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The Use of Pulse Pressure Variation and Stroke Volume Variation in Spontaneously Breathing Patients to Assess Dynamic Arterial Elastance and to Predict Arterial Pressure Response to Fluid Administration

Cecconi, Maurizio, MD, FRCA, FICM, MD(UK)*; Monge García, M. Ignacio, MD*†; Gracia Romero, Manuel, MD*†; Mellinghoff, Johannes, MSc*; Caliandro, Francesca, MD*; Grounds, Robert Michael, FRCA, FICM, MD*; Rhodes, Andrew, FRCA, FRCP, FICM, MD(res)*

doi: 10.1213/ANE.0000000000000442
Technology, Computing, and Simulation: Research Report
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BACKGROUND: Dynamic arterial elastance (Eadyn), defined as the pulse pressure variation (PPV) to stroke volume variation (SVV) ratio, has been suggested as a predictor of the arterial pressure response to fluid administration. In this study, we assessed the effectiveness of Eadyn to predict the arterial blood pressure response to a fluid challenge (FC) in preload-dependent, spontaneously breathing patients.

METHODS: Patients admitted postoperatively and monitored with the Nexfin monitor (BMEYE, Amsterdam, The Netherlands) were enrolled in the study. Patients were included in the analysis if they were spontaneously breathing and had an increase in cardiac output ≥10% during an FC. Patients were classified according to the increase in mean arterial blood pressure (MAP) after FC into MAP-responders (MAP increase ≥10%) and MAP-nonresponders (MAP increase <10%). Eadyn was continuously calculated from the PPV and SVV values obtained from the monitor.

RESULTS: Thirty-four FCs from 26 patients were studied. Seventeen FCs (50%) induced a positive MAP response. Preinfusion Eadyn was significantly higher in MAP-responders (1.39 ± 0.41 vs 0.85 ± 0.23; P = 0.0001). Preinfusion Eadyn predicted a positive MAP response to FC with an area under the receiver-operating characteristic curve of 0.92 ± 0.04 of standard error (95% confidence interval, 0.78–0.99; P < 0.0001). A preinfusion Eadyn value ≥1.06 (gray zone: 0.9–1.15) discriminated MAP-responders with a sensitivity and specificity of 88.2% (approximate 95% confidence interval, 64%–99%), respectively.

CONCLUSIONS: Noninvasive Eadyn, defined as the PPV to SVV ratio, predicted the arterial blood pressure increase to fluid administration in spontaneously breathing, preload-dependent patients.

Published ahead of print September 16, 2014.

From the *Department of Intensive Care Medicine, St. George’s Healthcare NHS Trust and St. George’s University of London, London, United Kingdom; and Servicio de Cuidados Intensivos y Urgencias, Hospital SAS de Jerez, Jerez de la Frontera, Spain.

Accepted for publication July 7, 2014.

Published ahead of print September 16, 2014.

Funding: All support was provided solely from institutional or departmental sources or both.

Conflict of Interest: See Disclosures at the end of the article.

Reprints will not be available from the authors.

Address correspondence to Maurizio Cecconi, MD, FRCA, FICM, MD(UK), Department of General Intensive Care, St. George’s Healthcare NHS Trust and St. George’s University of London, Tooting, London SW17 0QT, UK. Address e-mail to m.cecconi@nhs.net.

The aims of fluid resuscitation are the achievement of an adequate cardiac output (CO) and sufficient mean arterial blood pressure (MAP) for the body to maintain tissue oxygenation.1 Although the assessment of preload dependency has been extensively studied in recent years,2 only a small number of studies have focused on the arterial blood pressure prediction to intravascular volume expansion.3,4 Since the arterial blood pressure response to a fluid challenge (FC) cannot be easily predicted,4 simplifying the patient’s hemodynamic assessment to the determination of preload dependency only provides an incomplete evaluation.

