Predicting Fluid Responsiveness a Review of Literature and a Guide for the Clinician
Introduction
Infusion therapy is a medication; it has a dose, indications and side effects. Unfortunately, fluid therapy has a narrow therapeutic index, which makes over- and under-dosing easy. The higher the patient fragility, the more than complex the illness and the more astringent the status, the more likely is for patient harm to ensue due to unintentional fluid overload or restriction. This warrants particular attending to optimizing and individualizing infusion therapy in the perioperative setting. Scientific data bear witness that both restrictive and liberal protocols for fluid therapy are associated with increased charge per unit of complications [ane]. Because of this, in the last 20 years, a pregnant body of research was aimed at developing new methods for fluid responsiveness prediction [2]. The initial work of Marik et al. [iii] defined fluid responsiveness as an increase in cardiac output past 10% or more after a fluid bolus. According to these authors, fluid loading should be initialized only if an increase of cardiac output is needed and probable to exist acquired. Of form, if in that location is obvious fluid loss, actual or relative (similar initial phase of septic shock or exsanguination), administration of fluids should not be delayed. However, after initial resuscitation in that location is a stage where it is not axiomatic if and how much more fluid is needed. In such cases fluid prediction is necessary to avert complications. For example, the published Marik-Phillips bend [4] shows that administering fluids when the heart functions on the flat slope of the Frank-Starling bend leads to a steep increase in extravascular lung water (EVLW). Research focussed on prediction of fluid responsiveness followed naturally after hundreds of studies stated that static indices of preload like central venous pressure (CVP) have an extremely depression predictive value [v–vii]. The aim of this review is to await at different available methods for predicting fluid responsiveness, as well as their positive and negative sides.
Static indices of preload
These are the central venous pressure (CVP), pulmonary avenue occlusion pressure (PAOP), left ventricle end-diastolic pressure (LVEDP), left ventricular end-diastolic area (LVEDA), left ventricular terminate-diastolic volume (LVEDV), global end-diastolic volume (GEDV), inferior vena cava diameter and other related variables indicative of the momentary middle preload.
CVP is the most popular of all, because information technology is well known, easily obtainable and has a long tradition of use in the operating room OR and intensive care unit (ICU). CVP is used every bit a preload alphabetize of the right ventricle and to a lesser extent of the left ventricle. The following basic physiology principles in the stop-diastole CVP equalizes consecutively to the end diastolic force per unit area in the right ventricle, pulmonary artery, pulmonary capillaries, left atrium and left ventricle. LVEDP is related to LVEDV, which determines the LV preload. Based on the Frank-Starling law, higher preload means higher stroke book up to a certain point. Having these assumptions in mind information technology is highly-seasoned to conclude that higher CVP means college cardiac output up to a certain threshold. Official guidelines state a CVP value of at least 8 mmHg should exist achieved in resuscitation of septic stupor [8]. However, a more than complex analysis of the to a higher place mentioned warrants some criticism.
The problems with the use of CVP first with its measurement [9]. In order to measure CVP a central venous catheter needs to be placed, which is an invasive manipulation and can lead to complications. The anatomic location for the measurement of CVP is the junction of vena cava and the right atrium, that is where the central venous catheter tip should exist positioned. Manipulation of the catheter by staff, passive or active patient repositioning can change the catheter tip position leading to false measurement of CVP [x].
Furthermore, it is known that in patients with heart conditions (valve lesions, pulmonary hypertension, etc.) CVP differs significantly from the LVEDP [11]. More importantly the LVED pressure level-volume relationship is unpredictable in unlike patients and depends on factors such as eye crenel dimensions and compliance. Inter-individual variations in the gradient and shape of the LVED force per unit area-book bend brand clinical interpretation difficult. Some other trouble when using CVP as a guide for fluid therapy becomes evident if nosotros remember the Gyuton's concept of venous return [12]. Co-ordinate to Equation (1) venous render is modified past CVP. (1)
(ane)
Where VR is venous return; MSFP is hateful systemic filling pressure and Vres is venous resistance.
Low CVP values increase the venous return to the middle. Considering the centre tin pump just as much blood as is returned to information technology, cardiac output is increased past augmentation of venous return. The heart pump has a permissive office on venous render and if CVP rises during loading with fluid that may mean the middle is not capable of taking all the blood that comes [13]. That is why a trend of rising CVP values during fluid loading is not indicative of increasing cardiac output.
