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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 7  |  Issue : 1  |  Page : 84-90

Stroke volume variation compared with inferior vena cava distensibility for prediction of fluid responsiveness in mechanically ventilated patients with septic shock


Department of Critical Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt

Date of Submission30-Nov-2018
Date of Acceptance26-Feb-2019
Date of Web Publication16-Apr-2020

Correspondence Address:
MD Waleed S Abd El Hady
Department of Critical Medicine, Faculty of Medicine, University of Alexandria, Alexandria
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/roaic.roaic_102_18

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  Abstract 

Background The hemodynamic management of septic shock patients remains a complex challenge. Only 40–72% of intensive care unit (ICU) patients with homodynamic instability are able to respond to fluid loading. We postulated that the variation in vena cava diameter and its correlation to stroke volume variation could also be useful in identifying patients who may benefit from a volume load. The aim of this study was to test stroke volume variation (SVV) as a predictor of fluid responsiveness in mechanically ventilated patients with septic shock and its correlation with inferior vena cava (IVC) distensibility.
Patients This prospective study was conducted on 76 adult patients with septic shock on mechanical ventilation.
Results The responder and non-responder groups showed areas under the curve 0.963 as regards SVI (2nd) measurements, at the cut off value 36.0 the sensitivity was 97.0, specificity was 95.0, PPV 94.0%, NPV 96.0% and accuracy 95.0 in predicting the response. The SVI (1st) measurements showed areas under the curve 0.963, at the cut off value 8.5 the sensitivity was 95.0, specificity was 98.0, PPV 94.0%, NPV 97.0% and accuracy 96.0 in predicting the response. For Max DIVC within responder and non-responder groups, the areas under the curve 0.884, at the cut off value 2.2 the sensitivity was 82.0, specificity was 85, PPV 86.0%, NPV 83.0% and accuracy 84.0 in predicting the response.
Conclusions Stroke volume variation (SVV) can predict fluid responsiveness in mechanically ventilated patients with septic shock and can be correlated to inferior vena cava (IVC) distensibility.

Keywords: fluid responsiveness, inferior vena cava distensibility, mechanical ventilation, septic shock, stroke volume variation


How to cite this article:
Fayed AM, Abd El Hady WS, El Aleem Abd El hady MA, El Amir Melika M. Stroke volume variation compared with inferior vena cava distensibility for prediction of fluid responsiveness in mechanically ventilated patients with septic shock. Res Opin Anesth Intensive Care 2020;7:84-90

How to cite this URL:
Fayed AM, Abd El Hady WS, El Aleem Abd El hady MA, El Amir Melika M. Stroke volume variation compared with inferior vena cava distensibility for prediction of fluid responsiveness in mechanically ventilated patients with septic shock. Res Opin Anesth Intensive Care [serial online] 2020 [cited 2020 May 31];7:84-90. Available from: http://www.roaic.eg.net/text.asp?2020/7/1/84/282583


  Introduction Top


The hemodynamic management of septic shock patients remains a complex challenge [1]. A consensus conference report of the European Society of Intensive Care Medicine can provide guidance on how to perform hemodynamic monitoring in critically ill patients with circulatory shock [2].

However, only 40–72% of ICU patients with hemodynamic instability are able to respond to fluid loading by a significant increase in stroke volume or cardiac output (CO) [3]. Stroke volume is an important determinant of CO, which is the product of stroke volume and heart rate and is also used to calculate ejection fraction (EF) [4].

The detection of fluid responsiveness is of utmost importance in the management of patients with septic shock, answering the question ‘Can we improve CO and hence hemodynamics by giving fluid?’ Although still widely used to determine fluid therapy, cardiac filling pressures do not reliably predict responsiveness of cardiovascular parameters to fluid challenge [5]. Mechanical ventilation induces cyclic variations in vena cava flow and diameter that are reflected in changes in aortic flow within the time frame of a few heart beats [6]. The respiratory changes in aortic flow have previously been shown to be accurate predictors of fluid responsiveness. Assuming that mechanical insufflations-induced changes in systemic venous return are more marked in hypovolemic than in normovolemic conditions, we postulated that the variation in vena cava diameter could also be useful in identifying patients who may benefit from a volume load [7]. During the past decade, a number of dynamic tests of volume responsiveness have been reported [8].