Systemic arterial blood pressure is the result of the complex interaction between left ventricular ejection and the arterial system.5 For the same increase in CO, arterial blood pressure will change depending on baseline arterial tone.6 If the patient is profoundly vasodilated, as occurs in septic or anaphylactic shock, arterial blood pressure may then not improve after an FC, even if blood flow does. Therefore, the degree to which arterial blood pressure increases is a function of both left ventricular ejection and arterial elastance. Elastance is the change in pressure for a change in volume.7 In this regard, the functional assessment of arterial load by the dynamic arterial elastance (Eadyn), defined as the ratio between pulse pressure variation (PPV) and stroke volume variation (SVV) during a single respiratory cycle, has been proposed as an index to predict the arterial blood pressure response to FC.6 Rather than a steady-state assessment, Eadyn depicts the actual slope of the pressure–volume relationship providing a dynamic evaluation of the arterial load, in the same way that dynamic indexes of preload dependency aim to predict the CO response to a variation in cardiac preload. Therefore, the higher the Eadyn value, the more likely arterial blood pressure is to improve after an FC. The validity of this hypothesis has been recently tested in hypotensive preload-dependent patients3 and for predicting a reduction in vasopressor requirements after fluid administration in patients undergoing major hepatic resection.8

Theoretically, as long as PPV and SVV values are high enough for defining the slope of the pressure–volume curve, the impact of nonuniform ventilation during spontaneous breathing should equally affect both parameters. Therefore, Eadyn should remain constant and its predictive performance will remain valid.9 However, this assumption, although physiologically reasonable, has not yet been confirmed.

The aim of the present study therefore was to evaluate the effectiveness of Eadyn, measured noninvasively, for predicting the arterial blood pressure response to an FC in preload-dependent, spontaneously breathing postsurgical patients.

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METHODS

The analysis of Eadyn is part of a study to investigate hemodynamic variables to predict fluid responsiveness in intensive care unit patients. The study was approved by the Joint Research and Enterprise Office of St George’s Hospital and by the South East London Research Ethics Committee (REC Ref. Number 10/H0807/41). The sample size was calculated as 50 to obtain data in at least 20 patients (considering a percentage of fluid responders of about 40%). The analysis of Eadyn was performed a posteriori only on fluid responsive patients. No sample size calculation was made a priori regarding Eadyn.

Written informed consent was obtained before enrolling patients in the study.

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Patients

We collected data from high-risk surgical patients admitted postoperatively to the General Intensive Care Unit of St. George’s Hospital. Patients were monitored with the Nexfin hemodynamic monitoring system (BMEYE, Amsterdam, The Netherlands). Fluid administration was performed following the institutional early goal-directed therapy protocol.10 FC consisted of 250 mL of Gelofusin® (B Braun, Melsungen, Germany) administered over 5 to 10 minutes. Only spontaneously breathing patients with a CO increase ≥10% as measured by Nexfin after FC were considered fluid-responders and included in the analysis.

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Measurements

The Nexfin monitoring system estimates beat-to-beat stroke volume (SV) by using arterial pulse pressure analysis (PPA). The arterial blood pressure is initially measured noninvasively at the finger level using the volume clamp method described by Peñáz et al.11 and the Physiocal calibration by Wesseling for accounting for changes in unloaded volume.12 Finger arterial waveform pressure is then converted to brachial arterial pressure waveform by a transfer function. The PPA algorithm estimates SV by dividing the area under the systolic part of the reconstructed brachial arterial waveform by the aortic input impedance, estimated by a 3-element Windkessel model.13 A correction is also applied to account for nonlinear pressure dependency of cross-sectional area of the aorta and the influence of the patient’s characteristics on the aortic mechanical properties.13

Data files from the Nexfin monitor were exported for inspection in the Nexfin@PC software (version 1.0.1, BMEYE, Amsterdam, The Netherlands). The data were then exported to an Excel file using the FrameInspector software (version 2.3.0.2, BMEYE, Amsterdam, The Netherlands), and the average of the hemodynamic measurements for 1 minute before and after an FC was used for the statistical analysis.