A large torso of evidence dating since the 80 s, several hundred papers, experimentally show that CVP has a low predictive value for fluid responsiveness [v–7]. Information technology should non be neglected that CVP depends on so many factors (volume condition, venous capacitance, venous resistance, inotropic country of the heart, tricuspid regurgitation, mechanical ventilation parameters, etc.) that clinical interpretation becomes challenging [5,6]. In addition, the already mentioned physiologic regards underline that it is generally inappropriate to utilize filling pressure as an index for filling volume and more importantly as an index for the future reaction of increased preload.
In spite of the presented limitations, CVP has its role in evaluating haemodynamics. Low CVP values (<vi mmHg) are related to increased likelihood for fluid responsiveness [14]. On the other hand, loftier values (>15 mmHg) increase the risk of peripheral oedema formation and lower the organ perfusion pressure according to Equation (2) (two)
(2)
OPP – organ perfusion pressure; MAP – hateful arterial pressure.
Therefore, high CVP values may be used as an indicator to hold back volume loading [14]. Unfortunately, the majority of patients have a midrange CVP, which is non-informative. In determination, CVP is an of import variable and should exist used in addition to other data in circuitous patient evaluation. Withal, CVP is by and large a poor predictor of fluid responsiveness.
Pulmonary artery occlusion pressure (PAOP) is measured by catheterization of the pulmonary artery and occluding one of the second division branches. Because of the anatomical proximity to the left heart, PAOP is a improve estimate of LVEDP than CVP. Nevertheless, it shares many of the limitations of CVP and, in addition, the procedure to measure it is highly invasive. PAOP also is confirmed to exist a poor predictor of fluid responsiveness [xv]. That is non surprising, having in mind that LVEDP is a poor predictor itself [16]. Even LVEDV cannot be used for this purpose because the relationship between left ventricle filling and LVEDV is dependent on heart cavities characteristics and inotropic land, which are different between individuals and at dissimilar stages of illness [four]. Static hemodynamic parameters, including vena cava dimensions also accept a low predictive value for the response to volume loading, despite being generally informative for preload [17].The predictive value of some popular static parameters is shown in Table 1.
Table 1. Predictive value of static preload indices using data from Marik et al. [three].
Dynamic hemodynamic indices
Initial information for respiratory variation of hemodynamic variables and their relation to book status come up from canis familiaris experiments in the early on 80 s [eighteen]. Thirty years later on these papers served as a basis for human studies. The concept for prediction of fluid responsiveness was developed by Marik et al. [iii] summarizing available scientific data. Used in septic patients for a showtime, this concept turned out to be mostly applicative to mechanically ventilated patients and gained popularity in the international community of anaesthesiology and intensive care. Fluid responsiveness is defined every bit an increase in cardiac output by ten% or more after administration of fluid bolus (about 6 mL/kg torso weight) [iii]. Prediction of fluid responsiveness is conducted by measuring respiratory variation of hemodynamic parameters, such as stroke volume variation (SVV) [19], pulse pressure variation (PPV) [xx] and systolic force per unit area variation (SPV) [21] caused by heart-lung interactions during mechanical ventilation. Intermittent positive pressure level lung inflation causes a rise in intrathoracic pressure, which leads to a sure amount of blood being squeezed out of the pulmonary circulation into the left heart with every tidal jiff. That amount of claret is believed to exist roughly 100–150 mL. According to the Frank-Starling law this is followed by a slight increment in left ventricle's stroke volume (SV) during inspiration if the ventricle is fluid responsive. Reciprocal changes take place during expiration. Therefore, if LV is on the steep portion of the Frank-Starling curve, SV varies to a higher degree, opposing to the case if LV is on the flat portion of the bend. A person in good wellness has a stroke volume variation (SVV) of approximately 10–15%.
SVV is automatically calculated by a monitor software using Equation (iii) (3)
(iii)
Respiratory variation of stroke volume causes also respiratory variation in systolic force per unit area (SPV) and pulse pressure (PPV) because systemic vascular resistance does not change significantly during i breathing bike. PPV is calculated in a similar fashion to SVV using Equation (4). (four)
(iv)
More than recent studies suggest that respiratory variation of the plethysmographic curve can besides exist used for fluid responsiveness prediction. The parameter of interest is called plethysmography variability alphabetize (PVi) [22]. Significant scientific endeavor was aimed at respiratory variation of vena cava diameter, although results came out to disappoint. Ane big study reports an area under the ROC curve of 0.635 for this parameter [23].
