British Journal of Anaesthesia, 2002, Vol. 88, No. 1 124-126
© 2002 The Board of Management and Trustees of the British Journal of Anaesthesia
Short Communications |
Optimizing fluid therapy in mechanically ventilated patients after cardiac surgery by on-line monitoring of left ventricular stroke volume variations. Comparison with aortic systolic pressure variations
1Department of Anaesthesiology and 2Department of Cardiac Surgery, Ludwig-Maximilians-University, Großhadern University Hospital, Marchioninistr. 15, D-81377 Munich, Germany*Corresponding author
Accepted for publication: September 12, 2001
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Abstract |
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Background. Mechanical ventilation causes changes in left ventricular preload leading to distinct variations in left ventricular stroke volume and systolic arterial pressure. Retrospective off-line quantification of systolic arterial pressure variations (SPV) has been validated as a sensitive method of predicting left ventricular response to volume administration. We report the real-time measurement of left ventricular stroke volume variations (SVV) by continuous arterial pulse contour analysis and compare it with off-line measurements of SPV in patients after cardiac surgery.
Methods. SVV and SPV were determined before and after volume loading with colloids in 20 mechanically ventilated patients.
Results. SVV and SPV decreased significantly after volume loading and were correlated (r=0.89; P<0.001). Changes in SVV and changes in SPV as a result of volume loading were also significantly correlated (r=0.85; P<0.005). Changes in SVV correlated significantly with changes in stroke volume index (SVI) (r=0.67; P<0.005) as did changes in SPV (r=0.56; P<0.05). SVV determined before volume loading correlated significantly with changes in SVI (R=0.67; P <0.005). Using receiver operating characteristics curves, the area under the curve was statistically greater for SVV (0.824; 95% confidence interval: [CI] 0.64–1.0) and SPV (0.81; CI: 0.62–1.0) than for central venous pressure (0.451; CI: 0.17–0.74).
Conclusions. Monitoring of SVV enables real-time prediction and monitoring of the left ventricular response to preload enhancement in patients after cardiac surgery and is helpful for guiding volume therapy.
Br J Anaesth 2002; 88: 124–6
Keywords: heart, left ventricular preload; heart, left ventricular response; heart, systolic pressure variation; heart, central venous pressure; measurement techniques, pulse contour analysis; monitoring, haemodynamic
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Introduction |
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Correct assessment of hypovolaemia and the decision to undertake volume resuscitation is often difficult to make clinically. This is especially so in critically ill patients with compromised myocardial or pulmonary function, or with systemic inflammation from sepsis or cardiac surgery using cardiopulmonary bypass. In these patients, an adequate preload is of utmost importance for optimizing cardiac performance and organ perfusion. Positive airway pressures produced by mechanical ventilation are known to cause intermittent changes in biventricular preload which lead to distinct left ventricular stroke volume variations (SVV) and, in consequence, to systolic arterial pressure variations (SPV).1 Excessive SPV, visible as undulations in the arterial pressure curve trace, are a well recognized clinical sign of hypovolaemia. As demonstrated in earlier investigations, off-line quantification of SPV is a sensitive method of predicting left ventricular response to volume administration.2 3 Nevertheless, real-time and continuous quantification of SPV has not been determined. Arterial pulse contour analysis, which has been clinically validated for continuous cardiac output measurement,4 now enables continuous quantification of real-time SVV, which causes SPV. Berkenstadt and colleagues recently reported measurement of SVV to predict fluid responsiveness in patients undergoing brain surgery.5 However, to our knowledge, there are no published data on a comparison of SVV and SPV.
We investigated the relation between SVV and the haemodynamic response of the left ventricle to volume loading compared with the SPV determined off-line in 20 mechanically ventilated patients after cardiac surgery using cardiopulmonary bypass.
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Methods and results |
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With the approval of the local institutional ethics committee and informed consent, 20 patients were studied after elective cardiac surgery. Prior to surgery, each patient had a central venous catheter and a 4F thermistor-tipped arterial catheter (PV 20L16, Pulsion Medical Systems AG, Munich, Germany) inserted into the femoral artery and advanced into the distal abdominal aorta. This catheter was connected to a bedside haemodynamic monitor for arterial pulse contour analysis (PiCCO 4.1, Pulsion Medical Systems AG, Munich, Germany). Cardiac output and stroke volume were measured by the transcardiopulmonary thermodilution technique (performed in triplicate).4 Raw data were indexed using the body surface area to calculate thermodilution stroke volume index (SVI). After initial calibration of the arterial pulse contour cardiac output by thermodilution, cardiac output, pulse contour cardiac output and pulse contour stroke volume were recorded continuously. SVV, demonstrating the variations in the beat-to-beat stroke volume around the mean during the respiratory cycle, was assessed using an algorithm that utilizes a continuously sliding time window of 30 s to calculate the mean stroke volume. This time window was divided into four periods of 7.5 s; within each window, the highest and the lowest value of stroke volume were used to calculate SVV.
For the off-line calculation of SPV, we recorded the digitalized trace of the arterial pulse wave on a computer connected to the haemodynamic monitor. We used the same individual time window of 30 s divided into four periods of 7.5 s, which was analysed for the corresponding value of SVV and determined the highest and lowest value of systolic arterial pressure to calculate SPV.
