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Cardiovascular physiology

Predicting stroke volume and arterial pressure fluid responsiveness in liver cirrhosis patients using dynamic preload variables

A prospective study of diagnostic accuracy

Wu, Chun-Yu; Cheng, Ya-Jung; Liu, Ying-Ju; Wu, Tsung-Ta; Chien, Chiang-Ting; Chan, Kuang-Cheng on behalf of the NTUH Center of Microcirculation Medical Research (NCMMR)

Author Information
European Journal of Anaesthesiology: September 2016 - Volume 33 - Issue 9 - p 645-652
doi: 10.1097/EJA.0000000000000479
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Abstract

Introduction

Liver cirrhosis patients present unique haemodynamic characteristics such as hyperdynamic circulation, low systemic vascular resistance (SVR), high arterial compliance and peripheral vasodilation,1–3 which often interfere with haemodynamic monitoring. A fluid challenge remains one of the most common treatments for improving blood flow and maintaining arterial pressure. Therefore, it is crucial for a caregiver to predict whether a fluid challenge will elicit ‘fluid responsiveness’ in stroke volume (SV) and arterial pressure.4 Compared with conventional static fluid variables such as central venous pressure, dynamic fluid variables, which are derived from SV or pulse pressure fluctuations secondary to changes in intrathoracic pressure during volume-controlled mechanical ventilation, have been consistently reported to be superior predictors of SV fluid responsiveness in various surgical settings.5,6

Dynamic fluid variables are either pressure-based [(pulse pressure variation (PPV)], flow-based [SV variation (SVV)] or volume-based [plethysmographic variability index (PVI)]. For a given ventilator-induced change in SV, these three types of fluid variables may vary according to vascular compliance at the measurement level. However, the predictive ability of each dynamic preload variable is highly dependent on the reflection of normal arterial system compliance.7,8 Therefore, the ability of PPV, SVV and PVI to predict SV fluid responsiveness in liver cirrhosis patients remains unclear.

In addition to SV optimisation, arterial blood pressure optimisation is a critical component of haemodynamic stability, and differentiating arterial vasodilatation from hypovolaemia as the cause of hypotension is crucial; hence, a variable closely representing vascular tone is desirable. SVR is the variable most commonly used to describe vascular tone but SVR may not facilitate treating liver cirrhosis patients because this patient group often presents with a low SVR.3 The perfusion index, which is calculated as the ratio of pulsatile to non-pulsatile blood volumes and automatically calculated using a pulse oximeter, is a measure of the vascular tone in peripheral tissue9 and has been reported to predict the incidence of spinal anaesthesia-induced hypotension during caesarean section in parturient women,10 which is another population characterised by a low SVR. Recently, in patients undergoing mechanical ventilation, including critically ill patients,11 and in patients undergoing hepatic surgery, the PPV/SVV ratio has been proposed to reflect dynamic arterial elastance, thus facilitating the prediction of arterial pressure responsiveness to fluid, when such patients experience a fluid challenge.12 To date, no study has investigated the ability of these vascular tone variables to predict arterial pressure fluid responsiveness in liver cirrhosis patients.

In this study of liver cirrhosis patients, we investigated the ability of dynamic fluid variables, namely, PPV, SVV and PVI, to predict SV fluid responsiveness and assessed the ability of vascular tone variables, namely, the SVR index (SVRI), perfusion index and PPV/SVV ratio, to predict arterial pressure responsiveness to fluid.

Patients and methods

Ethical approval for this study (201309024RIND) was provided by the Research Ethics Committee of National Taiwan University Hospital, Taipei, Taiwan (Chairperson: Professor Hong-Nerng Ho) on 4 October 2013. After obtaining written informed consent adult recipients of a living donor orthotopic liver transplant were enrolled consecutively from November 2013 to April 2015. The exclusion criteria were a history of pulmonary resection, chronic respiratory insufficiency, left ventricular ejection fraction (LVEF) of less than 60%, pulmonary hypertension or arrhythmia (NCT01971333).

