2/2019
vol. 51
Review article
Contemporary perioperative haemodynamic monitoring
- Department of Anesthesiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute and Chongqing Cancer Hospital, Chongqing, China
- Department of Anesthesiology and Critical Care, OLV Ziekenhuis, Aalst, Belgium
- Department of Anesthesiology and Perioperative Medicine, University Hospital Brussels (VUB), Faculty of Medicine
and Pharmacy, VUB, Brussels, Belgium
Anaesthesiol Intensive Ther 2019; 51, 2: 147–158
Online publish date: 2019/06/28
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Haemodynamic monitoring is the cornerstone in the optimization of tissue perfusion and the prevention of deteriorating metabolism, both in the perioperative period and in the intensive care unit (ICU) setting. Haemodynamic alterations could be summarized in terms of cardiac dysfunction, changes of loading conditions (preload or/and afterload), and patient related issues (stress, sedation level, positioning, disease). Monitoring of haemodynamics serves to optimize pump performance, adequacy of circulation and tissue perfusion, and hence, interferes directly with patient outcome [1].
For several years, a trend towards less invasive haemodynamic monitoring has been observed, but so far none of these can be considered the gold standard for patients in the perioperative period. The pulmonary artery catheter (PAC) has been the clinical standard for many years. Initially, the PAC was used as a monitoring tool of filling pressures; however, the focus has been moved to assessment of cardiac output (CO) and mixed venous oximetry (SvO2). With the availability of calibrated and non-calibrated monitoring systems, stroke volume monitoring has become the primordial measured variable, with pressures being derived indirectly. The primary goal of these monitors is to assess fluid responsiveness and to trend haemodynamic variables. Each monitoring technique has advantages and shortcomings, and these should be strictly acknowledged. The inter-monitor variability of absolute CO differs significantly also in comparison with thermodilution. The clinician must therefore be very attentive and critical when interpreting monitoring data and should mainly rely on trend analysis rather than absolute values.
This review aims to present the clinical applications of different modern haemodynamic monitoring techniques, discuss advantages and disadvantages, and provide guidance to help the clinician select the most suitable technique for optimizing haemodynamics in individual patients during the perioperative period.
Blood flow and tissue perfusion assessment
Organ perfusion is the result of the heart pumping an oxygen-carrying fluid (blood) through a transport system (vessels), ensuring organ function. Delivery of O2 and nutrients and removal of CO2 and toxins are the tasks of tissue perfusion. Systemic blood pressure is the inflow pressure for organ perfusion and as such an indirect measure of blood flow, though a poor indicator of blood flow [2]. Low compliant vessels could result in high blood pressures that do not correlate with adequate perfusion.
When assessing the function of contracting cardiac chambers and propagating flow in vessels, it is important to realize that pressure remains an incomplete descriptor of volume and flow, as could be observed in the following equation:
ΔPressure × Compliance = ΔVolume
If volume is to be directly related to pressure, compliance must remain constant. However, both cardiac and vessel compliances are dynamic in nature. Drugs, sympathetic tonus, or a change in volume status all alter cardiac and vessel compliance. Cardiac compliance is influenced directly by e.g. filling, myocardial ischaemia or heart failure [3]. In addition, loading conditions must be estimated to allow assessment of cardiac function because improving loading conditions improve cardiac function in load-dependent hearts. Thus, optimization of cardiac compliance and loading conditions can improve blood flow. To accomplish this, haemodynamic monitoring is essential to achieve optimal perfusion and balance loading conditions and cardiac systolic function in such a manner that tissue perfusion is optimized [4, 5].
Traditional clinical assessment of tissue perfusion includes monitoring urine output, skin temperature, and capillary refill time, but all of these are characterized as insensitive and responsive with delay. Lactate is the most important indicator of hypoxic metabolism and low perfusion state [6, 7] but is a non-continuous parameter. In addition, lactate levels can be influenced by lactate-buffered fluids [8]. Mixed venous oxygen saturation (SvO2) is an important indicator of tissue oxygenation that is altered by changes in SaO2, VO2, haemoglobin (Hb) and cardiac output (CO). However, it only reflects the O2 supply/demand balance of the entire body oxygenation: a normal SvO2 does not exclude tissue hypoxia. For example, in patients with hyperdynamic septic shock and arterial-venous microcirculatory shunting, SvO2 may be high even though tissue hypoxia is present [8-10]. PCO2 gap is another early marker of hypoperfusion. It depends on the global CO2 production, on cardiac output and on the complex interplay between CO2 tension and CO2 content. It is also influenced by the dissociative curve of CO2 and tissue blood flow [11]. When SvO2 is normal/high, the presence of elevated PCO2 gap is indicative of the persisting impaired perfusion, which can help to distinguish hypoperfused patients with “normal” SvO2 from those with adequate perfusion [12].
To discriminate the etiology of cardiovascular dysfunction, the different constituents of haemodynamics, contractility, preload and afterload must be considered separately without losing sight of the fact that they are part of a larger, integrated system. There is a strong relationship between the three physiological entities, as suggested in the Frank-Starling curve (Figure 1). All three constituents will be discussed separately although their intimate relationship should always be kept in mind.
Assessment and optimization of preload
Assessment of fluid responsiveness
The Frank-Starling curve depicts the impact of volume administration on stroke volume in well-performing hearts versus those with decreased systolic function (Figure 1): the latter are characterized by a flat curve, without any potential to generate more pressure with additional administered volume. As a clinical correlate, both hypovolaemia and hypervolaemia can increase morbidity or mortality, especially in critically ill patients. Hypovolaemia has been associated with tissue hypoperfusion and subsequent hypoxia, insufficient perfusion and subsequent acute kidney injury, whereas hypervolaemia has been associated with tissue oedema, organ failure, increased ICU or ventilator days because of pulmonary oedema, secondary infection, and increased mortality [13, 14] (Figure 2). Recently, numerous studies showed that only ± 50% of patients are fluid responsive [15–17], which suggests that the patient’s preloading condition and fluid responsiveness should be determined before fluid resuscitation is started. For surgical patients, careful management of perioperative fluids with goal-direct therapy can greatly improve outcomes [18].
Basically, two options are possible to estimate preloading conditions: a fluid challenge and mechanically ventilation induced intra-thoracic pressure alterations of blood inflow in the thoracic cage through both the superior and inferior caval vein.
Fluid challenge strategies
Fluid challenge strategies may include passive leg raising (PLR) [19], end-expiratory occlusion test (EEO) [20], a mini-bolus challenge [21], or a bolus infusion [22] in combination with measurement of SV or CO and related haemodynamic parameters with fast-response devices before and after the test, permitting instantaneous assessment of preload and thus prediction of fluid responsiveness. The PLR test is now supported by solid evidence, overcoming the risk of overfilling patients in cardiogenic or obstructive shock, though it appears cumbersome because of the specific positioning of the ICU patient [19, 23]. PLR is a reversible fluid challenge (bolus of 300 mL) and may therefore be the first choice to identify fluid responsiveness in a safe and reversible way. However, position changes limit its use in the operating theatre [23]. Another reversible fluid challenge strategy, the EEO test, prevents any variation in intrathoracic pressure, which leads to an increase in venous return, and can predict fluid responsiveness in patients with protective ventilation in the operating room or ICU [24, 25].
The cardiac chambers and surrounding vessels are in particular sensitive to compression when hypovolaemia is present, as is shown in the next examples. The superior caval vein and the right atrium are more prone to compression in hypovolaemia with increased intrathoracic pressures and PEEP. Cyclic insufflation during inspiration squeezes the pulmonary capillaries more in hypovolaemia, increasing right ventricular afterload. Finally, during expiration a fall in stroke volume is more pronounced when the ventricles are functioning on the steep part of the Frank-Starling curve (Figure 1). The latter is the physiological background of the delta down (see below). All these examples demonstrate that hypovolaemia should be corrected not only to improve circulation but also to optimize pumping function of the ventricles.