The predictive value for fluid responsiveness of some widely used dynamic parameters is shown in Table two.
Tabular array 2. Predictive value of dynamic hemodynamic indices according to meta-analyses.
Dynamic indices of preload show a very good correlation with fluid responsiveness. That allows for independent awarding of these indices without cardiac output measurement for confirmation.
The predictive value of dynamic indices is dependent on some well-known factors. In club to maximize the predictive value, a number of conditions must be fulfilled: regular centre rhythm, controlled mechanical ventilation with Vt at least 8 mL/kg predicted body weight (PBW), no spontaneous breaths, closed chest, no mechanical assist devices generating changes in the arterial force per unit area waveform (ventricular assistance device, intra-aortic balloon pump), no abdominal hypertension [3]. Some of these limitations can be overcome using elementary tricks. For example, if lung protective ventilation is nowadays, tidal volume tin be briefly increased [26]. If there is atrial fibrillation afterwards cardiac surgery, temporary pacing tin be instituted on slightly college rate to achieve a regular rhythm. If there is an implanted intra-aortic balloon pump (IABP), it can exist put on standby for ane infinitesimal [27].
Determining the right threshold of dynamic variables for fluid responsiveness is difficult in clinical practice. The cutting off values vary between 8 and 15% in different reports [28–thirty]. Thus, a grey zone interval must be predictable where the predictive value is not optimal. Nevertheless, a method for overcoming this limitation has been proposed by Min et al. [31]. They elevated the tidal volume from 8 to 12 mL/kg for individuals with a greyness zone PPV and showed that PPV changed to a more informative value – the 'grey zone arroyo'.
Overall, the dynamic variables are useful for fluid responsiveness evaluation when some necessary conditions tin can be met.
Functional hemodynamic tests
These are used to test the position of the heart on the Frank-Starling curve past the bedside. They are divided into ii groups: fluid challenge tests and dynamic tests. Both demand a pre- and mail-intervention measurement of cardiac output to place fluid responders. Therefore, the method of cardiac output measurement, its accuracy and speed of conduction matter significantly.
The almost obvious way to test fluid responsiveness is to utilise fluids. This is the standard or 'maxi' fluid claiming [32]. Unremarkably about 500 mL or a 6–8 mL/kg fluid bolus is delivered for approximately 10–thirty min [33]. Cardiac output is measured before and after the fluid bolus, and if there is an increase of at least ten%, the patient is identified equally a fluid responder. Although still pop, the 'maxi' fluid challenge has important downsides. In a typical case it is needed to evaluate fluid responsiveness several times during the day and so repeated application of fluid challenge can be harmful [2]. The so-chosen mini fluid challenge consists of infusion of a small-scale amount of fluid, 100–150 mL for up to10 min [34]. In this instance, a smaller alter of cardiac output is sought − v%. The mini fluid challenge has a very good predictive value for fluid responsiveness (Table 3).
Table 3. Predictive value of hemodynamic functional tests.
The second group of tests, dynamic tests, change preload in various means without fluid loading. Probably most pop is the passive leg enhance test (PLR) where the intervention consists of passive leg raising for about 5 min [37]. That leads to an car transfusion of near 500 mL from the peripheral to the central venous blood volume. Again, cardiac output is measured earlier and later and an increase of at to the lowest degree 10% is sought. Some authors have reported measuring a alter in pulse pressure instead of cardiac output, although that lowers the predictive value of the PLR test [38]. Echocardiographic measurement of cardiac output or its estimates such every bit left ventricle output tract velocity fourth dimension integral and mitral inflow velocity take also been reportedly used to follow up the hemodynamic response to PLR [39]. On the downside, PLR is hard to perform intraoperatively. In many ICUs, beds can be positioned only in Trendelenburg position, which is non recommended because brain perfusion can be compromised. Using staff for passive leg raising tin can be impractical and is non e'er possible. Nevertheless, PLR is non-invasive, inexpensive and shows a very good predictive value for fluid responsiveness. Information technology must be emphasized that PLR can exist used in spontaneously animate patients with irregular rhythm, as well as the fluid challenge tests.
