary artery catheter (Baxter Healthcare Corporation, Irvine, CA) was inserted via an 8.5F introducer into the right internal jugular vein for monitoring of CVP and PCWP (Siemens monitor SC 9000, Erlangen, Germany).

The arterial catheter was connected to a computer for pulse contour analysis (Pulsion Medical System). To calibrate the system, a reference thermodilution CI measurement was performed in triplicate to derive a calibration factor and the individual aortic compliance (16).

SVV is presented as the change in SV (in percent) calculated over the last 30 s according to:MATH where SVmax is the mean value of four maximum SVs of the last 30 s, SVmin is the mean value of four minimum SVs of the last 30 s, and SVmean is the mean value SVs of the last 30 s.

Equation U1
Equation U1
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CI, SVI, SVV, and hemodynamic variables were measured after the induction of anesthesia (T1). After volume replacement by infusion of 6% hydroxyethyl starch (HES) 200/0.5 (7 mL/kg) with a rate of 1 mL · kg−1 · min−1 (mean, 552 mL), a second measurement was performed. Measurements were achieved in a hemodynamic steady-state without any application of vasoactive drugs. SPV and PPV were not calculated in our investigation.

After the assessment of normal distribution by the Lilliefors modification of the Kolmogorov-Smirnov test, the Student’s t-test was used to compare variables. Linear regression analysis was performed between SVV at baseline (T1) and the percentage values of changes in SVV (ΔSVV), SVI (ΔSVI), and CI (ΔCI) and between the changes in preload indicating variables (SVV, CVP, and PCWP) and the changes in preload dependent variables SVI and CI. A P < 0.05 was regarded as significant.

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Results

Except for heart rate, all hemodynamic variables changed significantly (P < 0.01) after volume loading. CI, SVI, MAP, CVP, and PCWP increased, whereas SVV and systemic vascular resistance index decreased (Table 1).

Table 1
Table 1
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Linear regression analysis between SVV at baseline (T1) and ΔSVV after volume application shows a linear correlation (r = −0.97;P < 0.01), whereas linear regression analysis between SVV (T1) and percentage changes of SVI (r = 0.19) and CI (r = 0.17) did not reveal a significant correlation between variables, as presented in Figure 1.

Figure 1
Figure 1
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Linear regression analysis between changes of preload indicating variables SVV, CVP, and PCWP and changes of the preload-dependent variables SVI and CI did not show a significant correlation among variables.

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Discussion

Several studies have shown that SPV and PPV were valuable indicators of fluid responsiveness during mechanical ventilation (3–10), whereas cardiac filling pressures (CVP and PCWP) were of little help when deciding on adequate volume therapy. Accurate measurement of SPV and PPV is difficult, and the technique has not yet been made commercially available.

The new PiCCO system offers continuous assessment of SVV, which is simple to evaluate and may indicate fluid responsiveness during mechanical ventilation. Positive-pressure ventilation induces cyclic changes in LVSV, which are mainly related to the expiratory decrease in left ventricular preload because of the inspiratory decrease in right ventricular filling and ejection (7).

The results of our study suggest that SVV derived from pulse contour analysis cannot serve as a variable of fluid responsiveness in mechanically ventilated cardiac surgical patients as indicated by the lack of correlation between SVV at baseline and ΔSVI after volume administration. The high correlation between SVV at baseline and ΔSVV only demonstrates a relationship between the ventilation-associated SVV during baseline conditions and the amount of decrease in SVV subsequent to the infusion of a defined volume: the larger the amount of ventilation-associated SVV, the larger the decrease in SVV, which is of little clinical interest. Therefore, SVV can merely predict the amount of the decrease in SVV after volume correction considering the SVV value at baseline but not the extent of the increase in SVI.

According to Berkenstadt et al. (11), an increase in SVI by 5% or more cannot be expected in patients with SVV values <9.5% subsequent to volume loading of 100 mL of 6% HES. This is of evident clinical interest to reduce needless volume replacement, but these findings cannot be supported by the results of our study. In our investigation, the increase in SVI after volume loading was >10% in all patients, although five patients showed a SVV <9.5% at baseline. Larger amounts of applied volume can obviously increase SVI significantly despite SVV values <9.5%, but the extent of this increase cannot be predicted. In contrast to the study of Berkenstadt et al. (11), we examined cardiac surgical patients with potential impaired ventricular function caused by their coronary artery disease, which could be a possible explanation for the differences. According to Michard and Teboul (7), the increase in SV as a result of end-diastolic volume increase depends on ventricular function because a decrease in ventricular contractility decreases the slope of the relationship between end-diastolic volume and SV.

A recent study of Reuter et al. (15) could demonstrate the ability of SVV to predict myocardial responsiveness to volume administration, but the authors used large tidal volumes up to 15 mL/kg, which can possibly affect SVV assessment. SVV, as well as SPV and PPV, depends on a positive-pressure breath and therefore could be influenced by tidal volume (6,10,17,18). As Szold et al. (10) and the respiratory systolic variation test by Perel (18) demonstrate, increased tidal volumes lead to progressively larger decreases in LVSV (6). However, Feissel et al. (12) found that analysis of respiratory changes in aortic blood velocity and thus in LVSV is an accurate method for predicting the hemodynamic effects of volume expansion in septic shock patients receiving mechanical ventilation using tidal volumes of 8–10 mL/kg. Thus, tidal volume issues may not be the main reasons for a lack of agreement between studies.

Our results stand in contrast to the findings of other authors (11,12,14,15) who demonstrated that SVV can serve as a predictor of changes in SVI or CI caused by volume replacement in mechanically ventilated patients, but confirms Denault et al. (19) who stated that much of the power signal of the arterial pulse is altered by ventilation, making the measure of SVV by pulse contour technique questionable at best because it uses the power spectral analysis to estimate volume (13). Pulse contour-derived estimates of SVV calculate SV from the impedance characteristics of the pulse-pressure waveform, analyzing only the systolic part of the arterial pressure wave using a complex algorithm (16). A potential limitation of the variable constitutes that SVV calculation has never been validated under positive-pressure ventilation to reflect actual SVV (13), just a variation in an impedance modeled variable that itself may show variation independent of actual changes in SV.

The possibility that some of the patients in our study were vasoconstricted such that SVV would be minimal even in preload-responsive patients (6) has to be taken into account but could not be supported by our systemic vascular resistance index data at baseline.

A major limitation of the study is that other variables of fluid responsiveness such as SPV, PPV, or transesophageal echocardiography-derived assessment of aortic blood flow were not measured simultaneously with the SVV. Even with this methodological limitation, our data suggest that in this setting of preoperative cardiac surgery, the PiCCO-derived SVV was not a predictor of preload responsiveness. Nevertheless, further studies are required to confirm these findings by simultaneously evaluating additional variables. The determinants of volume responsiveness seem to be complex and not easily identified by measures of a single variable, such as arterial pulse contour-derived estimates of SVV.

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References

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