In a study by Covertino et al. [26], stroke volume (SV) appeared to be the more sensitive and fastest parameter to predict volume changes after fluid administration. In hypovolaemic patients, CO falls less than SV because heart rate interferes in an unpredictable manner because of age or drugs (such as β-blocker). CO monitoring is not sufficient to manage patients with complex haemodynamic disorders because absent knowledge of preloading and afterloading conditions. Besides SV, stroke volume variation (SVV) or arterial pulse pressure variation (PPV) induced by respiratory variation turned out to be a valid dynamic assessment of fluid responsiveness in mechanically ventilated patients [27, 28]. Both invasive arterial wave monitoring and non-invasive stroke volume monitoring permit monitoring of PPV or SVV. Nevertheless, several important issues should be recognized: 1) tidal volume should be at least 8 mL kg-1 ideal body weight [29], 2) though only applicable in passively mechanically ventilated patients, specific triggered ventilatory settings could still reveal PPV [30], 3) absent arrhythmia, 4) spontaneous breathing could hamper proper interpretation, 5) acute cor pulmonale or acute respiratory failure could reduce the impact of intrathoracic pressure changes, 6) open chest mechanical ventilation will greatly abolish intrathoracic pressure swings, 7) in children, as the ages varies, the cardiovascular physiology changes might thereafter affect the value of SVV [31].
With cardiac ultrasound, mechanical ventilation induced alterations of intrathoracic pressures induce both delta down and delta up of the transaortic flow velocity. In a graded haemorrhage and retransfusion study, Preisman et al. [32] showed delta down being correlated with a small left ventricular end-diastolic volume already from early blood loss, whereas delta up is related to inspiratory augmentation of left ventricular stroke volume.
Changes of the diameter of the superior (ΔSVC) and inferior caval vein diameter (ΔIVC) induced by respiratory variation (tidal volume > 7 mL kg-1) are also predictors of fluid responsiveness with high specificity and sensitivity [33, 34]. Again, some caveats have to be recognized: right ventricular failure with pulmonary arterial hypertension will induce dilation of the afferent vessels, though hypovolaemia of the left ventricle could be present; significant tricuspid regurgitation following chest trauma will provoke dilated caval veins, while the left heart could be underfilled.
Nowadays, various dynamic parameters, derived from minimally invasive and non-invasive monitors, are used to evaluate and optimize a patient’s preload condition and cardiac output, and some appear to be associated with reduced mortality, ICU length of stay and duration of mechanical ventilation [28, 35].
Invasive monitoring
Static variables such as central venous pressure (CVP) have been shown to be poor predictors of fluid responsiveness in critically ill patients because they can be affected by changes in venous return, cardiac compliance, vessel tone and intra-thoracic pressures [36]. CVP assessment should be combined with other haemodynamic monitoring and clinical assessment [37], in particular in patients with right ventricular failure and/or severe pulmonary hypertension. A dynamic approach of the CVP is possible with passive leg raising, if the above-mentioned factors could be taken into account. The same rationale could be used in view of the value of pulmonary capillary wedge pressure (PCWP) to estimate left ventricular preload. However, numerous studies showed only a poor correlation of PCWP with filling status [38, 39].
For many years, invasive arterial pressure monitoring was combined with a PAC in haemodynamically unstable patients. A PAC can be used to obtain SV, CO, mixed venous oxygen saturation (SvO2) and other pressure and flow variables to achieve a complete haemodynamic picture. Originally, in the 1980s the FICK principle was the gold standard. Pulmonary artery pressures (PAP) and PCWP measured with a PAC used to be the clinical standard to evaluate loading conditions and heart function. ScVO2 became an interesting alternative in the management of patients with cardiac failure from what origin [40]. However, the clinical utility of PAC declined significantly from the end of the 90s because of the availability of alternative monitoring and the awareness of the potential of serious complications [41]. More recently, the PAC has been reserved for patients with hypoxia or acute pulmonary hypertension with overt right heart failure [42]. Moreover, recent reports show that use of the PAC does not improve outcome in critically ill patients [43, 44], a finding which is similar to other haemodynamic monitoring tools. Not the monitoring system itself, but the way it is integrated in haemodynamic monitoring strategies is an important feature in current practice.
With the development of minimally or non-invasive techniques, it is important to direct a guideline to use the specific monitoring in clinical practice.
Less invasive haemodynamic monitoring
For a few years, various monitors have been marketed and focus on step up systems offering the entire range from completely non-invasive over minimally invasive (with arterial pressure monitoring and derived variables) towards pulmonary artery catheter derived variables. The individual units can be utilized independently but can also be integrated into each other.
Calibrated systems
Thermodilution combined with arterial pulse contour analysis
PiCCO and VolumeView are monitoring tools combining arterial pulse contour analysis and transpulmonary thermodilution to derive a calculated CO, global end-diastolic volume (GEDV), cardiac function index (CFI), ejection fraction (EF), extravascular lung water (ELVW), pulmonary vascular permeability index (PVPI), SVV, PPV and ScvO2 [45]. These devices provide information of global heart function, preload, afterload, as well as the balance between oxygen delivery and consumption. Compared to PAC, PiCCO and VolumeView are less invasive yet provide continuous, real-time calculation of SV, reliable and acceptable in haemodynamically unstable patients [46]. GEDV and CFI can help to determine volume responsiveness, while EVLW and PVPI can help in the diagnosis and differentiation of the causes of pulmonary oedema [45]. SVV and PPV derived by PiCCO have proven to be a reliable predictor of fluid responsiveness during surgery and in the ICU [28, 47, 48]. However, frequent recalibration is required. Some bias may exist in patients with cardiac arrhythmias, vascular abnormalities, aortic aneurysm or aortic valve stenosis.
Lithium dilution combined with pulse contour method
The LiDCOplus system combines lithium dilution and the arterial pulse contour method to generate continuous CO measurements. Close agreement with thermodilution derived CO has been reported in surgical patients with low output states [49, 50]. The LiDCOplus device always needs recalibration to optimize accuracy [51, 52] and does not provide advanced haemodynamic variables such as EVLW.
Non-calibrated systems
Arterial pressure waveform analysis
The Vigileo/FloTrac system provides real-time CO measurements by deriving SV from the arterial pressure waveform recorded from an arterial catheter without any calibration, a technique also called arterial pressure waveform analysis (APCO). On the basis of numerous data, age, gender and BSA, APCO provides information about SV, CI, SVV, PPV and systemic vascular resistance indexed for BSA (SVRI) [27, 53]. Goal-directed therapy based on Vigileo/FloTrac system could improve haemodynamics and reduce the duration of respiratory support after cardiac surgery. Hamed et al. showed that preload optimization with the Vigileo/FloTrac system after CABG increased cardiac performance compared with the PAC [54], including information on SV, PPV and SVV values, read on the Vigileo/FloTrac device. However, PPV values between 9% and 13% constitute a gray zone, which does not permit reliable prediction of fluid responsiveness [17]. This gray area constitutes up to 25% of all monitored anaesthetized patients. PPV interpretation is also limited by cardiac arrhythmias, vascular abnormalities, and severe aorta regurgitation [55]. With rapid haemodynamic changes, clinical assessment should be broadened and take into account other factors, such as changes of intra-thoracic pressures and vasoactive drugs administered. Furthermore, the peripheral arterial pressure tracing is influenced by vascular tone, damping and reflection waves, much more than a central arterial pressure tracing. All these factors could induce deviations, though a comparison between a central aortic flow Doppler signal and a FloTrac obtained from a peripheral arterial catheter showed good correlation [56].
Transoesophageal cardiac ultrasound and Doppler (TOE)
TOE offers a complete range of haemodynamic variables, and goes much further than any other haemodynamic monitoring tool [3]. Haemodynamic parameters obtained by TOE can be used to assess and predict fluid responsiveness with parameters such as: 1) LVEDAI and right ventricular end-diastolic area indexed for body surface area (RVEDAI); 2) changes of diameter of the venous inlet into the thorax (including ΔIVC with transthoracic echo [vide infra] and ΔSVC with TOE); 3) SV derived from the area under the curve of a transaortic valvular Doppler signal (i.e. velocity-time integral (VTI), which reflects the distance one red blood cell is projected forward with each contraction; a constant aortic diameter is assumed); and 4) respiratory changes in peak velocity (ΔVpeak) and flow.