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Arterial Load Assessment

Arterial load is the net force imposed on left ventricular ejection and defines, along with left ventricular SV, the systemic arterial blood pressure profile.7 We evaluated its steady component using the total systemic vascular resistance (TSVR) (TSVR = MAP/CO × 80), and the pulsatile component by the net arterial compliance (C = SV/arterial pulse pressure [systolic minus diastolic arterial blood pressure]).14 Effective arterial elastance (Ea) was calculated as an integrative parameter that incorporates both the steady and pulsatile components of arterial load7,15 (Ea = 0.9 × systolic arterial blood pressure/SV, where 90% of systolic arterial blood pressure was used as a surrogate of left ventricular end-systolic pressure.).7,15,16 Dynamic assessment of arterial load was estimated with Eadyn, as the instantaneous relationship between PPV and SVV.3,6 Arterial PPV and SVV were calculated simultaneously every 5 seconds by the Nexfin monitor by standard formulae.17

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Statistical Analysis

Normal distribution of data was tested using Kolmogorov–Smirnov test with Lilliefors significance correction. The results are expressed as a mean ± SD. Patients were classified according to the MAP increase after FC into MAP-responders (≥10%) and nonresponders (<10%). This threshold was selected assuming an optimal ventriculo-arterial coupling, so for a 10% increase in CO, a MAP increase of 10% should be expected.18 Differences between MAP-responders and nonresponders at baseline were compared by means of an independent sample t test and in their evolution over time by one-way analysis of variance (ANOVA) followed by a Student t test with adjustment for repeated measurements, using group as the between-subjects factor and time as the within-subjects factor. The relationship between variables was assessed by Pearson’s correlation coefficient. Area under the receiver-operating characteristic (AUC) curves for baseline Eadyn, C, TSVR, and MAP according to MAP response after fluid administration were calculated and compared using the method described by DeLong et al.19 For the confidence intervals (CIs) of the AUC, the binomial exact CIs were used, although these CIs do not apply to the difference between AUCs. Optimal cutoff values were calculated by maximizing the Youden index (J = sensitivity + specificity − 1). A gray zone for Eadyn cutoff was created using resampling according to the approach described by Cannesson et al.20 In summary, we determined the Youden index for each bootstrapped sample from 1000 replications of the original study population. The median value and its approximate 95% CI of these 1000 optimal cutoffs were calculated. This bootstrapped 95%CI defines a gray zone around the optimum criterion in which prediction of MAP response after fluid administration remains inconclusive. This approach has been previously used in similar studies20,21 to avoid the classical dichotomic approach provided by receiver operating curve (ROC) analysis that often does not meet the reality of clinical practice.22

A P value <0.05 was considered statistically significant. All statistical analyses were 2-tailed and performed using MedCalc Statistical Software version 12.7.0 (MedCalc Software bvba, Ostend, Belgium; http://www.medcalc.org; 2013).

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RESULTS

Thirty-four FCs in 26 patients from 50 screened patients were included in the analysis. Sixteen patients were excluded for not meeting the CO increase criteria, 6 patients due to incomplete information for identifying the FC in the data file, and 2 patients for inadequate data collection or no FC recorded. No >2 FCs were analyzed per patient. Demographics and main characteristics of included patients are listed in Table 1.

Table 1

Table 1

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Hemodynamic Response to FC

Hemodynamic changes after fluid administration are summarized in Table 2. In the whole population, FC increased CO by 18 ± 7%, SV by 14 ± 9%, and MAP by 10 ± 8%. According to the a priori definition of MAP responders, only 17 FCs (50%) of 15 patients were classified as positive pressure responders.

Table 2

Table 2

FC-induced changes in CO and SV were poorly correlated with changes in MAP (r = 0.18, P = 0.30 and r = 0.22, P = 0.20; respectively). However, a significant relationship was observed between FC-induced increases in CO and SV, and arterial pulse pressure changes (r = 0.67 and r = 0.76; P < 0.0001, respectively). Individual changes in CO and MAP are shown in Figure 1.

