The measurement of cardiac output (CO) in a clinical setting is reserved for the high-risk patient because of the complexity, invasive nature, and expense of currently available techniques (1,2). However, there can be little argument that the availability of a simple and reliable method of measuring CO would make CO measurement more accessible to more patients (2). Impedance cardiography is an inexpensive and noninvasive approach to continuous CO measurement (3–5). The impedance method also detects blood-flow changes in the aorta (6), but how this information is translated to valid CO measurements remains a subject of much controversy. Ever since the method was developed by Kubicek et al. (5) more than 30 years ago, serious doubts have been cast on its reliability (7–9). In particular, comparisons with the thermodilution method in the intensive care setting have been disappointing (10–13).
The impedance method involves detecting small changes in electrical resistance during the cardiac cycle to a high-frequency low-amperage current passed through the thorax. The thoracic impedance changes cyclically as a function of time, and this results in a repetitive wave form. Several impedance variables are measured from the wave form, and these are used to estimate aortic blood flow (3–5). One of the most notable shortcomings of the impedance method is that we do not fully understand how the impedance changes during the cardiac cycle relate to stroke volume and CO. Several factors are known to affect the size and shape of the impedance wave form, such as changes in hemoglobin concentration (14), excessive lung fluid (15), and body habitus (16). Some investigators have also commented that impedance cardiography underestimates CO in the septic shock and vasodilated patient (11,17,18). Thus, changes in peripheral vascular resistance may also influence the size and shape of the impedance wave and CO measurements.
To investigate this hypothesis further, we developed an anesthetized dog model in which CO was accurately measured with an aortic flowprobe. We used this model to study the effects of pharmacologically induced changes in peripheral vascular resistance on impedance CO measurements. The impedance device used in the study was the RheoCardioMonitor (ACMA, Singapore) (19,20).
Ethical approval for the study was obtained from the Animal Research Ethics Committee of the Chinese University of Hong Kong. Male mongrel dogs were provided by the Laboratory Animal Services Centre of the Chinese University of Hong Kong. Anesthesia was induced by using IM ketamine 10% (5 mg/kg) and xylazine 2% (2 mg/kg) and was maintained throughout the experiment by using inhaled halothane 0.5%–1.0% in oxygen. The trachea was intubated, and the lungs were ventilated with a tidal volume of 10–15 mL/kg at a frequency of 12–15 breaths/min. Muscle relaxation was provided by rocuronium. IV access was secured in the forelimb and used to administer IV fluids (warmed saline at 2 mL · kg−1 · h−1) and drugs. The right femoral artery was cannulated to allow mean arterial blood pressure (MAP) recordings. Body temperature was maintained by covering the dog with an insulated blanket.
A thoracotomy at the left fourth intercostal space was performed. The pericardium was incised longitudinally to expose the aortic root. The ascending aorta was separated from the pulmonary artery for 2–3 cm by blunt dissection using the finger. The free fat surrounding the aorta was carefully removed. A snugly fitting flowprobe, either a 16- or 20-mm A-series ultrasonic probe (Transonic Systems Inc., Ithaca, NY), was placed around the ascending aorta, and ultrasonic gel was applied. A probe size was chosen that neither compressed the vessel wall nor was so loose that it allowed kinking. The probe cable was brought out of the thorax posteriorly. The pericardium was closed with sutures, a chest drain to underwater seal was inserted, the collapsed lung was reexpanded, and the chest wall was closed with sutures.
Aortic blood flow was measured by the flowprobe, which used a high-precision four-crystal array. It was connected to a T106 single-channel flowmeter (Transonic Systems) that also processed the transduced arterial blood pressure wave. The arterial blood pressure system was kept patent with a 10 mL/h saline infusion. A laptop computer collected the data and displayed it by using the software program WinDaq (DataQ Instruments, OH).
The RheoCardioMonitor consisted of six leads to be connected to the patient, a cardiograph module, a visual display unit, and a dedicated computer that analyzed the signal and stored data. An alternating 100-kHz 2-mA current was applied to the thorax of the dogs by 2 electrodes placed on the head and lower limb. The impedance to this current was detected by two pairs of opposing electrodes placed laterally on the mid neck and lower thorax, at the level of the diaphragm. Subcutaneous needle electrodes were used to improve the skin contact.