A left ventricular end-diastolic area indexed for body surface area (LVEDAI) < 5.5 cm2 m-2 clearly indicates preload status is low [57], though the compliance of the left ventricle should be taken into account [58]. In the absence of severe tricuspid regurgitation, both ΔSVC and ΔIVC are good predictors of fluid responsiveness in mechanically ventilated patient. ΔSVC determined by means of TOE seems to be more accurate, but ΔIVC is more accessible with the transthoracic approach [33, 34, 59]. VTI variation > 20% predicts fluid responsiveness in mechanical ventilated patients, but cannot be used in patients with aortic valve disease [4, 60]. ΔVpeak > 12% predicts fluid responsiveness with a sensitivity of 100% and a specificity of 89% in mechanically ventilated patients in septic shock with preserved LV systolic function [61]. TOE allows monitoring changes of CO that are in high clinical agreement with those of the thermodilution method [62], but it cannot be used in awake patients or in those with oesophageal pathology. Continuous TOE monitoring became available recently with smaller probes and a dedicated machine in critically ill patients [63].
Non-invasive haemodynamic monitoring
Cardiac ultrasound and Doppler
Transthoracic echocardiography (TTE) allows intermittent assessment of haemodynamics at the bedside, and provides invaluable information about the anatomy and global function of the heart and the cardiac valves and about the status of the great vessels as well [64]. Furthermore, dynamic parameters obtained from echo-Doppler can be used to assess fluid responsiveness during the breathing circle or fluid challenges [65]. In critically ill, mechanically ventilated patients, TTE has been shown to be an accurate and precise method to estimate SV and CO [66]. The left ventricular outflow tract (LVOT) VTI SV estimation correlates with volume responsiveness [67, 68]. Both VTI variation > 20% and IVC variation > 12–18%, as well as VTI increases > 12% after PLR suggested fluid responsiveness to be present in mechanically ventilated patients [65]. Respiratory variation of the maximal Doppler velocity in LVOT (VmaxAo) was also used to assess fluid responsiveness, and has high sensitivity [50]. SVI obtained from carotid Doppler increasing > 12% after PLR is another method that can predict fluid responsiveness, with a sensitivity and specificity of 94% and 86%, respectively [69].
EVLW can be captured easily with lung ultrasound: the presence of B lines, comet-like signals moving to-and-fro with mechanical ventilation or spontaneous breathing, is a typical diagnostic tool to elucidate pulmonary oedema in a non-invasive manner.
Perioperative haemodynamic monitoring by TTE-Doppler is an inevitable and indispensable tool [70], but it does not allow continuous real-time monitoring. Furthermore, each change in the patient’s condition requires repeated examination from different views, to eliminate ultrasound pitfalls and is strongly operator dependent.
Volume clamp and radial artery applanation tonometry
Devices using either the volume clamp method (such as Nexfin, CNAP, ClearSight) or radial artery applanation tonometry (such as T-Line) can provide continuous information of blood pressure, SV and PPV from analyzing the continuous arterial pressure waveform. These are uncalibrated, non-invasive, real-time techniques, which are very easy to perform. Many clinical studies have shown they reliably monitor perfusion pressure and CO in the perioperative period [71–73]. A moderate to normal relationship between CO estimations was obtained by this type of device in comparison with PiCCO or thermodilution [74–77]. As for fluid responsiveness prediction, PPV and SVV analysis from a Nexfin monitor have proven to generate reliable data in patients during mechanical ventilation in non-thoracic surgery or after CABG [78]. Stens et al. showed there is some age bias between SVV and PPV: SVV appears more sensitive in younger patients (age < 55 years), while PPV appears more sensitive in older patients (age > 55 years) [79]. Because haemodynamic parameters are derived from a finger or radial artery pulse pressure waveform, significant peripheral vessel resistance changes (such as with oedema or during vasoconstriction using vasoactive drugs), or hand or finger movement [75–77] may limit its clinical use. Also, in patients in shock (with cold extremities) or in an extreme Trendelenburg position (with compression of the subclavian artery between the clavicle and the first rib) signals of these devices could be too poor to allow clinical use. With these limitations, some studies showed that the estimation of CO by Nexfin technology in critically ill patients was not reliable for tracking the effects of a fluid challenge, with a high level of disagreement compared with echocardiography or PICCO monitor [80, 81].
Another tool utilizes flow variation exemplified by plethysmography. The SaO2 curve provides a non-invasive tool to monitor intra-thoracic pressure induced changes of stroke volume. This feature is used in the plethysmography variability index (PVI). From the SaO2 curve, a continuous pulsatile to non-pulsatile flow ratio calculated during surgery [82] integrated in a goal-directed fluid management may reduce lactate levels and facilitates perioperative fluid management [83].
Partial CO2 rebreathing
Partial CO2 rebreathing is a non-invasive technique that estimates CO by using respiratory gas analysis and pulse oximetry. Many studies suggest moderate to good agreement with CO measurements obtained by the thermodilution method during surgery and in ICU mechanically ventilated patients [84–87], but there was a great bias during a period of rapidly changing shunt and dead space, as occurs at the start of one-lung ventilation [88]. Although many studies have shown that CO was underestimated by the partial CO2 rebreathing method compared with the thermodilution method, it still can be used to guide haemodynamic management during surgery [87, 89]. In patients with acute lung injury, CO derived from the partial CO2 rebreathing method was shown to be unreliable [90]. Moreover, it cannot be used with spontaneously breathing patients.
Pulse wave transit time (PWTT)
The estimated continuous cardiac output (esCCO) system is a novel non-invasive CO measurement based on the relationship between PWTT and SV. PWTT is calculated from the R wave interval of the ECG and peripheral (SpO2) pulse wave arrival when ECG and SpO2 are simultaneously recorded [91]. A large sample size multicenter study demonstrated that esCCO had a close correlation with thermodilution method [92]. However, most of the results showed low accuracy and sensitivity with a large bias between esCCO and with TTE or thermodilution derived CO during cardiac or non-cardiac surgery, and it failed to assess the preload and SVR [93, 94]. There are potential inaccuracies when vasopressors are used to treat hypotension associated with decreased SVR, and SVV measurement with esCCO may require further improvement [95, 96].
Bio-impedance and bio-reactance
Another non-invasive real-time CO monitor is called bio-impedance cardiography, which is based on the measurements of the impedance (or resistance) a small electrical current encounters when it travels through the body or chest area. Bio-impedance changes when fluid levels in the thorax change, e.g. as the left ventricle contracts and blood flows into the thoracic aorta. Bio-impedance measures the changes in amplitude of the voltage change across the thorax [97]. Both positive and negative studies have been published, with some suggesting bio-impedance to be a useful non-invasive method to assess extracellular volume changes in patients undergoing cardiac surgery, with a close relationship with thermodilution [98, 99], while others reported a negative correlation between the accuracy of bio-impedance and increased fluid accumulation within the thorax [100–102]. Bio-impedance systems are sensitive to intra-thoracic fluids, such as in patients with oedema or pleural fluid, often present in critically ill patients.
A newer method, named bio-reactance, accurately measures the phase shift of an oscillating current that occurs when a current traverses the thoracic cavity – the higher the cardiac stroke volume (and thus the blood flow), the more significant these shifts become. In contrast to the bio-impedance method, studies showed a good relationship between CO determined by bio-reactance and minimally invasive methods or thermodilution method [103–105]. Bio-reactance can be an accurate method to assess fluid responsiveness in critically ill patients and in patients undergoing major abdominal-pelvic surgery [97, 103–105]. Nevertheless, measurement of CO and other parameters can be disturbed by changes in tissue oedema, pleural effusions, arrhythmias, electrical interference, pacemakers or motion [105, 106]. Furthermore, the present software does not allow assessment of rapid fluid shifts because of time lags of 30 s. Future software updates should permit nearly beat-to-beat monitoring.