Transthoracic echocardiography is becoming the tool of choice of hemodynamic assessment in many ICUs. It has been gaining popularity due to its noninvasiveness wherein the benefit far outweighs the risk. Use of respiratory inferior vena cava (IVC) diameter variation or collapsibility index (CI) is very popular because it is very easy to record, and needs a short learning curve, even for noncardiologist residents or physicians [9].


  Aim of the work Top


The aim of this study was to test stroke volume variation (SVV) as a predictor of fluid responsiveness in mechanically ventilated patients with septic shock and its correlation with IVC distensibility.


  Patients and methods Top


This prospective study was carried out on 76 adult patients with septic shock on mechanical ventilation who were admitted to the Critical Care Medicine Department in Alexandria Main University Hospital.

Inclusion criteria

  1. Age more than or equal to 18 years.
  2. Sepsis according to the 2016 definition, an increase in sequential organ failure assessment (SOFA) score of 2 or more, constitutes organ dysfunction. The SOFA score is calculated on the basis of the assessment of the following systems in the ICU setting:
    1. Respiratory (SPO2 <90% on room air).
    2. Neurological (as assessed by the Glasgow coma scale).
    3. Cardiovascular [mean arterial pressure (MAP)>65 mmHg] or administration of vasopressor (e.g. dopamine ≥5 μg/kg/min or norepinephrine).
    4. Coagulation (platelet count<100×109/l and INR >1.5).
    5. Renal (creatinine level >177 μmol/l and urine output <0.5 ml/kg/h for 2 h).
    6. Hepatic (bilirubin level >34 μmol/l).
  3. The quick SOFA criteria are recommended for use outside of the ICU patients with suspected infection who are likely to have poor outcome.
    • According to the new definition, septic shock with two or more of the following q SOFA criteria is likely to have poor outcomes typical of sepsis:
    1. Alteration of mental status.
    2. Systolic blood pressure less than or equal to 100 mmHg.
    3. Respiratory rate more than or equal to 22/min.
  4. Septic shock according to the 2016 definition is defined as sepsis with both of the following (and they are):
    1. Persistent hypotension requiring vasopressors to maintain MAP more than or equal to 65 mmHg.
    2. Serum lactate level more than 2 mmol/l (<18 mg/dl) despite adequate volume resuscitation.


Exclusion criteria

The exclusion criteria constituted the following (and they are):
  1. Cardiogenic shock
  2. Acute pulmonary edema (cardiogenic edema).
  3. LVEF % less than 40%.
  4. Patients with chronic kidney disease with oliguria and volume overload including patients on hemodialysis.
  5. Valvular heart disease: significant aortic or mitral valve lesions.
  6. Nonintubated patients.



  Methods Top


The acceptance of ethical committee of the faculty was obtained at the beginning of this study. All patients included in this study were subjected on admission to the following:
  1. Informed consent from the patients or their next of kin was taken before enrollment to the study.
  2. Complete history taking of patients.
  3. Complete physical examination.
  4. Glasgow coma scale.
  5. Laboratory investigation and arterial blood gases.
  6. Chest radiography daily and echocardiography on admission.
  7. Random blood sugar daily and when needed.
  8. Adequate sedation and muscle relaxation as needed by the patient .
  9. All patients were mechanically ventilated using volume-controlled mode (tidal volume 8–10 ml/kg, respiratory frequency 12–15 breaths/min, positive end expiratory pressure 0–2 cmH2O).
  10. Main arterial pressure was maintained above 65 mmHg by adjusting noradrenaline (norepinephrine) dose before starting measurements.
  11. Hemodynamic measurements were recorded in the supine position.
  12. For volume expansion, we will use 500 bolus fluids that will be administered rapidly over 10 min.
  13. The hemodynamic variables were recorded:
    1. Maximum and minimum DIVC values over a single respiratory cycle were measured, and the DIVC variation (DDIVC) calculated as the difference between the maximum and the minimum DIVC value, normalized by the mean of the two values and expressed as a percentage.
    2. CO was evaluated using echocardiography by measuring the diameter of the aortic orifice and the velocity time integral of aortic blood flow during end-expiration. All measurements were performed by a single experienced operator.



  Results Top


The responder group included 24 (51.1%) male individuals and 23 (48.9%) female individuals, and, in the nonresponder group, there were 15 (51.7%) and 14 (48.3%), respectively. Ages of the responder group ranged from 42 to 66, with a mean value of 53.49±7.84, and those of the nonresponder group ranged from 42 to 65, with a mean age of 53.93±6.27. There was no statistically significant relation between outcome and demographic data.