General anaesthesia was induced with intravenous (i.v.) fentanyl 1.2 μg kg−1 with etomidate 0.3 mg kg−1, with cisatracurium 0.15 mg kg−1 administered to obtain muscle relaxation. Anaesthesia was maintained in a standard manner with desflurane in an air/oxygen mixture and i.v. injections of fentanyl and cisatracurium. During surgery, the anaesthetic depth was maintained by keeping the bispectral index between 40 and 60. To facilitate the maintenance of normocapnia, monitored with an end-tidal CO2 monitor, mechanical ventilation was set to a tidal volume of 8 ml kg−1 with a respiratory rate of 10 to 15 breaths min−1 and a positive end-expiratory pressure of 5 cmH2O. The respiratory settings were not changed throughout the measurements.

Each patient received standard monitoring using a Philips Intellivue MP 70 monitor (Philips, Suresnes, France). After induction of general anaesthesia, a triple-lumen 5.5-FG catheter (Arrow central venous catheter; Teleflex Life Sciences Ltd., Athlone, Ireland) was inserted into the right internal jugular vein. A 4-FG thermistor-tipped arterial catheter (Pulsiocath thermodilution catheter; Pulsion Medical Systems, Munich, Germany) was inserted into the right femoral artery, advanced to the abdominal aorta and connected to the PiCCOplus system monitor: Feldkirchen Germany (version 7.0; Pulsion Medical Systems). The PiCCO system with the transpulmonary thermodilution technique can be used to generate the cardiac index, SV index (SVI) and SVRI, which are comparable to those generated using a pulmonary artery catheter.13–15 Continuous SVI measurement was initiated after the system was initially calibrated by injecting 20 ml of ice-cold normal saline (<8°C) through the central venous catheter (transpulmonary thermodilution) three times, and further calibration was performed hourly. The cardiac index was calculated as SVI × heart rate.

The Masimo Radical 7 co-oximeter (version 7.8; Masimo Corp., Irvine, California, USA) uses a finger clip to measure arterial oxygen saturation non-invasively on the basis of transcutaneous multi-wavelength analysis. The Masimo sensor was attached to the right index finger according to the manufacturer's instructions, while the i.v. cannula was inserted in the left upper limb.

SVV and PPV were calculated using the following formulae: SVV (%) = [(SVmax − SVmin)/SVmean] × 100 and PPV (%) = [(PPmax – PPmin)/PPmean] × 100. Using the PiCCOplus system, we measured SVmax and SVmin [or pulse pressure (PP)max and PPmin] as the mean values of the four extreme values of SV (or PP) during measurement from the femoral artery over 30 s. The SVmean (or PPmean) was recorded as the average value during this period.

The PVI, which is based on the perfusion index, was obtained using the Masimo Radical 7 SET co-oximeter. The PVI was calculated as [(perfusion indexmax − perfusion indexmin)/perfusion indexmax] × 100 over a period sufficient to include multiple respiratory cycles.

Vascular tone variables including the SVRI, perfusion index and PPV/SVV ratio were measured. The SVRI was calculated as (mean arterial pressure − central venous pressure) × 80/cardiac index. The perfusion index was calculated as the ratio of pulsatile to non-pulsatile blood volumes and was automatically calculated using the Masimo Radical 7 SET co-oximeter.

After the PiCCO monitor was set up, the patients were allowed to stabilise for 15 min. Subsequently, they received a fluid challenge of 10 ml kg−1 of 0.9% normal saline over 15 min, during the surgical preparation before skin incision. An additional saline challenge was administered 2 h after the surgical incision. During the dissection phase, each patient received a basal 0.9% normal saline infusion at a rate of 5 ml kg−1 h−1.

