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Year : 2019  |  Volume : 32  |  Issue : 2  |  Page : 389-396

Predictors of effective fluid therapy in the intensive care unit

1 Department of Anesthesia and ICU, Faculty of Medicine, Menoufia University, Menoufia, Egypt
2 Department of Intensive Care, Ministry of Health, Al Haram Hospital, Giza, Egypt

Date of Submission21-Oct-2017
Date of Acceptance31-Dec-2017
Date of Web Publication25-Jun-2019

Correspondence Address:
Dr. Heba M Naguib
104 Al-Haram Street, Giza, Cairo 32717
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/mmj.mmj_721_17

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Static and dynamic indices predicting fluid responsiveness (FR) in critically ill patients, physiological basis, advantages, disadvantages, and cut-off values for each method.
Materials and methods
Medical textbooks, Medscape, PubMed, and the ScienceDirect. The databases were searched from the start date of the database and a search was performed on May 2016 with no language restriction. The initial search found 25 articles of which 15 met the inclusion criteria that address preload responsiveness, FR, and cardiac output monitoring devices. Extraction was carried out depending on the validity, quality, and originality of the selected reviews and studies; and the focus was on studies that presented the latest updated findings on FR in the ICU. Each review and study was reviewed independently without intercomparisons. The layout was selected to present a big data including the most updated findings on the subject.
Dynamic indices predicting FR in the ICU provide the best prognosis and outcome. Early detection of fluid nonresponsive patients in the ICU will help avoid fluid overload, which is an independent predictor of mortality.
Dynamic FR monitoring methods are preferable to static methods. Each dynamic method has its benefits and limitations. Inferior vena cava (IVC) sonography such as IVC collapsibility, IVC distensibillity, and delta IVC might provide a valuable tool and alternate approach for guidance of fluid therapy in spontaneously breathing and mechanically ventilated patients, respectively.

Keywords: acute circulatory failure, fluid challenge, fluid responsiveness, fluid therapy, heart–lung interaction

How to cite this article:
Ghoniem EA, Sultan WE, Naguib HM. Predictors of effective fluid therapy in the intensive care unit. Menoufia Med J 2019;32:389-96

How to cite this URL:
Ghoniem EA, Sultan WE, Naguib HM. Predictors of effective fluid therapy in the intensive care unit. Menoufia Med J [serial online] 2019 [cited 2020 May 27];32:389-96. Available from: http://www.mmj.eg.net/text.asp?2019/32/2/389/260915

  Introduction Top

Early aggressive resuscitation of critically ill patients may limit and/or reverse tissue hypoxia and progression to organ failure and improve outcome. By contrast, excessive fluid resuscitation has been associated with increased complications, increased lengths of ICU and hospital stay, and increased mortality[1].

Fluid responsiveness (FR) is an increase in cardiac output (COP) or stroke volume (SV) greater than 10–15% from the baseline after a fluid challenge. If COP does not increase in response to the fluid challenge, then inotrope and/or vasopressor are required to increase the blood flow[2].

Only 40–72% of critically ill patients are preload responsive (functioning on ascending portion of the Frank–Starling curve). This approach will help avoid fluid overload, which is an independent predictor of mortality in patients with septic shock or acute respiratory distress syndrome (ARDS)[3],[4].

The traditionally measured variables of resuscitation have included blood pressure, pulse rate, central venous pressure (CVP), and arterial oxygen saturation (SaO2). These variables change minimally in early shock and are poor indicators of the adequacy of resuscitation in goal-directed fluid therapy (GDFT) algorithms[5].

Static markers of cardiac preload such a CVP and pulmonary artery occlusion pressure (PAOP) are inaccurate and poor predictors of FR[6],[7].

Dynamic markers of cardiac preload such as: the respiratory variation of arterial pulse pressure (PPV), stroke volume (SVV), photoplethysmography variability index (PVI) derived from pulse oximetry, aortic blood velocity (ΔV peak), and inferior vena cava caliber (IVC caliber) have been shown to be the best and most consistent parameters in patients on controlled mechanical ventilation. However, such indices suffer from several limitations. Alternative methods such as minifluid challenge, passive leg raising (PLR), and end-expiratory occlusion test have been developed for patients with spontaneous breathing with or without mechanical support[8].

The aim of this work was to provide the recent advances in the detection of FR to identify patients who can be eligible for fluid therapy and those who cannot benefit from volume expansion and in whom fluid loading can even be deleterious.

  Materials and Methods Top

We follow the PRISMA statement during the preparation of this review, and the steps previously described by Azkol et al.[9].