Drug therapy was not changed within the study period. After recording of central venous pressure, thermodilution SVI and SVV, and a recording of the arterial pressure curve trace for later determination of SPV, volume loading was performed over 10 min using 3.5% oxypolygelatine 20 ml x body mass index (mean 548 ml). The measurements were then repeated.
Statistical analysis of the data was performed on a standard personal computer using SPSS for Windows 10.0 run under Windows NT. All variables are expressed as mean (SD). Correlation of haemodynamic variables and their changes were assessed using Pearson’s correlation. Receiver operating characteristics (ROC) curves were calculated with varying discriminating thresholds for each variable to assess the ability to predict volume responsiveness.6
All patients tolerated the study treatment well. Overall, the thermodilution SVI increased from 40 (9) ml m–2 to 50 (9) ml m–2, whereas SVV decreased from 23 (7) to 11 (3)%, and SPV from 16 (7) to 6 (3) mm Hg. Central venous pressure increased significantly from 7 (2) to 10 (3) mm Hg. Linear regression analysis of SVV and SPV is shown in Figure 019F1A (R=0.89; P<0.001). Changes (%) in SVV (
SVV) and SPV (SPV) as a result of volume loading correlated significantly (R=0.85; P<0.005). Comparison of SVV and SPV using a Bland–Altman plot is shown in Figure 019F1B.7 Changes in thermodilution SVI (SVI) correlated significantly with SVV (R=0.67; P<0.005) and SPV (R=0.56; P<0.05). To investigate the ability of each variable to predict volume responsiveness, SVI was correlated with values of SVV determined before volume loading (r=0.67; P<0.005), as well as with values of SPV before volume loading (r=0.60; P<0.01). ROC curves for central venous pressure, SPV and SVV were generated with varying discriminating thresholds for each variable. Patients were classified as responders to volume loading if the increase in SVI was >15% (n=13), or as non-responders (n=7), according to Stetz et al.8 When comparing the areas under the ROC curves, the area for SVV (0.83; 95% confidence intervals [CI]: 0.64–1.0) and SPV (0.81; CI: 0.62–1.0) did not differ significantly, whereas the area for central venous pressure (0.42; CI: 0.17–0.74) was significantly smaller (P<0.001).
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Comment |
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These results primarily demonstrate the ability of continuous and real-time measurement of SVV by arterial pulse contour analysis to predict and assess the left ventricular response to volume loading in cardiac surgery patients. So far, directly accessible information on whether the sarcomeres of the left ventricle are still in the volume-dependent part of the Starling curve or have already reached their optimal fibre length (the latter describing ‘preload’ in the pure physiological sense),9 cannot be provided by routine clinical monitoring. SPV and its retrospective off-line quantification for assessment of volume dependency has been validated,2 3 as have arterial pulse pressure changes.10 The technique of arterial pulse contour analysis enables us to quantify reliably the underlying SVV causing SPV and pulse pressure changes. Moreover, this is possible by an on-line technique using SVV as a continuous bedside variable. As demonstrated here, SVV offers continuous unique functional data on the patient’s individual myocardial Starling curve and preload status, and thus enables prediction of volume responsiveness and monitoring of the effect of fluid loading. SVV is therefore a clinically useful and feasible bedside device for real-time functional preload monitoring in cardiac surgery patients.
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References |
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1 Jardin F, Farcot JC, Gueret P, Prost JF, Ozier Y, Bourdarias JP. Cyclic changes in arterial pulse during respiratory support. Circulation 1983; 83: 266–74
2 Perel A, Pizov R, Cotev S. Systolic blood pressure variation is a sensitive indicator of hypovolemia in ventilated dogs subjected to graded hemorrhage. Anesthesiology 1987; 67: 498–502[Web of Science][Medline]
3 Tavernier B, Makhotine O, Lebuffe G, et al. Systolic pressure variation as a guide to fluid therapy in patients with sepsis-induced hypotension. Anesthesiology 1998; 89: 1313–21[Web of Science][Medline]
4 Goedje O, Hoeke K, Lichtwarck-Aschoff M, et al. Continuous cardiac output by femoral arterial thermodilution calibrated pulse contour analysis: comparison with pulmonary arterial thermodilution. Crit Care Med 1999; 27: 2407–12[Web of Science][Medline]
5 Berkenstadt C, Margalit N, Hadani M, et al. Stroke volume variation as a predictor of fluid responsiveness in patients undergoing brain surgery. Anesth Analg 2001; 92: 984–9
6 Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148: 839–43
7 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1: 307–10[Web of Science][Medline]
8 Stetz CW, Miller RG, Kelly GE, Raffin TA. Reliability of the thermodilution method in the determination of cardiac output in clinical practice. Am Rev Respir Dis 1982; 26: 1001–4
9 Sonnenblick EH, Strobeck JE. Current concepts in cardiology: Derived indexes of ventricular and myocardial function. N Engl J Med 1977; 296: 978–82[Web of Science][Medline]
10 Michard F, Boussat S, Chemla D, et al. Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med 2000; 162: 134–8
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