Assessment of afterload
Afterload could be described through a two-element Windkessel model, taking together the main pulsatile component of arterial load total (arterial compliance or capacitance C) with C = SV/pulse pressure and a steady part, systemic vascular resistance (SVR = 80 × (MAP – CVP)/CO). Both are pressure and flow dependent. The effective arterial elastance (Ea) is a nowadays often forgotten measure, the ratio of end-systolic pressure (ESP) to SV. It lumps together the pulsatile and steady components of afterload and observes the arterial system as a single elastic volume. Ea therefore is dependent on SVR, heart rate and the elastic properties of the arterial system. ESP can be easily calculated as 0.9 × systolic blood pressure [107].
The dynamic Ea (Eadyn) is PPV/SVV and was thought to be a variable that could estimate the filling capacity of the circulation and therefore safely predict the response of the arterial pressure to preload optimization in preload-dependent patients with acute circulatory failure [108], but some conflicting results exist [109].
Minimally invasive monitors such as the Vigileo/FloTrac system, and oesophageal Doppler combined with minimally invasive arterial pressure monitor can be used to estimate PPV/SVV in mechanically ventilated patients [108, 110], while noninvasive monitoring (model flow based devices – Figure 3) can also be used in patients with spontaneous breathing [111]. Important is the fact that SVR should be normal to achieve correct data of SVV. If afterload changes, it is unknown to what extent mechanical ventilation could interfere with SVV [112].
The dynamic Ea (Eadyn) is PPV/SVV and was thought to be a variable that could estimate the filling capacity of the circulation and therefore safely predict the response of the arterial pressure to preload optimization in preload-dependent patients with acute circulatory failure [113], but some conflicting results exist [114]. If Eadyn is low, vasopressors should be considered to correct hypotension (Figure 4).
Afterload variables, such as left ventricular meridional wall stress (LV-ESWS), global longitudinal strain (GLS), SVR, total arterial compliance, aortic root size and descending aortic pressure/flow velocity, can be estimated with cardiac ultrasound [115–119]. Combined use of pulsatile changes of the aortic contour with TOE and invasively measured local aortic pressure at the same level approaches the arctangent model of Langewouters [116].
Assessment of cardiac contractility
In patients who are “fluid responsive”, fluid resuscitation can increase CO and optimize heart performance. In patients with cardiac failure, fluid resuscitation will aggravate heart function, but increasing ventricular contractility will improve it (at a constant afterload). Therefore, cardiac contractility should be assessed to identify the cause of shock. Echocardiography is able to rapidly identify the cause of hypotension, and it remains the mainstay diagnostic tool to assess cardiac pathology and haemodynamics. Both TOE and TTE can provide qualitative and quantitative information about cardiac systolic and diastolic function, structure and function of valves, absence of myocardial ischaemia, and intra-cardiac structures [3, 110].
Traditional variables such as SV, left ventricular ejection fraction (LVEF) and CO have some limitations if used to assess cardiac contractility, because they are affected by loading conditions [120]. Maximal LV power and preload-adjusted maximal ventricular power (PWRmax/D2) have been shown to better reflect the LV contractile state. PWRmax/D2 is more accurate and independent of preloading conditions, but less reliable in patients with severe hypovolaemia or severe hypertension [115, 121]. Nowadays, this parameter has been abandoned because of afterload interference.
Cardiac power index (CPI) could be obtained non-invasively via bio-reactance monitoring with the following formula:
CPI = MAP × CI/451
with CI – cardiac index, MAP – mean arterial blood pressure. Cardiac power was found to be the strongest haemodynamic correlate with mortality after cardiogenic shock [122]. Further studies should determine the value of this parameter in critically ill monitoring.
Nowadays, researchers are trying to develop more sensitive, accurate and non-invasive methods to assess cardiac contractility. The slope of the regional stretch-strain relationship measured from tissue Doppler imaging (TDI) can be used as a noninvasive index of the myocardial inotropic state, but cannot be used in patients with atrial arrhythmias or high heart rates with fusion of mitral inflow E and A waves [120]. Recently, non-invasive speckle tracking echocardiography (STE) allowed combined regional and global myocardial function assessment [123, 124]. Global peak longitudinal strain (GLS), determined from STE, is a sensitive and feasible method, which overcomes many of the limitations of LVEF. It can be used to elucidate left ventricular dysfunction in septic shock patients in a discontinuous manner, with improved prediction of prognosis after myocardial infarction in comparison with LVEF [125]. However, optimal imaging is necessary, and GLS can be affected by heart rate variability, breathing translation, and choice of region of interest in the myocardium [120, 124].
Clinical perspective
Which monitoring tool should be utilized in specific situations? Actually, Figure 4 shows clearly there is a gradation in invasiveness of haemodynamic monitoring, which should be respected when considering optimal choice of monitoring in an ASA II patient versus a critically ill patient with multiple co-morbidities. The choice of haemodynamic monitoring depends on the availability, acquaintance and experience of the team with the type of monitoring, the pathology presented and the degree of urgency. Furthermore, the time to implement one of the different monitoring tools also plays an important role in the choice. Hence, transoesophageal echocardiography and Doppler has a very short time to organize and implement, whereas a PAC necessitates a well-organized support by a nurse.
Still, a PAC, including SvO2 monitoring, is nowadays still the clinical standard, particular in patients with right ventricular failure and pulmonary hypertension. Whereas these patients benefit from pulmonary artery pressure monitoring, achieved by a PAC, right ventricular systolic function follow-up could be more easily performed by means of cardiac ultrasound, in particular transoesophageal echocardiography. The latter allows valvular function, most importantly of the tricuspid and pulmonary valve, to monitor pulmonary artery pressures from regurgitant flow velocities.
Also, patients with severe left ventricular dysfunction need close follow-up, avoiding fluid overload and keeping these patients relatively dry. Intraoperative monitoring could be done combining transoesophageal echocardiography (short axis view of the left ventricle in conjunction with mitral valve regurgitation and transaortic valve flow assessment) with an arterial monitoring system, allowing monitoring of stroke volume, SVV and cardiac power, if available. The latter monitoring system could be continued in the postoperative phase.
Even less invasive haemodynamic monitoring could be utilized in patients in whom no real cardiac burden is present and absence of aggressive surgery, but fluid and insensible losses could be considerable following long-term and extensive procedures (e.g. extensive plastic surgery with DIEP flap and breast reconstruction, open laparotomy).
In all cases, anaesthesiologists should aim for early goal-directed haemodynamic monitoring, including low lactate levels and perfusion pressures max. 20% below normal life perfusion pressure, aiming at preservation of homeostasis and body temperature.
Conclusions
There is an abundance of new minimally invasive or non-invasive, continuous and real-time monitors of cardiac function, perfusion and fluid responsiveness. Even though many studies have been and are being devoted to assessing the value of these monitors and their trending parameters, it is still far too early to confirm the effects these devices might have on outcome. It is important to master all levels of haemodynamic monitoring techniques – from completely non-invasive to minimally invasive and up to invasive monitoring – and acknowledge the limitations and shortcomings of all monitoring tools. Information from a haemodynamic monitor should be confirmed by data from another monitoring system to guarantee precise diagnosis (Figure 3), and thus correct management and optimization of the patient’s loading conditions and heart contractility.
Acknowledgements
1. Financial support and sponsorship: none.
2. Conflict of interest: none.
References
1. Corcoran T, Rhodes JE, Clarke S, Myles PS, Ho KM. Perioperative fluid management strategies in major surgery: a stratified meta-analysis. Anesth Analg 2012; 114: 640-651. doi: 10.1213/ANE.0b013e318240d6eb.
2. Magder SA. The highs and lows of blood pressure: toward meaningful clinical targets in patients with shock. Crit Care Med 2014; 42: 1241-1251. doi: 10.1097/CCM.0000000000000324.
3. Poelaert J, Schupfer G. Hemodynamic monitoring utilizing transesophageal echocardiography: the relationships among pressure, flow, and function. Chest 2005; 127: 379-390. doi: 10.1378/chest.127.1.379.
4. Poelaert J. Assessment of loading conditions with cardiac ultrasound. A comprehensive review. Anaesthesiol Intensive Ther 2015; 47: 464-470. doi: 10.5603/AIT.a2015.0068.