Search strategy

We checked on papers on FR from Medline databases (PubMed, Medscape, ScienceDirect), and furthermore from materials accessible on the Web. We utilized (fluid therapy – heart–lung interaction – FR) as seeking things in the title of the papers. The pursuit had performed in the electronic databases from the beginning date of every database to 2016.

Study selection

Each of the reviews had freely surveyed for consideration criteria.

  1. Published in the English language
  2. Published in analog-reviewed journals
  3. Focused on part of predictors of effective fluid therapy in the ICU.

If a review had several distributions on specific angles, we utilized the most recent production giving the most critical information.

Data extraction

Information from each qualified review had freely extracted in a copy utilizing an information accumulation frame to catch data on study attributes, mediations, quantitative outcomes detailed for every result of intrigue. Conclusion, remarks on each review had been made.

As a result of heterogeneity in the gathered information, it was unrealistic to perform a meta-analysis. The information was organized together and rearranged to result in this review.

The analyzed publications were evaluated according to evidence-based medicine criteria using the classification of the US Preventive Services Task Force and UK National Health Service protocol for evidence-based medicine in addition to the Evidence Pyramid [Figure 1],[Figure 2],[Figure 3].
Figure 1: Evidence based medicine pyramid.

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Figure 2: Sturdy flow charts.

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Figure 3: Dynamic indices predicting fluid responsiveness.

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  1. Level I: evidence obtained from at least one properly designed randomized controlled trial
  2. Level II-1: evidence obtained from well-designed controlled trials without randomization
  3. Level II-2: evidence obtained from well-designed cohort or case–control analytic studies, preferably from more than one center or research group
  4. Level II-3: evidence obtained from multiple time series with or without the intervention. Dramatic results in uncontrolled trials might also be regarded as this type of evidence
  5. Level III: opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.

Quality assessment

The quality of all the studies was surveyed. Important factors included study design, attainment of ethical approval, evidence of a power calculation, specified eligibility criteria, appropriate controls, and adequate information and specified assessment measures.

Data synthesis

An organized deliberate audit had performed with the outcomes arranged [Table 1],[Table 2],[Table 3].
Table 1: Dynamic markers of cardiac preload as a predictor of effective fluid therapy

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Table 2: Summary of studies of volume challenge

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Table 3: Dynamic markers of cardiac preload as a predictor of effective fluid therapy

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  Results Top

Study selection and characteristics

In total, 25 potentially relevant publications were identified from Medline databases (PubMed, Medscape, ScienceDirect), 10 articles were excluded as they did not meet our inclusion criteria. The selected studies were 15; these studies were deemed eligible by fulfilling the inclusion criteria. There was a high degree of heterogeneity regarding predicting fluid therapy in the ICU. The information was organized together and rearranged to result in this systematic review.

In 2008, the Bedside Echocardiographic Assessment in Trauma/Critical Care (The BEAT) examination was developed. Both the American Society of Echocardiography (ASE) and the American College of Emergency Physicians (ACEP) define the role of transthoracic echo (TTE) as a time-sensitive assessment tool for the symptomatic patient, primarily for the evaluation of global cardiac function and volume status. During this examination, variation in IVC diameter is used to distinguish patients who will likely respond to fluid resuscitation from those who will not and it may give an estimate of right atrial pressure and substitute for more invasive measurements. BEAT has been shown to be most effective at the extremes of volume status[22] [Table 4].
Table 4: Interpretation of volume status based on inferior vena cava alone (respirophasic inferior vena cava variation)

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According to dynamic markers of cardiac preload as predictors of effective fluid therapy

We selected six systematic review trials performed using the MEDLINE and Embase databases for articles published from 2002 to 2015[10],[11],[12],[13],[14],[15]. Clinical studies investigating the value of the dynamic (such as SVV and PPV) parameters in predicting FR in ICU were included. Patients were heterogeneous, including those after cardiac surgery, with severe sepsis, acute circulatory failure, and acute respiratory failure [Table 1].

Four prospective studies[11],[12],[13],[15] excluded patients with arrhythmia and severe cardiac or pulmonary dysfunctions. However, two prospective studies reported arrhythmias[10],[14].

The tidal volumes (TV) were mainly equal to or more than 8–10 ml/kg[10],[11],[12],[13],[14] with the exception in one study using low TV (<8 ml/kg) in ARDS[15].

Strategies of the fluid challenge were varied across the studies. Hydroxyethyl starch and penta starch were used in two studies[12],[15]; body position maneuvers to increase venous return were used in two studies[10],[11]; 50 ml crystalloid over 10 s was used in one study[14]; and 500 ml crystalloid was used in one study[13].