Haemodynamic data were recorded for one minute before (baseline) and 5 min after each fluid challenge. The averages of the haemodynamic measurements during these one minute periods before and after the fluid challenge were used for statistical analysis. Since the monitor updates the readings every 20 seconds, the three readings were averaged. During these measurements of the haemodynamic variables, surgery stopped for 1 min without any stimulation to the patient and without clamping or unclamping major vessels. During the investigation period (the 22 minute period when haemodynamic data was being recorded and the fluid challenge administered) , inotropes or vasopressors were not administered to any patient. Patients were considered SV responders if their SVI increased by at least 15% after the fluid challenge. Patients were considered arterial pressure responders if their mean arterial pressure increased by at least 15% after the fluid challenge.

Statistical analysis

Normally distributed data are expressed as mean ± SD and those which were not normally distributed as median (IQR). A Student's t-test or Mann–Whitney test was used to compare the haemodynamic variables between the responders and non-responders. A paired t-test or Wilcoxon signed rank test was used to compare haemodynamic variables before and after the fluid challenges. A Pearson correlation test was used to investigate the correlation coefficients among PPV, SVV and PVI and the correlation coefficients between percentage changes in the mean arterial pressure and SVI after the fluid challenges compared with those before the fluid challenges.

To determine the ability of the PPV, SVV, PVI and central venous pressure to predict SV and fluid responsiveness and the ability of the PPV/SVV ratio, perfusion index and SVRI to predict arterial pressure and fluid responsiveness, areas under the receiver operating characteristic curves (AUROCs) were calculated and compared using the Delong and Clarke–Pearson method.16 To calculate the sample size, we considered that most previously reported dynamic fluid variables had AUROCs of approximately 0.85 and then tested the probability of rejecting the null hypothesis that AUROC is 0.5. According to our pilot study, in which the number of SV responders was assumed to be half the number of SV non-responders, we calculated that at least seven responder and 14 non-responder challenges were required at a significance level of 0.05 and a power of 0.8. Statistical analysis was performed using MedCalc (MedCalc, Inc., Mariakerke, Belgium).

Results

We consecutively enrolled 37 patients; six patients were excluded because of impaired LVEF or arrhythmia. Table 1 summarises patient characteristics. In total, 62 fluid challenges were performed and there were 23 responders and 39 non-responders for SV fluid responsiveness and 16 responders and 46 non-responders for arterial pressure fluid responsiveness (Fig. 1).

Table 1
Table 1:
Patients’ characteristics
Fig. 1
Fig. 1:
Study flow chart. ‘Responders’ had increases in SV or MAP of at least 15% after fluid challenge. LVEF, left ventricular ejection fraction; MAP, mean arterial pressure; SV, stroke volume.

Before the fluid challenges, all three dynamic preload variables were significantly higher in the SV responders than in the non-responders (all P < 0.05; Table 2). After the fluid challenges, a significant decrease was observed in all three dynamic preload variables in the SV responders and non-responders, except that the SVV did not change significantly in the non-responders (Table 2). PPV/SVV ratio before the fluid challenges was comparable between the SV responders and non-responders. No significant change was observed in the PPV/SVV ratio before or after the fluid challenges in the SV responders and non-responders (Table 2).

Table 2
Table 2:
Changes in haemodynamic parameters before and after fluid loading in stroke volume fluid responders and non-responders

Before the fluid challenges, no significant difference was observed in any of the three dynamic preload variables in the arterial pressure responders and non-responders (Table 3). After the fluid challenges, a significant decrease was observed in all three dynamic preload variables in the arterial pressure responders and non-responders. The PPV/SVV ratio before the fluid challenges was comparable between the arterial pressure responders and non-responders. No significant change was observed in the PPV/SVV ratio before or after the fluid challenges in the arterial pressure responders and non-responders (Table 3).