[Table 1] shows the relation between outcome and SOFA, SPO2, and MAP. It was found that there was statistical significant relation between both groups as regarding the outcome and also there was no statistical significant relation between both groups as regarding the SPO2 and MAP on admission. (P>0.05).
Table 1 Relation between outcome, sequential organ failure assessment, SPO2, and mean arterial pressure

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[Table 2] shows the relation between outcome and heart rate at different periods of follow-up. There was a statistically significant relation between outcome and heart rate at different periods of follow-up (P<0.05).
Table 2 Relation between outcome, heart rate, and respiratory rate at different periods of follow-up

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[Table 3] shows the relation between outcome and respiratory rate at different periods of follow-up. There was a statistically significant relation between outcome and respiratory rate at different periods of follow up (P<0.05). There was a statistically significant relation between outcome and pH 2, PaO2 1, PaO2 2, PaCO2 2, and HCO3 2 (P<0.05), whereas there was no statistically significant difference with regard to pH 1, PaCO2 1, and HCO3 1 (P>0.05).
Table 3 Relation between outcome and blood gases at different periods of follow-up

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[Table 4] shows the relation between outcome and blood gases at different periods of follow-up. There was a statistically significant relation between outcome and SaO2 1, SaO2 2, and CO 2 (P<0.05), whereas there was no statistically significant relation with regard to CO 1, central venous pressure (CVP) 2, and CVP 1 (P>0.05).
Table 4 Relation between outcome and blood gases at different periods of follow-up

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[Table 5] shows the relation between outcome and CI, stroke volume index (SVI), and SVV at different periods of follow-up. There was a statistically significant relation between outcome and SVI 2, SVV 1, and SVV 2 (P<0.05), whereas there was no statistically significant relation with regard to CI 1, CI 2, and SVI 1 (P>0.05).
Table 5 Relation between outcome and collapsibility index, stroke volume index, and stroke volume variation at different periods of follow-up

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[Table 6] shows the relation between outcome and minimum and maximum DIVC at different periods of follow-up. Minimum DIVC of the responder group ranged from 2 to 2.9, with a mean value of 2.45±0.30 and that of the nonresponder group ranged from 2 to 3 with a mean value of 2.55±0.31. Maximum DIVC of the responder group ranged from 2 to 3, with a mean value of 2.56±0.33, and that of the nonresponder group ranged from 1.20 to 2.50, with a mean value of 1.95±0.36. There was a statistically significant relation between outcome and maximum DIVC (P<0.05), whereas there was no statistically significant relation with regard to minimum DIVC (P>0.05).
Table 6 Relation between outcome and minimum and maximum DIVC at different periods of follow-up

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[Table 7] shows the agreement (sensitivity, specificity, and accuracy) for SVI (2nd) with responder and nonresponder groups; the SVI (2nd) measurements show area under the curve (AUC) value of 0.963; at the cut-off value of 36.0, the sensitivity was 97.0, specificity was 95.0, positive predictive value (PPV) 94.0%, negative predictive value (NPV) 96.0%, and accuracy 95.0 in predicting the response. The SVI (1st) measurements show an AUC value of 0.963; at the cut-off value of 8.5, the sensitivity was 95.0, specificity was 98.0, PPV 94.0%, NPV 97.0%, and accuracy 96.0 in predicting the response. While the SVI (2nd) measurements show AUC of 0.915, at the cut-off value of 6.1, the sensitivity was 88.0, specificity was 92.0, PPV 85.0%, NPV 90.0%, and accuracy 93.0 in predicting the response. For maximum DIVC within responder and nonresponder groups, the AUC was 0.884; at the cut-off value of 2.2, the sensitivity was 82.0, specificity was 850, PPV 86.0%, NPV 83.0%, and accuracy 84.0 in predicting the response ([Figure 1],[Figure 2],[Figure 3]).
Table 7 Agreement (sensitivity, specificity, and accuracy) for stroke volume index (2nd) with responder and nonresponder groups

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Figure 1 ROC curve for SVI (2nd). ROC, receiver operating characteristic; SVI, stroke volume index.

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Figure 2 ROC curve for SVV (1st, 2nd). ROC, receiver operating characteristic; SVV, stroke volume variation.

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Figure 3 ROC curve for DIVC. ROC, receiver operating characteristic.