5. Monge Garcia MI, Jian Z, Settels JJ, et al. Performance comparison of ventricular and arterial dP/dtmax for assessing left ventricular systolic function during different experimental loading and contractile conditions. Crit Care 2018; 22: 325. doi: 10.1186/s13054-018-2260-1.
6. Kraut JA, Madias NE. Lactic acidosis. N Engl J Med 2014; 371: 2309-2319. doi: 10.1056/NEJMra1309483.
7. Boldt J. Clinical review: Hemodynamic monitoring in the intensive care unit. Crit Care 2002; 6: 52-59. doi: 10.1186/cc1453.
8. Spoelstra-de Man AM, Smorenberg A, Groeneveld AB. Different effects of fluid loading with saline, gelatine, hydroxyethyl starch or albumin solutions on acid-base status in the critically ill. PLoS One 2017; 12: e0174507. doi: 10.1371/journal.pone.0174507.
9. Walley KR. Use of central venous oxygen saturation to guide therapy. Am J Respir Crit Care Med 2011; 184: 514-520. doi: 10.1164/rccm.201010-1584CI.
10. Stucchi R, Poli G, Fumagalli R. Haemodynamic monitoring in ICU. Minerva Anesth 2006; 72: 483-487.
11. Dres M, Monnet X, Teboul JL. Hemodynamic management of cardiovascular failure by using PCO(2) venous-arterial difference. J Clin Monit Comput 2012; 26: 367-374. doi: 10.1007/s10877-012-9381-x.
12. Mallat J, Lemyze M, Tronchon L, Vallet B, Thevenin D. Use of venous-to-arterial carbon dioxide tension difference to guide resuscitation therapy in septic shock. World J Crit Care Med 2016; 5: 47-56. doi: 10.5492/wjccm.v5.i1.47.
13. Boldt J, Ince C. The impact of fluid therapy on microcirculation and tissue oxygenation in hypovolemic patients: a review. Intensive Care Med 2010; 36: 1299-1308. doi: 10.1007/s00134-010-1912-7.
14. Magee G, Zbrozek A. Fluid overload is associated with increases in length of stay and hospital costs: pooled analysis of data from more than 600 US hospitals. Clinical Outcomes Res 2013; 5: 289-296. doi: 10.2147/CEOR.S45873.
15. Bentzer P, Griesdale DE, Boyd J, MacLean K, Sirounis D, Ayas NT. Will this hemodynamically unstable patient respond to a bolus of intravenous fluids? JAMA 2016; 316: 1298-1309. doi: 10.1001/jama. 2016.12310.
16. Michard F, Teboul JL. Predicting fluid responsiveness in ICU patients: a critical analysis of the evidence. Chest 2002; 121: 2000-2008. doi: 10.1378/chest.121.6.2000.
17. Cannesson M, Le Manach Y, Hofer CK, et al. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a “gray zone” approach. Anesthesiology 2011; 115: 231-241. doi: 10.1097/ALN.0b013e318225b80a.
18. Joosten A, Alexander B, Delaporte A, Lilot M, Rinehart J, Cannesson M. Perioperative goal directed therapy using automated closed-loop fluid management: the future? Anaesthesiol Intensive Ther 2015; 47: 517-523. doi: 10.5603/AIT.a2015.0069.
19. Cherpanath TG, Hirsch A, Geerts BF, et al. Predicting fluid responsiveness by passive leg raising: a systematic review and meta-analysis of 23 clinical trials. Crit Care Med 2016; 44: 981-991. doi: 10.1097/CCM. 0000000000001556.
20. Georges D, de Courson H, Lanchon R, Sesay M, Nouette-Gaulain K, Biais M. End-expiratory occlusion maneuver to predict fluid responsiveness in the intensive care unit: an echocardiographic study. Crit Care 2018; 22: 32. doi: 10.1186/s13054-017-1938-0.
21. Biais M, de Courson H, Lanchon R, et al. Mini-fluid chanllenge of 100 ml of crystalloid predicts fluid responsiveness in the operating room. Anesthesiology 2017; 127: 450-456. doi: 10.1097/ALN. 0000000000001753.
22. Carsetti A, Cecconi M, Rhodes A. Fluid bolus therapy: mornitoring and predicting fluid responsiveness. Curr Opin Crit Care 2015; 21: 388-394. doi: 10.1097/MCC.0000000000000240.
23. Monnet X, Marik PE, Teboul JL. Prediction of fluid responsiveness: an update. Ann Intensive Care 2016; 6: 111. doi: 10.1186/s13613-016-0216-7.
24. Bisis M, Larghi M, Henriot J, de Courson H, Sesay M, Nouette-Gaulain K. End-expiratory occlusion test predicts fluid responsiveness in patients with protective ventilation in the operating room. Anesth Analg 2017; 125: 1889-1895. doi: 10.1213/ANE.0000000000002322.
25. Myatra SN, Prabu NR, Divatia JV, Monnet X, Kulkarni AP, Teboul JL. The changes in pulse pressure variation or stroke volume variation after a “tidal volume challenge’’ reliably predict fluid responsiveness during low tidal volume ventilation. Crit Care Med 2017; 45: 415-421. doi: 10.1097/CCM.0000000000002183.
26. Convertino VA, Ludwig DA, Cooke WH. Stroke volume and sympathetic responses to lower-body negative pressure reveal new insight into circulatory shock in humans. Auton Neurosci 2004; 111: 127-134. doi: 10.1016/j.autneu.2004.02.007.
27. Rathore A, Singh S, Lamsal R, Taank P, Paul D. Validity of Pulse Pressure Variation (PPV) Compared with Stroke Volume Variation (SVV) in Predicting Fluid Responsiveness. Turk J Anaesthesiol Reanim 2017; 45: 210-217. doi: 10.5152/TJAR.2017.04568.
28. Trifi A, Abdellatif S, Daly F, Nasri R, Touil Y, Ben Lakhal S. Ultrasound stroke volume variation induced by passive leg raising and fluid responsiveness: an observational cohort study. Med Intensiva 2019; 43: 10-17. doi: 10.1016/j.medin.2017.11.002.
29. De Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med 2005; 31: 517-523. doi: 10.1007/s00134-005-2586-4.
30. Grassi P, Lo Nigro L, Battaqlia K, Barone M, Testa F, Berlot G. Pulse pressure variation as a predictor of fluid responsiveness in mechanically ventilated patients with spontaneous breathing activity: a pragmatic observation study. HSR Proc Intensive Care Cardiovascular Anesth 2013; 5: 98-109.
31. Yi L, Liu Z, Qiao L, Wan C, Mu D. Does stroke volume variation predict fluid responsiveness in children: A systematic review and meta-analysis. PLoS One 2017; 12: e0177590. doi: doi: 10.1371/journal.pone.0177590.
32. Preisman S, DiSeqni E, Vered Z, Perel A. Left ventricular preload and function during graded haemorrhage and retransfusion in pigs: analysis of arterial pressure waveform and correlation with echocardiography. Br J Anaesth 2002; 88: 716-718. doi: 10.1093/bja/88.5.716.
33. Leung JM, Levine E. Left ventricular end-systolic cavity obliteration as an estimate of intraoperative hypovolemia. Anesthesiology 1994; 81: 1102-1109.
34. Vignon P, Repessé X, Bégot E, et al. Comparison of echocardiography indices used to predict fluid responsiveness in ventilated patients. Am J Respir Crit Care Med 2017; 195: 1022-1032. doi: 10.1164/rccm.201604-0844OC.
35. Muller L, Bobbia X, Toumi M, et al. Respiratory variations of inferior vena cava diameter to predict fluid responsiveness in spontaneously breathing patients with acute circulatory failure: need for a cautious use. Crit Care 2012; 16: R188. doi: 10.1186/cc11672.
36. Eskesen TG, Wetterslev M, Perner A. Systematic review including re-analyses of 1148 individual data sets of central venous pressure as a predictor of fluid responsiveness. Intensive Care Med 2016; 42: 324-332. doi: 10.1007/s00134-015-4168-4.
37. Magder S. Right Atrial pressure in the critically ill: how to measure, what is the value, what are the limitations? Chest 2017; 151: 908-916. doi: 10.1016/j.chest.2016.10.026.