Figure 1

Figure 1

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Effects of FC on Arterial Load Parameters

The effects of volume administration on arterial load variables are summarized in Table 3. Individual differences between MAP-responders and nonresponders for each arterial load variable are presented in Figure 2. In the overall group, fluid administration increased C from 0.64 ± 0.21 mL/mm Hg to 0.69 ± 0.21 mL/mm Hg (P = 0.0006) and decreased TSVR from 1290 ± 336 dyn·s·cm−5 to 1202 ± 304 dyn·s·cm−5 (P < 0.0001). Neither Eadyn nor Ea changed after FC when considering all the patients.

Table 3

Table 3

Figure 2

Figure 2

At baseline, MAP and Eadyn were significantly different between groups (Table 2 and 3, Fig. 2). Preinfusion Eadyn levels were positively correlated with FC-induced increases in all components of arterial blood pressure (Fig. 3). By contrast, none of the other studied arterial load variables was significantly correlated with changes in arterial blood pressure produced by FC.

Figure 3

Figure 3

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Prediction of Arterial Pressure Response to FC

The area under the ROC curve for the prediction of MAP response to FC for Eadyn (0.92 ± 0.04; 95% CI, 0.78–0.99) was significantly higher than for Ea (AUC: 0.59 ± 0.1; 95% CI, 0.40 – 0.75; P = 0.0024), TSVR (AUC: 0.52 ± 0.1; 95% CI, 0.34–0.70; P = 0.0001), C (AUC: 0.64 ± 0.1; 95% CI, 0.45–0.79; P = 0.0081), except for baseline MAP (AUC: 0.75 ± 0.09; 95% CI, 0.57–0.88; P = 0.0433) (Fig. 4). A preinfusion Eadyn value >1.06 predicted a positive MAP response after fluid administration with a sensitivity and specificity of 88.2% (approximate 95% CI, 64%–99%), respectively. Bootstrapped “gray zone” around the associated criterion of maximal Youden index ranged from 0.9 to 1.15, which includes approximately 35% of all the FCs performed.

Figure 4

Figure 4

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DISCUSSION

In this study, we have shown that the ratio of PPV and SVV can be used to calculate Eadyn in spontaneously breathing patients and that Eadyn can be measured noninvasively with PPA. Eadyn predicted the resulting increase in arterial blood pressure from an FC in volume-responsive, spontaneously breathing postsurgical patients.

An FC is often used to test the response of the cardiovascular system to fluid administration23 and in postsurgical patients.24,25 Arterial blood pressure optimization is an important component of hemodynamic resuscitation. Although a normal MAP value does not guarantee an adequate global perfusion pressure, it seems reasonable to maintain a sufficient MAP level to avoid tissue hypoperfusion and further organ injury.26 A sustained low arterial blood pressure, or even a sole episode of hypotension, has been associated with a poor outcome in patients with septic shock.27–30 Timing for vasopressor introduction, however, is still not well established, and vasoactive drugs are usually initiated only after an arbitrary amount of IV fluid has been administered.26,31 Predicting the arterial response to fluid administration is very important in the perioperative settings. Hypotension during the induction of anesthesia is common and associated with worse long-term outcome.32,33 Whether fluids or pressors should be used is still a matter of debate. While strategies aiming at optimizing blood flow have shown that this could lead to improvement in outcome,24 goal-directed strategies aiming at how to manage pressors during hypotension could have profound implications for the management of patients under general anesthesia. Decreased arterial blood pressure due to a loss of vascular tone could therefore lead to fluid overload if aggressive volume resuscitation is aimed at a MAP target and vasoactive therapy is delayed.29 On the contrary, if low arterial blood pressure is the result of an inadequate blood flow, early administration or an inappropriately high dose of vasoactive drugs could aggravate an already impaired organ perfusion.34