Table 3
Table 3:
Changes in haemodynamic parameters before and after fluid loading in mean arterial pressure fluid responders and non-responders

The AUROCs (95% confidence interval) calculated for predicting SV fluid responsiveness in liver cirrhosis patients were 0.794 (0.673 to 0.886) for PPV, 0.754 (0.628 to 0.854) for SVV and 0.800 (0.679 to 0.891) for PVI (Fig. 2). No significant difference was observed in AUROCs of any dynamic preload variable. The cut-off values for the PPV, SVV and PVI were 10% (sensitivity 78.3%, specificity 79.5%), 12% (sensitivity 69.6%, specificity 71.8%) and 11% (sensitivity 95.7%, specificity 59.0%), respectively. In contrast, the AUROC of central venous pressure did not significantly predict SV fluid responsiveness.

Fig. 2
Fig. 2:
Receiver operating characteristic curves describing the ability of PPV, SVV and the PVI to predict a fluid challenge-induced increase of at least 15% in the stroke volume index. PPV, pulse pressure variation; PVI, plethysmographic variability index; SVV, stroke volume variation.

Each vascular tone variable investigated in this study failed to predict arterial pressure fluid responsiveness in liver cirrhosis patients. A sub-analysis showed that these vascular tone variables still failed to predict arterial pressure fluid responsiveness in the SV responders (patients in preload-dependent status).

A significant correlation was observed among the three dynamic preload indices before and after the fluid challenges (Table 4). PPV and SVV were highly correlated before and after the fluid challenges (before, r = 0.79; after, r = 0.90). The PVI and PPV were mildly correlated before the fluid challenges (r = 0.49) and moderately correlated after the fluid challenges (r = 0.60). The PVI and SVV were mildly correlated before the fluid challenges (r = 0.48) and moderately correlated after the fluid challenges (r = 0.62).

Table 4
Table 4:
Agreements between three dynamic preload variables before and after fluid challenges

Compared with the dynamic preload variables, the static haemodynamic changes were less evident. Before the fluid challenges, the heart rate, central venous pressure, SVRI and perfusion index were comparable between the responders and non-responders in SV fluid responsiveness (Table 2) and those in arterial pressure fluid responsiveness (Table 3). Compared with the SV responders, the SV non-responders had a higher baseline SVI [45 (40 to 51) vs. 36 (33 to 45) ml m−2, P < 0.01], higher baseline cardiac index (3.80 ± 1.13 vs. 3.12 ± 0.71 l min−1 m−2, P = 0.011) and comparable baseline mean arterial pressure (Table 2). The baseline SVI and cardiac index were comparable between the arterial pressure responders and non-responders, with the arterial pressure non-responders showing a higher baseline mean arterial pressure than the responders [79 (71 to 86) vs. 70 (56 to 78) mmHg, P < 0.01; Table 3].

In SV responders, the fluid challenge induced significant increases in the mean arterial pressure [from 75 (62 to 81) to 77 (69 to 89) mmHg], SVI [from 36 (33 to 45) to 44 (40 to 54) ml m−2], cardiac index (from 3.12 ± 0.71 to 3.76 ± 0.91 l min−1 m−2) and central venous pressure [from 3 (1 to 5) to 5 (3 to 7) mmHg] and induced significant decreases in the SVRI (from 1863 ± 678 to 1621 ± 594 mmHg l−1 m−2; all P < 0.05; Table 2). In SV non-responders, the fluid challenge induced no significant changes in SVI, cardiac index, mean arterial pressure or SVRI. In arterial pressure responders, the fluid challenge induced significant increases in the mean arterial pressure [from 70 (56 to 78) to 86 (72 to 92) mmHg], SVI [from 40 (33 to 47) to 45 (41 to 51) ml m−2], cardiac index (from 3.31 ± 0.83 to 3.69 ± 0.90 l min−1 m−2) and central venous pressure [from 3 (1 to 5) to 5 (3 to 7) mmHg; all P < 0.05; Table 3]. The fluid challenge also induced significant increases in SVI and cardiac index in the arterial pressure non-responders, but the mean arterial pressure did not significantly change and SVRI significantly decreased from 1805 ± 697 to 1594 ± 696 mmHg l−1 m−2 (P < 0.05; Table 3).