38. Swenson J, Bull D. Intraoperative diagnosis and treatment of pleural effusion based on transesophageal echocardiographic findings. Anesth Analg 1999; 89: 309-310.
39. Goedje O, Seebauer T, Peyerl M, Pfeiffer U, Reichart B. Hemodynamic mornitoring by double-indicator dilution techenique in patients after orthotopic heart transplantation. Chest 2000; 118: 775-781. doi: 10.1378/chest.118.3.775.
40. Rivers EP, Ander DS, Powell D. Central venous oxygen saturation mornitoring in the critically ill patients. Curr Opin Crit Care 2001; 7: 204-211.
41. Gidwani UK, Goel S. The pulmonary artery cather in 2015: the Swan and the Phoenix. Cardiol Rev 2016; 24: 1-13. doi: 10.1097/CRD. 0000000000000082.
42. Rajaram SS, Desai NK, Kalra A, et al. Pulmonary artery catheters for adult patients in intensive care. Cochrane Database Syst Rev 2013; 28: CD003408. doi: 10.1002/14651858.CD003408.pub3.
43. Schwann NM, Hillel Z, Hoeft A, et al. Lack of effectiveness of the pulmonary artery catheter in cardiac surgery. Anesth Analg 2011; 113: 994-1002. doi: 10.1213/ANE.0b013e31822c94a8.
44. Litton E, Morgan M. The PiCCO monitor: a review. Anaesth Intensive Care 2012; 40: 393-409. doi: 10.1177/0310057X1204000304.
45. Pinsky MR, Teboul JL. Assessment of indices of preload and volume responsiveness. Curr Opin Crit Care 2005; 11: 235-239.
46. Hofer CK, Muller SM, Furrer L, Klaghofer R, Genoni M, Zollinger A. Stroke volume and pulse pressure variation for prediction of fluid responsiveness in patients undergoing off-pump coronary artery bypass grafting. Chest 2005; 128: 848-854. doi: 10.1378/chest.128.2.848.
47. Rex S, Brose S, Metzelder S, et al. Prediction of fluid responsiveness in patients during cardiac surgery. Br J Anaesth 2004; 93: 782-788. doi: 10.1093/bja/aeh280.
48. Mora B, Ince I, Birkenberg B, et al. Validation of cardiac output measurement with the LiDCO™ pulse contour system in patients with impaired left ventricular function after cardiac surgery. Anaesthesia 2011; 66: 675-681. doi: 10.1111/j.1365-2044.2011.06754.x.
49. Menger J, Mora B, Skhirtladze K, Fischer A, Jan Ankersmit H, Dworschak M. Accuracy of Continuous Cardiac Output Measurement With the LiDCOplus System During Intra-Aortic Counterpulsation After Cardiac Surgery. J Cardiothorac Vasc Anesth 2016; 30: 592-598. doi: 10.1053/j.jvca.2015.09.022.
50. Cecconi M, Dawson D, Casaretti R, Grounds RM, Rhodes A. A prospective study of the accuracy and precision of continous cardiac output monitoring devices as compared to intermittent thermodilution. Minerva Anestesiol 2010; 76: 1010-1017.
51. de Wilde RB, Geerts BF, van den Berg PC, Jansen JR. A comparison of stroke volume variation measured by the LiDCOplus and FloTrac-Vigileo system. Anaesthesia 2009; 64: 1004-1009. doi: 10.1213/ane. 0b013e3181ac6dac.
52. Asamoto M, Orii R, Otsuji M, Bougaki M, Imai Y, Yamada Y. Reliability of cardiac output measurements using LiDCOrapid™ and FloTrac/Vigileo™ across broad ranges of cardiac output values. J Clin Monit Comput 2017; 31: 709-716. doi: 10.1007/s10877-016-9896-7.
53. Hamed MA, Goda AS, Eldein RMS. Comparison of goal-directed haemodynamic optimization using pulmonary artery catheter and autocalibrated arterial pressure waveform analysis Vigileo-FloTrac™ system in on-pump coronary artery bypass graft surgery: a randomized controlled studya. Anesth Essays Res 2018; 12: 517-521. doi: 10.4103/aer.AER_58_18.
54. Biais M, Vidil L, Sarrabay P, Cottenceau V, Revel P, Sztark F. Changes in stroke volume induced by passive leg raising in spontaneously breathing patients: comparison between echocardiography and Vigileo/FloTrac device. Critical Care 2009; 13: R195. doi: 10.1186/cc8195.
55. Ganter MT, Alhashemi JA, Al-Shabasy AM, et al. Continuous cardiac output measurement by uncalibrated pulse wave analysis and pulmonary artery catheter in patients with septic shock. J Clin Monit Comput 2016; 30: 13-22. doi: 10.1007/s10877-015-9672-0.
56. Biais M, Nouette-Gaulain K, Roullet S, Quinart A, Revel P, Szatark F. A comparison of stroke volume variation measured by Vigileo/Flo Trac system and aortic Doppler echocardiography. Anesth Analg 2009; 109: 466-469. doi: 10.1213/ane.0b013e3181ac6dac.
57. Skarvan K, Lambert A, Filipovic M, Seeberger M. Reference values for left ventricular function in subjects under general anaesthesia and controlled ventilation assessed by two-dimensional transoesophageal echocardiography. Eur J Anaesthesiol 2001; 18: 713-722.
58. Vieillard-Baron A, Chergui K, Rabiller A, et al. Superior vena caval collapsibility as a gauge of volume status in ventilated septic patients. Intensive Care Med 2004; 30: 1734-1739. doi: 10.1007/s00134-004-2361-y.
59. Barbier C, Loubieres Y, Schmit C, et al. Respiratory changes in inferior vena cava diameter are helpful in predicting fluid responsiveness in ventilated septic patients. Intensive Care Med 2004; 30: 1740-1746. doi: 10.1007/s00134-004-2259-8.
60. Slama M, Masson H, Teboul JL, et al. Respiratory variations of aortic VTI: a new index of hypovolemia and fluid responsiveness. Am J Physiol Heart Circ Physiol 2002; 283: H1729-1733. doi: 10.1152/ajpheart.00308.2002.
61. Feissel M, Michard F, Mangin I, Ruyer O, Faller JP, Teboul JL. Respiratory changes in aortic blood velocity as an indicator of fluid responsiveness in ventilated patients with septic shock. Chest 2001; 119: 867-873. doi: 10.1378/chest.119.3.867.
62. Dark PM, Singer M. The validity of trans-esophageal Doppler ultrasonography as a measure of cardiac output in critically ill adults. Intensive Care Med 2004; 30: 2060-2066. doi: 10.1007/s00134-004-2430-2.
63. Cioccari L, Baur HR, Berger D, et al. Hemodynamic assessment of critically ill patients using a miniaturized transesophageal echocardiaography probe. Crit Care 2013; 17: R121. doi: 10.1186/cc12793.
64. Jorgensen MR, Juhl-Olsen P, Frederiksen CA, Sloth E. Transthoracic echocardiography in the perioperative setting. Curr Opin Anaesthesiol 2016; 29: 46-54. doi: 10.1097/ACO.0000000000000271.
65. Mielnicki W, Dyla A, Zawada T. Utility of transthoracic echocardiography (TTE) in assessing fluid responsiveness in critically ill patients – a challenge for the bedside sonographer. Med Ultrason 2016; 18: 508-514. doi: 10.11152/mu-880.
66. Mercado P, Maizel J, Beyls C, et al. Transthoracic echocardiography: an accurate and precise method for estimating cardiac output in the critically ill patient. Crit Care 2017; 21: 136. doi: 10.1186/s13054-017-1737-7.
67. Blanco P, Aguiar FM, Blaivas M. Rapid Ultrasound in Shock (RUSH) Velocity-Time Integral: A Proposal to Expand the RUSH Protocol. J Ultrasound Med 2015; 34: 1691-1700. doi: 10.7863/ultra.15.14.08059.
68. Bou Chebl R, Wuhantu J, Kiblawi S, Carnell J. Bedside echocardiography and passive leg raise as a measure of volume responsiveness in the emergency department. J Ultrasound Med 2019; 38: 1319-1326. doi: 10.1002/jum.14812.