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  Discussion Top


This prospective study was carried out on 76 adult patients with septic shock who were on mechanical ventilation and who were admitted to the Critical Care Medicine Department in Alexandria Main University Hospital.

The patients were classified into two groups, the responder group, which included 47 (61.8%) patients and the nonresponder group which included 29 (38.2%) patients.

As regards the age, there was no significant difference between the responders and nonresponders (53.49±7.84 vs. 53.93±6.27). Moreover, there was no significant difference between responders and nonresponders as regards sex in the two groups. Our results agreed with Muller et al. [10].

SOFA score in the responder group ranged from 5 to 15, with a mean value of 9.04±3.20, and, in the nonresponder group, it ranged from 5 to 10 with a mean value of 7.59±1.70. There was no statistically significant increase in the SOFA score in responder group more than that in the nonresponder group (P<0.05).

These results agreed with the study of Perner and Faber [11] who concluded that the SOFA score showed a significant increase in nonresponder patients.

In our study, the baseline characteristic features of the responder and nonresponder patients matched the results with regard to hemodynamic PO2, MAP, systolic blood pressure, respiratory rate and laboratory data (platelet count, creatinine, and bilirubin). Many studies agreed with our findings [12],[13],[14]; these studies showed the homogeneity of all patients with regard to basic data, whether hemodynamic or laboratory data [15].

In our study, the mean arterial blood pressure all over the period of follow-up showed no significant difference between the responder and nonresponder patients; this agreed with other studies which proved that the fluid-induced changes in CO are not reflected at all by the fluid-induced changes in MAP [16],[17].

In this study, the heart rate showed a significant increase in responder patients than in the nonresponder patients, the significant increase in heart rate in the responder group was noticed from 2 h up to 12 h. These results were in agreement with those of the study carried out by Cherpanath and colleagues [17],[18] who concluded that the presence of increased delivery of oxygen, impaired oxygen extraction and consumption can be predominant, especially during sepsis. Furthermore, CO was not only determined by preload and contractility, but, in particular, by afterload and heart rate as well, making the increase in CO by fluid loading just part of the solution.

In our study, in contrast with the results of heart rate, which increased in responder patients, the respiratory rate was increased in nonresponder patients all over the period of study; these results were in agreement with Teboul and Monnet [19] who concluded that the respiratory variations in stroke volume and its derivatives were affected by respiratory rate, but the caval index was unaffected. This suggested that the right and left indices of ventricular preload variation are dissociated. At high respiratory rates, stroke volume variations have limited ability to predict fluid responsiveness, whereas caval index still valid [17].

The blood picture in our study showed a significant increase in hemoglobin level, white blood cells, and platelets in the responder patients more than in the nonresponder patients, whereas the kidney function showed insignificant difference. The hemodynamic data showed a significant improvement in pH, PaO2, PaCO2, and HCO3 in second measurements. The SaO2 showed a significant increase in responder patients more than in nonresponder patients in the two periods of follow-up. Moreover, Preau S [20] found that the hemodynamic data were improved in responder patients more than in nonresponder patients.

In our study, measurements of SVI (2nd measurements) ranged from 34.5 to 43.2, with a mean 38.84±2.45% in the responder group, whereas, in nonresponders, it ranged from 31.2 to 36.9, with a mean 34.08±1.43. SVV (1st measured) ranged from 10.3–15.4, with a mean 12.73±1.44% in responders, whereas in nonresponders it ranged from 4.0 to 10.4, with a mean 7.24±2.09. At the second measurement, the SVV ranged from 5.20 to 13.3 with a mean 9.25±2.20 in responders whereas, in nonresponders, it ranged from 0.9 to 9.1, with a mean 4.86±2.29. These results showed that SVI and SVV were significantly higher in responders than in nonresponders (P<0.001). The SVI (2nd) measurements showed AUC of 0.963; at the cut-off value of 36.0, the sensitivity was 97.0, specificity was 95.0, PPV 94.0%, NPV 96.0%, and accuracy 95.0 in predicting the response. SVV (1st, 2nd) within responder and non-responder groups: SVI (1st) measurements showed areas under the curve 0.963, at the cut off value 8.5, the sensitivity was 95.0, specificity was 98.0, PPV 94.0%, NPV 97.0% and accuracy 96.0 in predicting the response, while SVI (2nd) measurements showed areas under the curve 0.915, at the cut off value 6.1, the sensitivity was 88.0, specificity was 92.0, PPV 85.0%, NPV 90.0% and accuracy 93.0 in predicting the response. Although the SVI (2nd) measurements showed AUC of 0.915, at the cut-off value of 6.1, the sensitivity was 88.0, specificity was 92.0, PPV 85.0%, NPV 90.0%, and accuracy 93.0 in predicting the response.