Stroke volume (SV) was calculated by the RheoCardioMonitor by using a modified Kubicek equation (5):
where L is the distance between the two current-detecting electrodes, Zo is the mean thoracic impedance, and ρ is the resistivity of the thorax. LVET is the left ventricular ejection time, dZ/dt(max) is the impedance index of flow, and Z(s − q) compensates for the asynchronism between the right and left ventricles, which are derived from the impedance wave form. The factor k in the calculation represents a complex formula based on the subject’s body habitus (20). The system was calibrated before use by imputing the dimensions of the thorax (thoracic length and the circumferences of the neck and lower thorax). CO was derived by multiplying by heart rate.
The anesthetized dog and measurement systems were allowed to stabilize for 30 min after preparation. The dog’s circulation was then first vasoconstricted by using an incrementally increasing infusion of phenylephrine 1–5 μg · kg−1 · min−1. Vasodilation was achieved by increasing the concentration of inhaled halothane (2%–4%) until the MAP decreased to 60 mm Hg. Finally, vasoconstriction was achieved by using adrenaline 0.1–1.0 μg · kg−1 · min−1. The dog’s circulation was allowed to return to baseline for 5 min between treatments. Data collection was restricted to 1–2 h to minimize any drift in measurements by the RheoCardioMonitor.
The flowmeter and RheoCardioMonitor measurements were recorded at 10-s intervals, which were subsequently transferred to Microsoft Excel (Redmond, WA), where they were averaged to provide data at 1-min intervals. These data were inspected for any obvious outliers that differed by >50% from adjacent values. They were replaced by values that were more in keeping with the general trend of the data: the average of adjacent values. Outliers accounted for 1%–5% of data points depending on the particular experiment. The total peripheral resistance (TPR) was calculated by the equation TPR = MAP × 80/COFP (resistance units), where COFP was the CO from the flowprobe. The offset or bias between CO measurements was calculated by finding the difference between the paired measurements (COIC − COFP) (L/min), where COIC was the CO from the RheoCardioMonitor.
For each experiment, CO was measured by each method for the range of circulatory variables tested. The percentage changes for these variables were calculated from the range of values over the minimum value. Time plots and accompanying scattergrams were created to investigate the relationships between TPR and the offset between the two methods of measuring CO (Fig. 1). Correlation and regression analysis was used to determine the relationship between the offset and TPR. This was performed with StatView for Windows (SAS Institute Inc., Cary, NC).
Eight dog experiments were performed. The mean (range) weight of the dogs was 19.5 kg (16–26 kg), and data collection for each experiment lasted 81 min (58–106 min). A total of 547 data sets were collected. The range of hemodynamic variables tested in each dog is shown in Table 1. The average percentage change [mean (range)] in the values measured was 190% for COFP (89%–425%), 129% for MAP (89%–194%), 136% for heart rate (20%–210%), and 266% for TPR (94%–580%).
COIC measurements underestimated CO when TPR decreased and overestimated CO at higher values for TPR. This dependence on TPR is demonstrated in Figure 1, in which COIC underestimated CO between 20 and 50 min, when the dog in Experiment 1 was vasodilated by the administration of halothane. A scattergram of measurement bias against TPR confirms this effect. There was a significant linear correlation in all eight experiments between the measurement bias and the logarithm of the TPR (Fig. 2). Correlation coefficients for regression of measurement bias against TPR ranged from 0.46 to 0.89 (P < 0.0001) (Table 2). Overall, there was a mean (sd) 0.62 L/min (0.18 L/min) change in the measurement bias each time the TPR was halved or doubled (Table 2). This was equivalent to a 34% shift in COIC, derived from the mean offset (0.62 L/min) divided by the overall mean experimental COFP (1.8 L/min).
The main finding of this study was that COIC measurements are altered by changes in peripheral resistance, such that vasodilation causes CO to be underestimated and vasoconstriction results in overestimation (Figs. 1 and 2). Previous investigations in this area have mainly evaluated the degree of agreement between impedance measurement and a reference method without regard for the potential influence of peripheral resistance (21).