Some other functional examination is the end-expiratory occlusion test (EEOT). It is performed the same mode as measuring car PEEP: the expiration concord function of the ventilator is used. Expiration hold is connected for 15–30 s (depending on the ventilator make and model) and leads to a drib in intrathoracic pressure, which allows for an increase in venous render and a blood bolus to the right and left centre. If both ventricles are fluid responsive, the cardiac output will ascent briefly. Because the time interval for cardiac output measurement is brusk, a continuous cardiac output monitoring technique must be used. EEOT was described for the first time past Monnet [forty].
Diverse other tests are proposed in the scientific literature, although studies are small, unmarried-centered and evidence is scarce. Such tests apply Valsalva manoeuvre, recruitment of the lungs, etc. for testing the preload reserve of the heart.
In summary, functional fluid responsiveness tests have very high predictive value and can be used in a wider population of patients in comparison to dynamic variables, including spontaneously breathing and arrhythmic patients.
Avant-garde hemodynamic monitoring platforms
There is a rapidly expanding market place for hemodynamic monitoring systems supporting bedside fluid responsiveness evaluation [41]. A number of commercially bachelor devices can be used for measurement of dynamic indices of preload. These platforms usually contain the ability to measure cardiac output, besides, which is needed not only to calculate SVV, but also to couple with dynamic hemodynamic tests. The monitoring systems can be graded in terms of their invasiveness as invasive (cardinal venous line and arterial line needed), mini-invasive (arterial line needed) and not-invasive (no insertion of vascular catheters needed).
Dynamic variables like PPV and SVV are derived using arterial waveform analysis. Arterial waveform is obtained from an arterial catheter connected to a pressure level sensor, which in turn converts the coordinating pressure indicate to digital and allows for software analysis of parameters of interest [42,43].
The aureate standard method for cardiac output measurement is the pulmonary artery thermodilution (PATD) using a pulmonary avenue catheter (PAC). A fluid bolus of known book and temperature is injected in the proximal port of a pulmonary artery catheter. Thermal sensors discover the temperature change at the catheter tip positioned in the pulmonary artery over time. Afterwards software generates thermodilution bend and calculates the blood flow needed to produce it, finer, that is the right ventricle CO. More recent monitors employ transpulmonary thermodilution (TPTD). The same methodology is used, but temperature changes are detected in the femoral rather than in the pulmonary artery. PAC insertion is avoided that way. TPTD devices allow for measurement of useful parameters, such as global ejection fraction and extravascular lung h2o, which bring of import information in sight [44]. Cardiac output tin can be estimated too mini-invasively using pulse contour analysis of the arterial waveform and software incorporated calculation algorithms. That is referred to equally uncalibrated cardiac output [45]. Completely non-invasive measurement of cardiac output is possible in the well-nigh contempo advancements of technology using the two finger-cuff technology. Arterial waveform is derived without arterial catheter using finger plethysmography [46]. Although appealing, the mini- and not-invasive methods for CO measurement accept a high error rate compared with thermodilution CO measurements, which makes them not reliable for the monitoring of critically ill patients. Future innovations improving the accuracy are eagerly awaited. Meanwhile companies accept combined intermittent thermodilution and pulse contour assay derived CO to create the and then-called continuous calibrated cardiac output monitoring systems [47].
Some of the well-known and widely used devices in the field of advanced hemodynamic monitoring are manufactured by the companies Edwards Lifesciences, Pulsion-Getinge and Lidco.
Edwards Lifesciences (Irvine, CA, Usa) produce a number of clinical platforms for advanced monitoring. Hemosphere® is a device incorporating several monitoring systems, including a PAC and the Edwards FloTrac pressure sensor. Hemosphere® derives SVV, PPV and PATD CO. Continuous calibrated CO is also displayed. The EV1000® platform derives SVV and PPV using the Edwards VolumeView sensor. EV1000® provides also continuous calibrated monitoring of cardiac output using transpulmonary thermodilution (TPTD) coupled with pulse contour analysis of the femoral artery waveform. Vigileo® is another monitor which is defended to uncalibrated CO and SVV measurement using the Edwards FloTrac sensor. The Clearsight® system allows not-invasive conclusion of CO, SVV and PPV using two finger pressure cuffs and infrared low-cal plethysmography.