69. Marik PE, Levitov A, Young A, Andrews L. The use of bioreactance and carotid Doppler to determine volume responsiveness and blood flow redistribution following passive leg raising in haemodynamically unstable patients. Chest 2013; 143: 364-370. doi: 10.1378/chest.12-1274.
70. Szmuk P, Pivalizza E, Warters RD, Ezri T, Gebhard R. An evaluation of the T-Line Tensymeter continuous noninvasive blood pressure device during induced hypotension. Anaesthesia 2008; 63: 307-312. doi: https://doi.org/10.1111/j.1365-2044.2007.05369.x.
71. Wagner JY, Sarwari H, Schon G, et al. Radial artery applanation tonometry for continuous noninvasive cardiac output measurement: a comparison with intermittent pulmonary artery thermodilution in patients after cardiothoracic surgery. Crit Care Med 2015; 43: 1423-1428. doi: 10.1097/CCM.0000000000000979.
72. Raggi EP, Sakai T. Update on finger-application-type noninvasive continuous haemodynamic monitors (CNAP and ccNexfin): physical principles, validation, and clinical use. Semin Cardiothorac Vasc Anesth 2017; 21: 321-329. doi: 10.1177/1089253217708620.
73. Renner J, Gruenewald M, Hill M, et al. Non-invasive assessment of fluid responsiveness using CNAP™ technology is interchangeable with invasive arterial measurements during major open abdominal surgery. Br J Anesth 2017; 118: 58-67. doi: 10.1093/bja/aew399.
74. Saugel B, Meidert AS, Langwieser N, et al. An autocalibrating algorithm for non-invasive cardiac output determination based on the analysis of an arterial pressure waveform recorded with radial artery applanation tonometry: a proof of concept pilot analysis. J Clin Monit Comput 2014; 28: 357-362. doi: 10.1007/s10877-013-9540-8.
75. Ameloot K, Van De Vijver K, Broch O, et al. Nexfin noninvasive continuous haemodynamic monitoring validation against continuous contour and intermittent transpulmonary thermodilution derived cardiac output in critically ill patients. Scientific World Journal 2013; 2013: 519080. doi: 10.1155/2013/519080.
76. Bubenek-Turconi SI, Craciun M, Miclea I, Perel A. Noninvasive continuous cardiac output by the Nexfin before and after preload modifying maneuvers: a comparison with intermittent thermodilution cardiac output. Anesth Analg 2013; 117: 366-372. doi: 10.1213/ANE.0b013e31829562c3.
77. Lansdorp B, Ouweneel D, de Keijzer A, van der Hoeven JG, Lemson J, Pickkers P. Non-inasive measurement of pluse pressure variation and systolic pressure variation using a finger cuff corresponds with intra-arterial measurement. Br J Anesth 2011; 107: 540-545. doi: 10.1093/bja/aer187.
78. Stens J, Oeben J, Van Dusseldorp AA, Boer C. Non-invasive measurements of pulse pressure variation and stroke volume variation in anesthetized patients using the Nexfin blood pressure monitor. J Clin Monit Comput 2016; 30: 587-594. doi: 10.1007/s10877-015-9759-7.
79. Wagner JY, Grond J, Fortin J, Negulescu I, Schofthaler M, Saugel B. Continuous noninvasive cardiac output determination using the CNAP system: evaluation of a cardiac output algorithm for the analysis of volume clamp method-derived pulse contour. J Clin Monit Comput 2016; 30: 487-493. doi: 10.1007/s10877-015-9744-1.
80. Monnet X, Picard F, Lidzborski E, et al. The estimation of cardiac output by the Nexfin device is poor reliability for tracking the effects of a fluid challenge. Crit Care 2012; 16: R212. doi: 10.1186/cc11846.
81. Taton O, Fagnoul D, De Backer D, Vincent JL. Evaluation of cardiac output in intensive care using a non-invasive arterial pluse contour technique(Nexfin(®) compared with echocardiography. Anesthesia 2013; 68: 917-923. doi: 10.1111/anae.12341.
82. Cannesson M, Desebbe O, Rosamel P, et al. Pleth variability index to monitor the respiratory variations in the pulse oximeter plethysmographic waveform amplitude and predict fluid responsiveness in the operating theatre. Br J Anaesth 2008; 101: 200-206. doi: 10.1093/bja/aen133.
83. Forget P, Lois F, deKock M. Goal-directed fluid management based on the pulse oximeter-derived pleth variability index reduces lactate levels and improves fluid management. Anesth Analg 2010; 111: 910-914. doi: 10.1213/ANE.0b013e3181eb624f.
84. Joosten A, Raj Lawrence S, Colesnicenco A, et al. Personalized versus protocolized fluid management using noninvasive haemodynamic monitoring (Clearsight System) in patients undergoing moderate-risk abdominal surgery. Anesth Analg 2019; 129: e8-e12. doi: 10.1213/ANE.0000000000003553.
85. Botero M, Kirby D, Lobato EB, Staples ED, Gravenstein N. Measurement of cardiac output before and after cardiopulmonary bypass: comparison among aortic transit-time ultrasound, thermodilution, and non-invasive partial CO2 rebreathing. J Cardiothorac Vasc Anesth 2004; 18: 563-572.
86. Kotake Y, Yamada T, Nagata H, et al. Improved accuracy of cardiac output estimation by the partial CO2 rebreathing method. J Clin Monit Comput 2009; 23: 149-155. doi: 10.1007/s10877-009-9172-1.
87. Ng JM, Chow MY, Ip-Yam PC, Goh MH, Agasthian T. Evaluation of partial carbon dioxide rebreathing cardiac output measurement during thoracic surgery. J Cardiothorac Vasc Anesth 2007; 21: 655-658. doi: 10.1053/j.jvca.2007.01.012.
88. Rocco M, Spadetta G, Morelli A, et al. A comparative evaluation of thermodilution and partial CO2 rebreathing techniques for cardiac output assessment in critically ill patients during assisted ventilation. Intensive Care Med 2004; 30: 82-87.
89. Valiatti JL, Amaral JL. Comparison between cardiac output values measured by thermodilution and partial carbon dioxide rebreathing in patients with acute lung injury. Sao Paulo Med J 2004; 122: 233-238. doi: /S1516-31802004000600002.
90. Sugo Y, Akiyama T, Takeda S, Ishihara H. A non-invasive continuous cardiac output measurement method utilizing ECG and SpO2 pulse wave. Jpn Med Instrum 2005; 75: 63-69. doi: 10.1109/IEMBS.2010.5626343.
91. Yamada T, Tsutsui M, Sugo Y, et al. Multicenter study verifying a method of noninvasive continuous cardiac output measurement using pulse wave transit time: a comparison with intermittent bolus thermodilution cardiac output. Anesth Analg 2012; 115: 82-87. doi: 10.1213/ANE.0b013e31824e2b6c.
92. Smetkin AA, Hussain A, Fot EV, et al. Estimated continuous cardiac output based on pulse wave transit time in off-pump coronary artery bypass grafting: a comparison with transpulmonary thermodilution. J Clin Monit Comput 2017; 31: 361-370. doi: 10.1007/s10877-016-9853-5.
93. Magliocca A, Rezoagli E, Anderson TA, Burns SM, Ichinose F, Chitilian HV. Cardiac output measurements based on the pulse wave transit time and thoracic impedance exhibit limited agreement with thermodilution method during orthotopic liver transplantation. Anesth Analg 2018; 126: 85-92. doi: 10.1213/ANE.0000000000002171.
94. Suzuki T, Suzuki Y, Okuda J, et al. Cardiac output and stroke volume variation measured by the pulse wave transit time method: a comparison with an arterial pressure-based cardiac output system. J Clin Monit Comput 2019; 33: 385-392. doi: 10.1007/s10877-018-0171-y.
95. Biais M, Berthezene R, Petit L, Cottenceau V, Sztark F. Ability of esCCO to track changes in cardiac output. Br J Anaesth 2015; 115: 403-410. doi: 10.1093/bja/aev219.