In all eight experiments, the bias between the impedance and reference methods was strongly correlated with the peripheral resistance (r = 0.46–0.89; P < 0.0001) (Table 2). This finding helps to explain why the impedance method generally does not yield good agreement with other methods of CO measurement, such as thermodilation, when studied in critically ill patients, in whom the peripheral resistance may be very variable. Such patients may be excessively vasodilated because of sepsis or vasoconstricted because of stress or vasopressor administration. Furthermore, we found that halving or doubling the peripheral resistance offset the readings by more than 0.6 L/min, thus introducing an error of 34%. When this error is added to the errors due to other factors that influence impedance measurements (14–16), it provides an explanation for the excessive measurement bias of 40%–60% found in some validation studies (10–12). Clinically acceptable differences in the measurements should not exceed 20%–30% (13).
In studies involving healthy volunteers, peripheral resistance tends to vary less. This accounts for studies that indicate that impedance cardiography works reliably in healthy subjects. The greatest changes in TPR normally seen in volunteer studies are due to postural reflexes evoked by head-up tilting or standing erect, which accounts for up to a 50% increase in TPR (22–24). However, estimates based on data from the present study suggest that standing would change the measurement bias by <20% (i.e., halving or doubling the TPR shift the bias by 34%). Thus, peripheral resistance probably does not vary sufficiently in most volunteer studies to significantly affect impedance measurements.
When using the RheoCardioMonitor, we found that the 10-second measurements of CO varied greatly. Whether this is a problem specific to the RheoCardioMonitor or whether it is present in impedance cardiographs in general is unclear, because the impedance signal from which the impedance data are derived is very fragile and thus difficult to measure with any precision and consistency. The quality of the impedance signal was improved in this study by the use of subcutaneous needle electrodes, and the variability between measurements was also reduced by averaging the data at one-minute intervals and eliminating any obvious outliers, because they were deemed false or artifactual data. These measures helped to improve the resolution of any trends within the data, such as the dependence on TPR. The wide variability of the data can be clearly seen (Fig. 2).
Aortic blood flow is one of the main sources of the impedance signal (4). A study in which the heart was electrically isolated from the thorax showed that contraction of the heart contributed little to the overall impedance change, while the main impedance signal originated from volume changes in the aorta and pulmonary vessels (25). Wang and Patterson (26) mathematically modeled the thorax and estimated that arterial and venous blood flow contributes 57%, the lungs contribute 39%, and structural changes contribute 4% to the overall signal. Although the source of the impedance signal is known, the mechanism by which the impedance signal is produced has not been fully elucidated. Both Kubicek (6) and Visser (27) have suggested that expansion of the aorta during systole is responsible for the impedance change. Visser (27) has further suggested that as blood accelerates into the aorta, its resistivity decreases, thus also contributing to the impedance changes (27). However, these theories on the origin of the impedance signal have never been confirmed through in vivo experiments.
The expansion theory of the aorta as an explanation of the source of the impedance signal is in keeping with our findings. The aorta is a prominent structure within the thorax. It has a high conductivity relative to other tissues, because it contains blood. Thus, any change in aortic diameter should alter thoracic impedance and, during systole, should cause a transitory change in thoracic impedance. Impedance cardiography detects the impedance change and uses it to estimate CO. The validity of this measurement is based on the assumption that aortic distention is directly related to aortic blood flow, and, to an extent, this is true because of the pulsatile nature of aortic blood flow. However, other factors also influence aortic distension, such as vessel wall elasticity and the rate of increase in intraluminal pressure. The latter is dependent on the afterload or compliance of the arterial tree, of which the peripheral vascular resistance is a major determinant. Therefore, if aorta expansion is the main source of the impedance signal, one should not be surprised if variations in TPR alter COIC.
In summary, this study shows the effect of peripheral resistance on COIC measurements. It supports the theory that distention of the aorta is the main source of the impedance signal, and it provides an explanation for the failure of reliable COIC in the critically ill patient. For impedance cardiography to become a useful clinical tool for CO measurement in sick patients, the algorithms used to calculate COIC will need to be adapted to compensate for significant changes in MAP and peripheral resistance.
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