Pulsion-Getinge (Feldkirchen, Germany) is another visitor known for a wide spectrum of hemodynamic monitors. Most popular and established is the PiCCO Technology®, which uses TPTD and arterial waveform analysis to deliver continuous calibrated cardiac output, as well every bit SVV and PPV. PiCCO Applied science® is available equally an integrated module for IntelliVue® and CMS® Patient Monitors from Philips Medical Systems. The Pulsioflex® monitoring system delivers measurement of SVV, PPV and uncalibrated CO using the Pulsion ProAQT sensor. Equally an reward, there is a manual calibration choice for cardiac output using a measurement obtained by a different modality, for instance echocardiography. The non-invasive device of the company is represented past the NICCI Technology®, which allows for non-invasive estimation of SVV, PPV and uncalibrated CO.
Lidco (London, UK) is the producer of the LIDCO monitor. Equally opposing to the thermodilution method, LIDCO uses injection of lithium containing solution for CO measurement. The modify in the lithium concentration over time is used to calculate the cardiac output. The LIDCO monitor comes in iii modalities: a not-invasive (LIDCO Rapid®), a mini-invasive (LIDCO Plus®) and a calibrated one (LIDCO Unity®). Calibration tin exist done via lithium injection or using a manually entered value.
Massimo (Irvine, CA, U.s.a.) offers measurement of PVi® (plethysmography variability index). It is obtained not-invasively using infrared light pulse plethysmography. PVi is obtainable aslope Masimo SET® Pulse Oximetry and Rainbow® Pulse CO-Oximetry.
An interesting addition is the AJL Capstesia Biotablet®. Information technology allows measurement of PPV using a photo of any arterial waveform displayed on a monitor. Information technology was originally offered as a mobile application, at present it is available as a tablet containing the licensed software.
Fluid responsiveness in the COVID-19 era
The COVID-19 pandemic has presented a unique challenge for healthcare around the globe. The quality of intendance can exist jeopardized by staff and resource shortages accompanying high patient volume load on hospitals during virus outbreaks. The methods for fluid responsiveness evaluation are mostly valid for the COVID-19 patients, nevertheless specific considerations must be taken into account. Currently guidelines recommend a restrictive fluid strategy in COVID-nineteen patients with acute respiratory distress syndrome (ARDS) and vasopressor therapy every bit treatment in COVID-19 circulatory shock [48]. Lack of sufficient nursing staff and resources directs clinicians towards elementary, cheap and easy to use methods for fluid responsiveness prediction.
CVP measurement can be get-go to come into play, as most patients in severe condition already have a central line. The predictive value of very low CVP (beneath vi mmHg) shows it is fairly probable that the patient is responsive to fluids. On the other hand, a high CVP value (above xv mmHg) is a good predictor of fluid not-responsiveness [14]. Nonetheless, the majority of patients have a midrange CVP. They are often being ventilated with high PEEP or in prone position which makes CVP reliability fifty-fifty lower.
Dynamic hemodynamic variables tin be useful in the COVID ICU when criteria can exist met. If available, a Vigileo monitor can exist set up to monitor SVV. PVi may also exist measured using one of the Masimo devices discussed higher up. Having that in mind, it must be emphasised that many ARDS patients have very low lung compliance, which makes it difficult to ventilate with a tidal volume of 8 mL/kg [49]. A lower predictive value of dynamic indices is to exist anticipated in these patients.
Fluid challenges are associated with higher risk for circulatory overload when repeatedly done. The mini fluid challenge is more appealing in the setting of COVID-nineteen ARDS. Still cardiac output coupling is needed to evaluate response, which is problematic. If available, echocardiography can exist used to detect a alter in CO or LVOT VTI. Passive leg raise test, or alternatively Trendelenburg position, can be tried in combination with pulse pressure level monitoring if CO cannot be measured.