Unfortunately, since the arterial blood pressure response depends not only on blood flow changes but also on arterial load,6,9 knowing whether a patient is volume-responsive only provides an incomplete answer for the question: Will arterial blood pressure improve with fluid administration? In this regard, SVV and PPV are well recognized and widely used indexes of fluid responsiveness.35 Cyclical changes in left ventricular SV induced by intermittent positive-pressure ventilation determine observed variations in both SV and arterial pulse pressure.36 Furthermore, the instantaneous relationship between PPV and SVV (i.e., Eadyn) determines the slope of the pressure–volume relationship and the degree of flow dependency of arterial blood pressure.6 Therefore, instead of a static evaluation of arterial pressure–volume relationship as provided by C, TSVR, or Ea, Eadyn defines the dynamic interaction of SV and the arterial system, and hence the functional assessment of arterial load. Accordingly, in the same way that SVV and PPV are not measurements of cardiac preload or volume status (although they are influenced by them), Eadyn should not be interpreted as a direct measurement of arterial load (neither static nor pulsatile), but as a dynamic index.

Even if PPV and SVV cannot be used to predict increases in CO or SV in spontaneously breathing patients, theoretically their relationship (as defined by Eadyn) should not be affected by spontaneous breathing activity, since the impact of irregular variations in intrathoracic pressure should influence both components to the same degree. Therefore, as long as the magnitude of PPV and SVV allows reliably depicting the slope of arterial pressure–volume relationship, the predictive value of Eadyn should remain valid even during spontaneous ventilation, as our results suggest.

Since hypotension can be a hallmark of hypoperfusion, its detection and treatment require a rapid response to avoid organ failure. Although fluid administration remains the first recommended therapy, low arterial blood pressure could be related not only to inadequate blood flow but also to a loss of arterial tone. In this regard, the assessment of Eadyn could help to discriminate those preload-dependent patients in whom arterial blood pressure will improve only with fluids or by using vasopressors. Hypothetically, if a hypotensive patient is not a pressure-responder (low Eadyn), vasopressors should be initiated to improve MAP, even if the patient is preload dependent. If the patient is a pressure-responder (high Eadyn), vasopressor therapy should be delayed and intravascular volume administration alone should increase arterial blood pressure. Furthermore, pressure-responder patients who are already receiving vasoactive drug therapy could theoretically benefit from fluid therapy to reduce vasopressor dosage or even withdrawal once an adequate MAP level is reached. Finally, in patients with an inconclusive Eadyn value, vasopressors may be introduced at the discretion of the physician. Interestingly, the gray zone for the Nexfin-derived Eadyn threshold found in this study was very similar to that originally suggested.6 If our results are confirmed, this approach could potentially be used in many clinical scenarios in anesthesia and intensive care. The fact that Eadyn can be assessed in spontaneously breathing patients opens a new field of research in anesthesia and intensive care. For instance, it could be used to study the effect of anesthetic drugs on the arterial elastance and on the blood pressure at the induction of anesthesia. This may lead to the development of different techniques to use, or pressors or fluids in patients undergoing different types of anesthesia.

This study has some limitations that must be discussed. First, we used the Nexfin monitor for both CO and arterial blood pressure measurements. The Nexfin monitoring system has been previously validated for measuring arterial blood pressure37,38 and estimating CO in perioperative patients39,40 during routine cardiac function evaluation41 or during changes in cardiac preload induced by FC or postural maneuvers.39,42 One study has questioned the ability of this device to track CO changes after intravascular volume expansion.43 This study was performed in critically ill patients, in whom the frequent presence of hypoperfusion could diminish the reliability of this device. Moreover, the ability of PPA to detect changes in CO during FC seems to be a common property of PPA, probably due to the minor impact of variations in arterial load during IV FC.44 Second and importantly, since we used a PPA method for CO estimation, a mathematical coupling between blood pressure changes and CO increases after FC cannot be excluded. An independent technique, such as thermodilution, would have been desirable. Also, the SVV value provided by the Nexfin monitor is derived from the PPA technique; therefore, an inherent limitation was introduced into our Eadyn calculation, since SVV and PPV are not independently measured. Third, our study involves a small number of patients who underwent high-risk surgery, and the majority of the included patients was not hypotensive. The small number of hypotensive patients (9) prevented a subgroup analysis in hypotensive and normotensive patients. Also this was a population of high-risk surgical patients, and we do not know whether our results can be extrapolated to sicker intensive care unit patients, such as patients with acute respiratory distress syndrome and septic shock.