In agreement with our results Muller et al. [21], who assessed the usefulness of SVI recorded by transthoracic echocardiography to predict fluid responsiveness in spontaneously breathing critically ill patients; they examined 40 patients with severe sepsis, bleeding, and dehydration. SVI after 500 ml fluid resuscitation showed best cut-off value of 40% with AUC 0.77 (P=0.08) with sensitivity, specificity, PPV, and NPV of 70, 80, 72, and 83%, respectively. In comparison to our results which showed a best cut-off value of 37% with AUC 0.908 (P<0.001) with sensitivity, specificity, PPV, NPV were 90, 70, 75, and 87.5%, respectively, although we did not include patients with bleeding or dehydration as Muller et al. [21] did, as they may be yet hemodynamically stable and not in need of fluid resuscitation as patients with severe sepsis or septic shock in whom fluid resuscitation is main stay treatment, and this could explain our higher AUC value [21].

In our study, it was found that there was signficiant difference between the responder and non-responder patients regarding maximum DIVC, the area under the curve 0.884, at the cut off value 2.2 the sensitivity was 82.0, specificity was 85, PPV 86.0%, NPV 83.0% and accuracy 84.0.

IVC diameters variations have been studied in mechanically ventilated patients without any spontaneous breathing effort. IVC distensibility (DIVC) has been measured as maximum diameter during inspiration − minimum diameter during expiration/minimum diameter during expiration. Mahjoub et al. [22] showed a sensitivity and specificity of 90% using a cut-off distensibility index of 18% to indicate fluid responsiveness. The efficacy of the respiratory variation in DIVC in mechanically ventilated patients with severe sepsis and septic shock have been studied by Nazmy et al. [23] who conducted a study on 70 patients with severe sepsis and septic shock admitted to Critical Care Department in Alexandria Main University Hospital, Egypt. Both hemodynamic and echocardiographic parameters were measured before and throughout the fluid resuscitation to determine fluid responsiveness. The dIVC was able to discriminate between responders and nonresponders with a cut-off value of 23.5% (100% sensitivity and specificity) before fluid resuscitation and 18% (80% sensitivity and 75% specificity) after fluid resuscitation; hence, he concluded that ΔDIVC can be applied as a dynamic predictor of fluid responsiveness not only at first fluid challenge but also before every volume increment throughout the time of volume expansion [23]. In our study, the percent of change of CVP in response to fluids (after 100cc and 500cc) failed to differentiate between responders and non-responders; therefore ∆CVP can’t be used to predict fluid responsiveness. This also agreed with data obtained from Marik and Cavallazzi [24].

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med 2013; 41:580–637.  Back to cited text no. 1
    
2.
Cecconi M, De Backer D, Antonelli M, Beale R, Bakker J, Hofer C et al. Consensus on circulatory shock and hemodynamic monitoring. Task force of the European Society of Intensive Care Medicine. Intensive Care Med 2014; 40:1795–1815.  Back to cited text no. 2
    
3.
Cannesson M, Musard H, Desebbe O. The ability of stroke volume variations obtained with Vigileo/FloTrac system to monitor fluid responsiveness in mechanically ventilated patients. Anesth Analg 2009; 108:513–517.  Back to cited text no. 3
    
4.
Alicia M. Reference right ventricular systolic and diastolic function normalized to age, gender and body surface area from steady − state free precession cardiovascular magnetic resonance. Eur Heart J 2015; 16:15–33.  Back to cited text no. 4
    
5.
Michard F, Teboul JL. Predicting fluid responsiveness in ICU patients. A critical analysis of the evidence. Chest 2002; 121:2000–2008.  Back to cited text no. 5
    
6.
Morgan BC, Martin WE, Hornbein TF, Crawford EW, Guntheroth WG. Hemodynamic effects of intermittent positive pressure respiration. Anesthesiology 1966; 27:584–590.  Back to cited text no. 6
    
7.
Reuter DA, Felbinger TW, Schmidt C, Kilger E, Goedje O, Lamm P, Goetz AE. Stroke volume variations for assessment of cardiac responsiveness to volume loading in mechanically ventilated patients after cardiac surgery. Intensive Care Med 2002; 28:392–398.  Back to cited text no. 7
    