96. Galarza L, Mercado P, Teboul JL, et al. Estimating the rapid haemodynamic effects of passive leg raising in critically ill patients using bioreactance. Br J Anaesth 2018; 121: 567-573. doi: 10.1016/j.bja.2018.03.013.
97. Koobi T, Kahonen M, Koskinen M, Kaukinen S, Turjanmaa VM. Comparison of bioimpedance and radioisotope methods in the estimation of extracellular water volume before and after coronary artery bypass grafting operation. Clin Physiol 2000; 20: 283-291.
98. Spiess BD, Patel MA, Soltow LO, Wright IH. Comparison of bioimpedance versus thermodilution cardiac output during cardiac surgery: evaluation of a second-generation bioimpedance device. J Cardiothorac Vasc Anesth 2001; 15: 567-573. doi: 10.1053/jcan.2001. 26533.
99. Lorne E, Mahjoub Y, Diouf M, et al. Accuracy of impedance cardiography for evaluating trends in cardiac output: acomparison with oesophageal Doppler. Br J Anaesth 2014; 113: 596-602. doi: 10.1093/bja/aeu136.
100. Critchley LA, Calcroft RM, Tan PY, Kew J, Critchley JA. The effect of lung injury and excessive lung fluid, on impedance cardiac output measurements, in the critically ill. Intensive Care Med 2000; 26: 679-685.
101. Kamath SA, Drazner MH, Tasissa G, Rogers JG, Stevenson LW, Yancy CW. Correlation of impedance cardiography with invasive haemodynamic measurements in patients with advanced heart failure: the bioimpedance cardiography (BIG) substudy of the evaluation study of congestive heart failure and pulmonary artery catheterization effectiveness (ESCAPE) trial. Am Heart J 2009; 158: 217-223. doi: 10.1016/j.ahj.2009.06.002.
102. Keren H, Burkhoff D, Squara P. Evaluation of a noninvasive continuous cardiac output monitoring system based on thoracic bioreactance. Am J Physiol Heart Circ Physiol 2007; 293: H583-589. doi: 10.1152/ajpheart.00195.2007.
103. Squara P, Rotcajg D, Denjean D, Estagnasie P, Brusset A. Comparison of monitoring performance of Bioreactance vs. pulse contour during lung recruitment maneuvers. Crit Care 2009; 13: R125. doi: 10.1186/cc7981.
104. De Pascale G, Singer M, Brealey D. Comparison of stroke volume measurement between non-invasive bioreactance and esophageal Doppler in patients undergoing major abdominal-pelvic surgery. J Anesth 2017; 31: 545-551. doi: 10.1007/s00540-017-2351-1.
105. Teboul JL, Saugel B, Cecconi M, et al. Less invasive haemodynamic monitoring in critically ill patients. Intensive Care Med 2016; 42: 1350-1359. doi: 10.1007/s00134-016-4375-7.
106. Monge Garcia ML, Guijo Gonzalez P, Gracia Romero M, et al. Effects of fluid administration on arterial load in septic shock patients. Intensive Care Med 2015; 41: 1247-1255. doi: 10.1007/s00134-015-3898-7.
107. Garcia ML, Romero MG, Cano AG, et al. Dynamic arterial elastance as a predictor of arterial pressure response to fluid adinisteration: a validation study. Crit Care 2014; 18: 626. doi: 10.1186/s13054-014-0626-6.
108. Lanchon R, Nouette-Gaulain K, Stecken L, Sesay M, Lefrant JY, Biais M. Dynamic arterial elastance obtained using arterial signal does not predict an increase in arterial pressure after a volume expansion in the operating room. Anaesth Crit Care Pain Med 2017; 36: 377-382. doi: 10.1016/j.accpm.2017.05.001.
109. Monge Garcia Ml, Gil Cano A, Gracia Romero M. Dynamic arterial elastance to predict arterial pressure response to volume loading in preload-dependent patients. Crit Care 2011; 15: R15. doi: 10.1186/cc9420.
110. Cecconi M, Monge Garcia MI, Gracia Romero M, et al. 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. Anesth Analg 2015; 120: 76-84. doi: 10.1213/ANE.0000000000000442.
111. Schmidt C, Roosens C, Struys M, et al. Contractility in humans after coronary artery surgery. Anesthesiology 1999; 91: 58-70.
112. Pinsky MR. Probing the limits of arterial pulse contour analysis to predict preload responsiveness. Anesth Analg 2003; 96: 1245-1247.
113. Lanchon R, Nouette-Gaulain K, Stecken L, Sesay M, Lefrant JY, Biais M. Dynamic arterial elastance obtained using arterial signal does not predict an increase in arterial pressure after a volume expansion in the operating room. Anesth Crit Care Pain Med 2017; 36: 377-382. doi: 10.1016/j.accpm.2017.05.001.
114. Monge Garcia MI, Gil Cano A, Gracia Romero M. Dynamic arterial elastanceto predict arterial pressure response to volume loading in preload-dependent patients. Crit Care 2011; 15: R15. doi: 10.1186/cc9420.
115. Heerman JR, Segers P, Roosens CD, Gasthuys F, Verdonck PR, Poelaert JI. Echocardiographic assessment of aortic elastic properties with automated border detection in an ICU: in vivo application of the arctangent Langewouters model. Am J Physiol Heart Circ Physiol 2005; 288: H2504-2511. doi: 10.1152/ajpheart.00368.2004.
116. Vallée F, Le Gall A, Joachim J, et al. Beat-by-beat assessment of cardiac afterload using descending aortic velocity-pressure loop during general anesthesia: a pilot study. J Clin Monit Comput 2018; 32: 23-32. doi: 10.1007/s10877-017-9982-5.
117. Sahlen A, Hamid N, Amanullah MR, et al. Impact of aortic root size on left ventricular afterload and stroke volume. Eur J Appl Physiol 2016; 116: 1355-1365. doi: 10.1007/s00421-016-3392-0.
118. Galderisi M, Lomoriello V, Santoro A, et al. Differences of myocardial systolic deformation and correlates of diastolic function in competitive rowers and young hypertensives: a speckle-tracking echocardiography study. J Am Soc Echocardiogr 2010; 23: 1190-1198. doi: 10.1016/j.echo.2010.07.010.
119. Klaeboe LG, Edvardsen T. Echocardiographic assessment of left ventricular systolic function. J Echocardiogr 2019; 17: 10-16. doi: 10.1007/s12574-018-0405-5.
120. Sharir T, Feldman MD, Haber H, et al. Ventricular systolic assessment in patients with dilated cardiomyopathy by preload-adjusted maximal power. Validation and noninvasive application. Circulation 1994; 89: 2045-2053. doi: https://doi.org/10.1161/01.CIR.89.5.2045.
121. Fincke R, Hochman JS, Lowe AM, et al. Cardiac power is the strongest hemodynamic correlate of mortality in cardiogenic shock: a report from the SHOCK trial registry. J Am Coll Cardiol 2004; 44: 340-348. doi: 10.1016/j.jacc.2004.03.060.
122. Jasaityte R, Claus P, Teske AJ, et al. The slope of the segmental stretch-strain relationship as a noninvasive index of LV inotropy. JACC Cardiovasc Imaging 2013; 6: 419-428. doi: 10.1016/j.jcmg.2012.10.022.
123. Ng PY, Sin WC, Ng AK, Chan WM. Speckle tracking echocardiography in patients with septic shock: a case control study (SPECKSS). Crit Care 2016; 20: 145. doi: 10.1186/s13054-016-1327-0.
124. Wdowiak-Okrojek K, Wejner-Mik P, Kasprzak JD, Lipiec P. Recovery of regional systolic and diastolic myocardial function after acute myocardial infarction evaluated by two dimensional speckle tracking echocardiography. Clin Physiol Funct Imaging 2019; 39: 177-181. doi: 10.1111/cpf.12553.
125. Antoni ML, Mollema SA, Delgado V, et al. Prognostic importance of strain and strain rate after acute myocardial infarction. Eur Heart J 2010; 31: 1640-1647. doi: 10.1093/eurheartj/ehq105.
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