Fourth, we did not collect data to correct for patient’s comorbidities and to see whether these may affect the diagnostic accuracy of Eadyn. Despite these limitations, the predictive performance of Eadyn remained significantly superior to other arterial load variables, perhaps with a reasonably good sensitivity and specificity, and a narrow gray zone. Moreover, the Eadyn threshold found in this study should not be extrapolated to other devices based on PPA, since this value is inherent to each monitoring device used and its specific PPA algorithm.

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CONCLUSIONS

In conclusion, we found that in fluid-responsive, spontaneously breathing patients undergoing postoperative hemodynamic optimization, the use of PPV and SVV can be used to assess the Eadyn. This allowed us to predict the arterial blood pressure response to an FC. Further studies are required to recommend the use of this parameter in current hemodynamic optimization protocols.

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DISCLOSURES

Name: Maurizio Cecconi, MD, FRCA, FICM, MD(UK).

Contribution: This author conceived and designed the study, participated in the recruitment of patients, performed the data analysis, interpreted the data, and wrote the manuscript.

Attestation: Maurizio Cecconi approved the final manuscript, reviewed the original study, attests to the integrity of the original data and the analysis reported in this manuscript, and is also the archival author.

Conflicts of Interest: Maurizio Cecconi in the last 5 years has received honoraria or travel expenses or both from Edwards Lifesciences, LiDCO, Cheetah Medical, Bmeye (Amsterdam, The Netherlands), Masimo (Neuchatel, Switzerland), and Deltex Medical.

Name: M. Ignacio Monge García, MD.

Contribution: This author performed the data analysis, interpreted the data, and wrote the manuscript.

Attestation: M. Ignacio Monge García approved the final manuscript, reviewed the original study, and attests to the integrity of the original data and the analysis reported in this manuscript.

Conflicts of Interest: M. Ignacio Monge García is consultant for Edwards Lifesciences (Irvine, CA) and has received travel expenses from Deltex Medical.

Name: Manuel Gracia Romero, MD.

Contribution: This author performed the statistical analysis, interpreted the data, and wrote the manuscript.

Attestation: Manuel Gracia Romero approved the final manuscript.

Conflicts of Interest: The author has no conflicts of interest to declare.

Name: Johannes Mellinghoff, MSc.

Contribution: This author participated in the patient recruitment, data collection, provided technical support, and contributed to the critical review of the manuscript.

Attestation: Johannes Mellinghoff approved the final manuscript.

Conflicts of Interest: The author has no conflicts of interest to declare.

Name: Francesca Caliandro, MD.

Contribution: This author participated in the patient recruitment, data collection, provided technical support, and contributed to the critical review of the manuscript.

Attestation: Francesca Caliandro approved the final manuscript.

Conflicts of Interest: The author has no conflicts of interest to declare.

Name: Robert Michael Grounds, FRCA, FICM, MD.

Contribution: This author made substantial contributions to the analysis and interpretation of data, were involved in drafting the manuscript, and contributed to its critical review.

Attestation: Robert Michael Grounds approved the final manuscript.

Conflicts of Interest: The author has no conflicts of interest to declare.

Name: Andrew Rhodes, FRCA, FRCP, FICM, MD(res).

Contribution: This author made substantial contributions to the analysis and interpretation of data, were involved in drafting the manuscript, and contributed to its critical review.

Attestation: Andres Rhodes approved the final manuscript.

Conflicts of Interest: Andres Rhodes has received honoraria from and serves on an advisory board for LiDCO (London, UK) and has received honoraria from Covidien (Dublin, Ireland), Edwards Lifesciences, and Cheetah Medical (Vancouver, WA).

This manuscript was handled by: Maxime Cannesson, MD, PhD.

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