Complex clinical platforms are cumbersome, and their use requires significant personnel endeavor and skill. Cardiac output thermodilution measurement is difficult in the COVID-19 ICU. An international survey shows that cardiac output is measured predominantly with echocardiography in Europe [50]. A subgroup of patients with COVID-xix have significant myocardial depression due to myocardial injury, septic cardiomyopathy, or right ventricle dysfunction. Interestingly echocardiography revealed hyper-dynamic state (43%), hypovolemia (22%), a left ventricular dysfunction (21%) and a right ventricular dilation (xx%) in critically ill COVID-19 patients [l]. Information technology might be advisable to screen patients with poor response to initial treatment using echocardiography. Previous studies accept pointed out ultrasound machine use as potential gamble factor for virus spread [51]. That can be minimized by dedicating i US machine for the needs of the COVID-19 area of the hospital. Another subset of COVID-19 patients (about x%) present with accompanying diarrhoea [52]. Appropriate rehydration must be ensured before awarding of advanced hemodynamic monitoring.
To summarize, currently no all-time tool for fluid responsiveness assessment in COVID-nineteen critical patients tin can be pointed out. Clinicians must evaluate the clinical context and the characteristics of each method to find the most advisable solution for each particular example. Large-scale studies are needed in that clinical field.
Discussion
A review of the present methods for fluid responsiveness prediction shows that numerous alternatives are at hand depending on the patient condition, equipment availability and clinical setting. None of these methods has absolute sensitivity and specificity and they all have their positive and negative sides. The use of these methods warrants correct identification of most fluid responsive patients.
In add-on, information technology should be emphasised that being fluid responsive is the normal land of apportionment, which is no indication for fluid loading by itself. The methods for prediction of fluid responsiveness should be used together with all other bachelor clinical data. For instance, if cardiogenic lung oedema is present, fluid loading would obviously not be wise even if the patient is fluid responsive.
Criticism has been addressed to the dynamic hemodynamic indices regarding the number of criteria needed for a proficient predictive value. While it is true that well-nigh of the intensive care patients do not meet all criteria co-ordinate to the initial studies in that field, as stated before, uncomplicated techniques can be applied to overcome many of these limitations. These authors have obtained promising results from a study aimed at using stroke volume variation in patients with intra-aortic balloon pump (Getinge) after cardiac surgery [27]. Other groups presented evidence that tidal volumes tin exist increased ('tidal volume challenge' if lung protective ventilation protocol is used) to optimize the SVV predictive value. Transcutaneous or intravenous ventricular pacing tin can be used to achieve regular rhythm if there is atrial fibrillation. Furthermore, all these weather are needed for maximizing the predictive value of dynamic indices. These indices can be used to estimate the likelihood for fluid responsiveness without the to a higher place-mentioned conditions met, however 1 must and then conceptualize a lower predictive value. Thus, if SVV is extremely high or low (>twenty% or <5%) in a spontaneously breathing patient, it is well-nigh probably indicative for fluid responsiveness.
Regarding the functional hemodynamic tests, our research group has interesting preliminary results, not published yet. According to our findings a 'mini' fluid challenge has an even better predictive value than stoke volume variation, which confirms data from cited meta-analyses [16,36]. Furthermore, in our opinion, end expiratory occlusion testing is challenging practically, because cardiac output measurement must be done very quickly at the end of the test. Pulmonary avenue thermodilution with manual injection for measurement like the Edwards Lifesciences Swan-Ganz catheter cannot be used for that purpose. Three sequent measurements with similar thermodilution curves are required for accuracy, which is too slow for capturing the brief hemodynamic event of EEOT. Thus, if EEOT is used in combination with pulmonary artery thermodilution, we would suggest conducting the test iii times and measurement of cardiac output subsequently each test. Alternatively and maybe more accordingly, a continuous calibrated cardiac output monitor such every bit Edwards Lifesciences EV1000 clinical platform or Pulsion – Getinge PICCO Technology could be chosen.
Finally, it cannot be overemphasized that the static indices of preload similar CVP and PAOP are usually not informative of fluid responsiveness. That is especially truthful for mid-range values, which are about common in daily practice.
Conclusions
Based on the bachelor data, dynamic hemodynamic indices and functional tests are good predictors of fluid responsiveness. They should be used in clinical scenarios where the demand of fluids is non obvious. Static indices of preload should also be taken into account when determining the hemodynamic state of the apportionment. However, their value as predictors of fluid responsiveness is express.
Source: https://www.tandfonline.com/doi/full/10.1080/13102818.2021.1960190
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