8.
Marik PE, Monnet X, Teboul JL. Hemodynamic parameters to guide fluid therapy. Ann Intensive Care 2011; 1:1.  Back to cited text no. 8
    
9.
Brennan JM, Ronan A, Goonewardena S, Blair JE, Hammes M, Shah D et al. Handcarried ultrasound measurement of the inferior vena cava for assessment of intravascular volume status in the outpatient hemodialysis clinic. Clin J Am Soc Nephrol 2006; 1:749–753.  Back to cited text no. 9
    
10.
Muller L, Bobbia X, Toumi M, Louart G, Molinari N, Ragonnet B 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.  Back to cited text no. 10
    
11.
Perner A, Faber T. Stroke volume variation does not predict fluid responsiveness in patients with septic shock on pressure support ventilation. Acta Anaesthesiol Scand 2006; 50:1068–1073.  Back to cited text no. 11
    
12.
Tokuda Y, Song MH, Mabuchi N, Usui A, Ueda Y. Right ventricular end-diastolic volume in the postoperative care of cardiac surgery patients a marker of the hemodynamic response to a fluid challenge. Circ J 2007; 71:1408–1411.  Back to cited text no. 12
    
13.
Jellinek H, Krafft P, Fitzgerald RD et al. Right atrial pressure predicts hemodynamic response to apneic positive airway pressure. Crit Care Med 2000; 28:672–688.  Back to cited text no. 13
    
14.
Bennett-Guerrero E, Kahn RA, Moskowitz DM, Falcucci O, Bodian CA. Comparison of arterial systolic pressure variation with other clinical parameters to predict the response to fluid challenges during cardiac surgery. Mt Sinai J Med 2002; 69:96–100.  Back to cited text no. 14
    
15.
Heenen S, De Backer D, Vincent JL. How can the response to volume expansion in patients with spontaneous respiratory movements be predicted. Crit Care 2006; 10:R102.  Back to cited text no. 15
    
16.
Monnet X, Letierce A, Hamzaoui O, Chemla D, Anguel N, Osman D et al. Arterial pressure allows monitoring the changes in cardiac output induced by volume expansion but not by norepinephrine. Crit Care Med 2011; 39:1394–1399.  Back to cited text no. 16
    
17.
Pierrakos C, Velissaris D, Heenen S, Heenen S, De Backer D, Vincent JL. Can changes in arterial pressure be used to detect changes in cardiac index during fluid challenge in patients with septic shock? Intensive Care Med 2012; 38:422–428.  Back to cited text no. 17
    
18.
Cherpanath T, Geerts B, Lagrand W, Groenoveld A. Basic concepts of fluid responsiveness. Neth Heart J 2013; 21:530–536.  Back to cited text no. 18
    
19.
Teboul JL, Monnet X. Prediction of volume responsiveness in critically ill patients with spontaneous breathing activity. Curr Opin Crit Care 2008; 14:334–339.  Back to cited text no. 19
    
20.
Preau S, Dewavrin F, Demaeght V, Chiche A, Voisin B, Minacori F et al. The use of static and dynamic haemodynamic parameters before volume expansion: a prospective observational study in six French intensive care units. Anaesth Crit Care Pain Med 2015; 35:93–102.  Back to cited text no. 20
    
21.
Muller L, Toumi M, Bousquet PJ et al. An increase in aortic blood flow after an infusion of 100 ml colloid over 1 min can predict fluid responsiveness: the mini-fluid challenge study. Anesthesiology 2011; 115:541–547.  Back to cited text no. 21
    
22.
Mahjoub Y, Pila C, Friggeri A, Zogheib E, Lobjoie E, Tinturier F et al. Assessing fluid responsiveness in critically ill patients: false-positive pulse pressure variation is detected by Doppler echocardiographic evaluation of the right ventricle. Crit Care Med 2009; 37:2570–2575.  Back to cited text no. 22
    
23.
Nazmy AMARA, Al Badawy TH, El Morsy AA. Cardiovascular fluid responsiveness in mechanically ventilated patients with severe sepsis and septic shock. Alexandria University; 2013.  Back to cited text no. 23
    
24.
Marik PE, Cavallazzi R. Does the central venous pressure predict fluid responsiveness? An updated meta-analysis and a plea for some common sense. Crit Care Med 2013; 41:1774–1781.  Back to cited text no. 24
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]



 

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