Devices were different across the studies using Esophageal Doppler, PiCCO (Pulsion Medical System, Munich, Germany), FloTrac/Vigileo (Edwards Lifesciences, Irvine, California, USA), photoplethysmography, and TTE[10],[11],[12],[13],[14],[15].

The definition of FR according to these studies ranging from 10 to 25% increases from the baseline[10],[11],[12],[13],[14],[15].

Two studies included comparison with an established reference standard such as pulmonary artery catheter[13],[15]. Pulmonary artery catheter-derived indices were compared with indices measured by direct arterial trace versus photoplethysmogram and PiCCO. The results of this qualitative systematic review confirm the shortcomings of static measurements (such as PAOP) and affirm the potential for dynamic measurements (such as SVV and PPV) as determinants of FR. Dynamic indices had better correlation and areas under the receiving operating characteristic curve (AUROC) than static measures across studies. Any variable with an AUROC curve that was significantly above 0.5 (i.e., the lower limit of the 95% CI was above 0.5) was considered predictive.

According to static markers of cardiac preload as predictors of effective fluid therapy

A retrospective study of Shippy et al.[23] in 1984 reported the relationship between CVP and measured blood volume (r). Fifteen hundred simultaneous measurements of blood volume and CVP in a heterogeneous cohort of 188 ICU patients demonstrate no association between these two variables (r = 0.27). The correlation between change in CVP (Δ CVP) and change in blood volume was 0.1 (r2 = 0.01). This study demonstrates that patients with a low CVP may have volume overload and, likewise, patients with a high CVP may be volume depleted.

Another three retrospective studies[16],[18],[24] were selected from 19 studies published from 1966 to June 2007 determined the relationship between CVP/ΔCVP and change in cardiac performance following a fluid challenge. The pooled AUROC curve was 0.56 (95% CI: 0.51–0.61). The pooled correlation coefficient between baseline CVP and change in stroke index/cardiac index was 0.18 (95% CI: 0.08–0.28). The pooled correlation between Δ CVP and change in stroke index/cardiac index was 0.11 (95% CI: 0.01–0.21). The baseline CVP was 8.7 ± 2.3 mmHg in the responders, as compared with 9.7 ± 2.2 mmHg in nonresponders. These retrospective studies demonstrated the inability of CVP/ΔCVP to predict the hemodynamic response to a fluid challenge and, so CVP should not be used to make clinical decisions regarding fluid management [Table 2].

According to mortality and ICU length of stay

Four randomized controlled trials are selected from a total of 14 randomized controlled trials published between March 2007 and December 2016 comparing the dynamic assessment of FR with standard care for acute volume resuscitation in adults admitted to the ICU. The primary outcome was mortality at the longest duration of follow-up (28–30 days) in one trial[19], and 90 days in the other[20]. Fluid therapy guided by dynamic assessment was associated with decreased mortality compared with standard care (RR: 0.59; 95% CI: 0.42–0.83; I2 = 0%; n = 1586). The absolute risk reduction in mortality associated with fluid therapy guided by dynamic assessment was 2.9% (95% CI: −5.6 to −0.2%). The secondary outcome was associated with reduced ICU length of stay (−1.16 d; 95% CI: −1.97 to −0.36; I2 = 74%; n = 394) and reduced duration of mechanical ventilation (−2.98 h; 95% CI: −5.08 to −0.89; I2 = 34%; n = 334)[17],[21] [Table 3].

  Discussion Top

The results of studies included in our systematic review demonstrated that dynamic indices of FR are preferable to static methods. Dynamic indicators have been shown to be the best and most consistent predictors of FR. They work as markers of cardiac preload (position on the Frank–Starling curve) and have the ability to identify the volume status without the need to give fluid and to monitor the response which is the most efficient way to prevent both hypovolemia and fluid overload. PPV or SVV of greater than 9–13% was shown to be predictive of FR[11].

GDFT based on dynamic parameters (PPV, SVV, PVI, IVC caliber) is able to decrease complications of excessive fluid administration as well as ICU length of stay and mortality rate. The differential mortality effects may be due to improved end-organ perfusion, optimal timing of fluid bolus administration in relation to physiologic demand, or minimization of crystalloid volume[17],[20].

Dynamic indicators rely on heart–lung interactions, the respiratory-induced variations in left ventricular (LV) stroke volume, induced by positive pressure ventilation which provokes a cyclic decrease in the right ventricular (RV) SV through two mechanisms; decreased preload (decreased venous return) and increased afterload (increased transpulmonary pressure). RV SV reaches its minimum value by the end of inspiration resulting in a consequent decrease in LV filling and thus LV SV after a lag period of 2–3 heart beats[25].