The fluid challenges did not induce significant changes in the heart rate or perfusion index in responders and non-responders of both SV (Table 2) and arterial pressure (Table 3).

Discussion

In this study, we determined that dynamic preload variables, namely, PPV, SVV and PVI, significantly predicted SV fluid responsiveness in liver cirrhosis patients. However, all investigated vascular tone variables failed to predict arterial pressure responsiveness fluid to a fluid challenge.

Few studies have investigated the ability of dynamic preload variables to predict SV fluid responsiveness during liver transplantation. Gouvea et al.17 reported no significant difference in the baseline PPV of SV responders and non-responders and stated that the change in PPV was consistent with fluid challenges during liver transplantation, which does not agree with our results. This discrepancy may be attributable to three factors. First, they studied only 15 patients. Second, because liver cirrhosis patients exhibit altered vascular compliance, the fluid challenge volume in that study (<6 ml kg−1) may have been insufficient to induce significant changes in SV. Third, the PPV was measured from the radial artery, whereas it was measured from the femoral artery in our study; liver cirrhosis patients may present discrepancies between central and peripheral blood pressures.18

This study is the first to investigate PVI in liver cirrhosis patients. The ability of PVI to predict SV fluid responsiveness has been investigated in patients with altered vascular tones. Biais et al.19 reported that PVI was poorly correlated with PPV in critically ill patients receiving norepinephrine infusions, which is in accordance with our results. Although we found that PVI was significantly correlated with PPV and SVV, the correlation coefficient represented only a mild-to-moderate correlation. Because PVI was measured at the level of the peripheral tissue microcirculation and PPV and SVV were measured at the level of the central arteries, the low correlation may be attributed to the association of liver cirrhosis with peripheral vasodilatation and splanchnic blood volume stealing.1–3 Monnet et al.7 reported that PVI is a weak predictor of SV fluid responsiveness in septic shock patients receiving norepinephrine infusions, which is inconsistent with our results. Although haemodynamic characteristics such as low SVR are common to sepsis patients and liver cirrhosis patients, the use of vasopressors in septic shock patients may lead to arterial constriction and venous pressure elevation, which may lead to a higher afterload-dependent haemodynamic status compared with the preload-dependent haemodynamic status and a decrease in the ability of PVI to predict SV fluid responsiveness. Moreover, we determined that although the AUROC of the PVI was not significantly higher than those of PPV or SVV, we observed a higher sensitivity for PVI (95.7% for PVI vs. 78.3% for PPV and 69.6% for SVV). Because the blood volume in peripheral tissues depends on vascular distensibility, which is considered to remain unchanged during the course of one mechanical breath, PVI may demonstrate a higher sensitivity to ventilator-induced changes than PPV does in patients with altered arterial compliance, such as paediatric patients.20

In this study, the AUROCs, the sensitivity or specificity to predict SV fluid responsiveness and the cut-off values of each dynamic preload variable were slightly lower than those in some previous studies. For instance, a sensitivity of 81% and a specificity of 80% were observed for SVV.21 This may be attributable to two factors. First, liver cirrhosis is associated with marked alterations in the intra-hepatic and extra-hepatic vasculature, including central and peripheral vascular compliance changes, reduced vascular resistance and autonomic dysfunction,22,23 which result in less evident mechanical ventilation-induced SV changes. Second, cirrhotic cardiomyopathy may be prevalent in liver cirrhosis patients, even in those presenting with normal preoperative LVEF.24,25 In the cirrhotic heart, the slope of the Starling curve may be depressed, resulting in a lower SV increase in response to a fluid challenge.