Dynamic indicators have limitations that they must be used in mechanically ventilated patients with no spontaneous breathing attempts; TV needs to be adequate 8–10 ml/kg; positive end-expiratory pressure (PEEP) to not exceed 5 cm H2O; and the patient needs to be in normal sinus rhythm[25].

Limitations of the dynamic parameter may be mitigated by incorporating a PLR into the dynamic assessment. The PLR test is a reversible preload challenge of around 300 ml of blood that can be repeated as frequently as required without infusing fluid. PLR is accurate in spontaneously breathing patients, with cardiac arrhythmia, low TV ventilation, and low lung compliance. The mean threshold was a PLR-induced increase in COP of 10% or more. Pulse contour analysis, ECHO, with measurements of the PLR-induced changes in the velocity time integral of the LV outflow tract and esophageal Doppler, with measurements of the aortic blood flow are techniques reported for COP monitoring[26].

One of the most intuitive way to test FR is to administer a small volume of fluid and observe its effects on COP using PICCO or Bioreactance (CHEETAH NICOM Technology, Cheetah Medical, Inc., Centre St Suite, Newton Center, MA, USA). The minifluid challenge using a 100 ml colloid bolus over 1 min with concomitant COP monitoring induces an increase in COP by 10% which predicts FR equal to that of a 500 ml crystalloid infusion. Ten second fluid challenge uses a 50 ml crystalloid bolus over 10 s with monitoring of CO or SV was recently reported as a method for the detection of FR with a cut-off value of 10% increase in CO or SV after fluid administration. Limitations of small volumes of mini-fluid challenge can only induce small changes in COP; thus, the test requires a very precise cardiac output monitoring system[14].

The variation of IVC diameter measured by TTE has been reported to detect preload responsiveness with reasonable accuracy. In spontaneously breathing patients; if IVC collapsibility index [(maximum diameter–minimum diameter)/maximum diameter × 100] greater than 42%, it suggests FR. In patients with spontaneous breathing. The IVC distensibility index [(maximum diameter–minimum diameter)/minimum diameter × 100] might be valuable in mechanically ventilated patients with a cut-off value of 18%[27]. IVC variability index [(maximum diameter–minimum diameter)/mean diameter × 100] greater than 12% can also suggest FR in mechanically ventilated patients[28].

Factors that may affect IVC diameters include patients with elevated pulmonary artery pressure, pulmonic or tricuspid valve disease, low TV less than 8 ml/kg as in ARDS and condition with increased intra-abdominal pressures and higher PEEP level more than the physiologic PEEP (3–5 cm H2O)[25].

Static hemodynamic parameters including CVP and PAOP were reported to be of a poor value in the prediction of FR in both spontaneously breathing and mechanically ventilated patients. This is because measurements of those pressures are not accurate in the presence of huge variations of intrathoracic pressure[23]. Also, the predictive value of RV end-diastolic volume and LV end-diastolic volume is not reliable because of the ability of the heart to respond to preload does not depend on the value of the ventricular volume, but on how that volume is located in the specific Frank–Starling curve of that heart[7].

Transpulmonary thermodilution is the best technique that provides an easy measurement of the global end-diastolic volume and extravascular lung water (EVLW) that evaluate the volume status rather than the volume responsiveness. Increased EVLW is always potentially life threatening, mainly because it impairs gas exchange and reduces lung compliance. EVLW and tissue edema increase markedly because of the increased cardiac filling pressures and transmitted hydrostatic pressures which trigger the release of natriuretic peptides, affecting the endothelial permeability indirectly. This is followed by a rapid shift of intravascular fluid into the interstitial space leading to a marked increase in EVLW and tissue edema[29].

  Conclusion Top

Decisions regarding fluid therapy in the ICU are among the most challenging and important tasks that clinicians face on a daily basis. Specifically, almost all clinicians would agree that both hypovolemia and volume overload increase the morbidity and mortality of patients. Dynamic FR monitoring methods are preferable to static method. Each dynamic method has its benefits and limitations. IVC collapsibility and distensibility indices are valuable in spontaneously breathing and mechanically ventilated patients, respectively. Knowing whether or not a fluid infusion can improve COP is crucial when treating hemodynamically unstable patients. GDFT based on dynamic parameters is able to decrease complications of excessive fluid administration as well as ICU length of stay and mortality rate.

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Conflicts of interest

There are no conflicts of interest.

  References Top

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  [Figure 1], [Figure 2], [Figure 3]

  [Table 1], [Table 2], [Table 3], [Table 4]


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