This study is the first to investigate the predictive abilities of the PPV/SVV ratio, perfusion index and SVRI for arterial pressure fluid responsiveness in liver cirrhosis patients. The perfusion index and SVRI failed to predict arterial pressure fluid responsiveness because both variables represent the static state of the vascular tone of the microcirculation over the fingertip and arterioles; at this level, peripheral vasodilatation is common in liver cirrhosis patients.1 In contrast, the PPV/SVV ratio is proposed to be the dynamic interaction between arterial pressure and SV, instead of being a static evaluation of the arterial pressure–volume relationship. In this study, PVV and SVV were obtained at the level of the central arteries, which are less affected by peripheral vasodilatation and changes in pulse wave velocity. However, we determined that the PPV/SVV ratio failed to predict arterial pressure fluid responsiveness in liver cirrhosis patients, even among SV responders (patients in preload-dependent status). These results showed that an altered relationship exists between arterial pressure and SV in both the larger and peripheral vessels of liver cirrhosis patients and that fluid challenges may be less effective for reversing hypotension in liver cirrhosis patients, even in those in preload-dependent status (SV responders).

Liver transplantation consists of three physiological stages: the hepatic dissection, anhepatic and neohepatic phases. The anhepatic phase is associated with inferior vena cava clamping, and the neohepatic phase is associated with reperfusion syndrome. Both phases exhibit unstable vascular tone and cardiac contractility. In contrast, the hepatic dissection phase is associated with fewer haemodynamic aberrations and is more suitable for investigations of haemodynamic monitoring in liver cirrhosis patients.

Using the PiCCO system is not the gold standard for cardiac output measurement compared with the pulmonary arterial catheter. Hadian et al.26 reported less agreement between PiCCO and pulmonary arterial catheter for the measured trend of cardiac output changes in response to vasoactive agent administration in post-cardiac surgery settings. The cardiac output generated using PiCCO is more easily affected by unstable vascular tone and cardiac contractility, which are common in cardiac patients.27 In patients with lower SVR, such as liver cirrhosis patients and sepsis patients, the PiCCO system has been reported to be reliable for assessing cardiac index changes induced by volume expansion.15,28 During our measurements, the vascular tone was less likely to change because the surgery had been temporarily stopped. In addition, to improve its reliability, we calibrated the PiCCO system each hour and before each haemodynamic measurement, which has been reported to improve the reliability of PiCCO-generated cardiac output values.29–31

Our study had some limitations. First, the ability of PVI to predict fluid responsiveness is related to the signal processing method.32 Therefore, our results may not be generalised to other devices or software-generating plethysmographic variations. Second, although the tidal volume in this study (8 ml kg−1) was set within the limit of the currently recommended range for abdominal surgery (6 to 8 ml kg−1),33 our result may not be directly translated into a lower tidal volume setting such as 6 ml kg−1. Because the ventilator-induced SV change possibly remains, one can expect lower threshold values when using PPV, SVV and PVI to predict SV and fluid responsiveness at lower tidal volume settings.

In conclusion, we found that the three dynamic preload variables, namely, PPV, SVV and PVI, predicted SV fluid responsiveness and that their changes were consistent with fluid challenges in liver cirrhosis patients under mechanical ventilation. Therefore, these dynamic preload variables might be useful indicators for fluid management in liver cirrhosis patients receiving mechanical ventilation. However, the PPV/SVV ratio, the perfusion index and the SVRI were not predictive of arterial pressure fluid responsiveness in liver cirrhosis patients.

Acknowledgements relating to this article

Assistance with the study: The authors acknowledge statistical assistance provided by the Taiwan Clinical Trial Statistical Center, Training Center and Pharmacogenomics Laboratory, which is founded by the National Research Program for Biopharmaceuticals (NRPB) at the Ministry of Science and Technology of Taiwan (MOST 104–2325-B-002–032) and the Department of Medical Research in National Taiwan University Hospital.

Financial support and sponsorship: none.

Conflicts of interest: none.

Presentation: none.

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