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Critical Care Medicine  |   September 2011
An Increase in Aortic Blood Flow after an Infusion of 100 ml Colloid over 1 Minute Can Predict Fluid Responsiveness: The Mini-fluid Challenge Study
Author Affiliations & Notes
  • Laurent Muller, M.D., M.Sc.
    *
  • Medhi Toumi, M.D.
    *
  • Philippe-Jean Bousquet, M.D.
  • Béatrice Riu-Poulenc, M.D.
  • Guillaume Louart, M.D.
    *
  • Damien Candela, M.D.
    *
  • Lana Zoric, M.D.
    *
  • Carey Suehs, Ph.D.
  • Jean-Emmanuel de La Coussaye, M.D., Ph.D.
    §
  • Nicolas Molinari, Ph.D.
  • Jean-Yves Lefrant, M.D., Ph.D.
    §
  • *Staff Anesthesiologist and Intensivist, Division Anesthésie Réanimation Urgences Douleur, Groupe Hospitalo-Universitaire Caremeau, CHU Nîmes, Place du Professeur Robert Debré, Nîmes, France; Faculté de Médecine, Université Montpellier 1 Equipe d'Accueil 2992, Laboratoire de Physiologie Cardiovasculaire et d'Anesthésie Expérimentale, Faculté de Médecine, Place du Professeur Robert Debré, Nîmes. Biostatistician, Département Biostatistiques Epidémiologie Clinique Santé Publique Information Médicale, CHU Nîmes, Place du Professeur Robert Debré; Faculté de Médecine, Université Montpellier 1. Staff Intensivist, Service Anesthésie Réanimation, Hôpital Purpan, Place du Docteur Baylac, Toulouse, France. §Professor of Anesthesiology and Critical Care Medicine, Division Anesthésie Réanimation Urgences Douleur, Groupe Hospitalo-Universitaire Caremeau, CHU Nîmes, Place du Professeur Robert Debré; Faculté de Médecine, Université Montpellier 1 Equipe d'Accueil 2992, Laboratoire de Physiologie Cardiovasculaire et d'Anesthésie Expérimentale, Faculté de Médecine, Place du Professeur Robert Debré.
Article Information
Critical Care Medicine / Cardiovascular Anesthesia / Critical Care / Renal and Urinary Systems / Electrolyte Balance / Respiratory System
Critical Care Medicine   |   September 2011
An Increase in Aortic Blood Flow after an Infusion of 100 ml Colloid over 1 Minute Can Predict Fluid Responsiveness: The Mini-fluid Challenge Study
Anesthesiology 9 2011, Vol.115, 541-547. doi:10.1097/ALN.0b013e318229a500
Anesthesiology 9 2011, Vol.115, 541-547. doi:10.1097/ALN.0b013e318229a500
What We Already Know about This Topic
  • Predicting fluid responsiveness in a noninvasive fashion remains a difficult clinical problem in hemodynamically unstable and mechanically ventilated patients

What This Article Tells Us That Is New
  • In patients with low-volume mechanical ventilation and acute circulatory failure, transthoracic echocardiography of the subaortic velocity time index variation after a low volume of hydroxyethyl starch is infused accurately predicts fluid responsiveness

IN intensive care units (ICUs), decisions regarding volume expansion are challenging but frequently required. Treatment of hypovolemia requires rapid fluid infusion, but excessive fluid loading can induce peripheral and pulmonary edema and compromise microvascular perfusion and oxygen delivery.1,2 In the last decade, dynamic variables such as stroke volume variation, pulsed pressure variation (PPV), respiratory variation of aortic blood flow (monitored with esophageal Doppler), and aortic peak velocity (assessed by echocardiography) have been shown to be more accurate in predicting fluid responsiveness than classically used static variables (central venous pressure [CVP]) and pulmonary artery occlusion pressure in mechanically ventilated patients.3  12 However, dynamic indicators cannot be used in spontaneously breathing patients and those with cardiac arrhythmia. In addition, because the variation of aortic blood flow is generated by the pressure transmitted from the airways to the pleural and pericardial spaces, these dynamic variables have been shown to be less predictive of fluid responsiveness when a tidal volume less than 8 ml · kg−1is applied and/or in patients with low pulmonary compliance.13 Because of these limitations, a new concept centering on a “noninvasive fluid challenge” has been developed recently.14 The passive leg-raising test was shown to mimic a volume expansion of approximately 300 ml via  the recruitment of the blood fraction contained in the venous reservoir.14,15 This maneuver converts unstressed volume to stressed volume and accurately predicts fluid responsiveness.15,16 In some situations, such as complex leg and/or pelvic trauma, passive leg-raising tests cannot be performed. Therefore, it can be useful to develop a third type of test that does not require leg raising to test fluid responsiveness and avoid the deleterious effects of an unnecessary fluid challenge.
In the current study, we tested the hypothesis that a low volume (100 ml) of rapidly delivered fluid can predict fluid responsiveness. By using a low volume for this “mini-fluid” challenge, the deleterious effects of fluid among nonresponders would be limited hypothetically. According to the Frank-Starling cardiac function curve, the concept of fluid responsiveness is defined as a significant increase in stroke volume secondary to an increase in cardiac preload. Moreover, because of the form of the curve, the increase in stroke volume theoretically would be greater in the steep portion of the Frank-Starling curve at the beginning (in particular, the first 100 ml) of the fluid challenge. In addition, the stroke volume theoretically would be greater at the beginning of the fluid challenge, especially when the rate of fluid administration is increased. A positive response to volume expansion usually is defined as a 15% increase in cardiac output or cardiac index after a fluid challenge over 10–30 min.17 Transthoracic echocardiography provides a rapid, simple, and noninvasive assessment of stroke volume via  the measurement of the subaortic velocity time index (VTI). Therefore, the primary hypothesis of the current study was that the increase of VTI after the infusion of the first 100 ml (ΔVTI100) of colloid over 1 min could predict fluid responsiveness after a total fluid challenge of 500 ml over 15 min (ΔVTI500).
Materials and Methods
The current study was approved by the Institutional Review Board of the Nîmes University Hospital (Nîmes, France). The patient's closest family member was informed of the study.
Sedated (Ramsay score = 4–6)18,19 and mechanically ventilated ICU patients without spontaneous breathing and with acute circulatory failure were eligible to participate in this study. Acute circulatory failure was defined as systolic arterial blood pressure less than 90 mmHg or the need for vasopressors (norepinephrine more than 0.1 μg · kg−1· min−1) to maintain a systolic blood pressure more than 90 mmHg.4 The association of a clinical infection, the presence of systemic inflammatory response syndrome, and acute circulatory failure defined septic shock.20 
Inclusion and Exclusion Criteria
Mechanically ventilated and sedated ICU patients with acute circulatory failure in whom a fluid challenge was indicated because of signs of hypoperfusion (oliguria less than 0.5 ml · kg−1· h−1, cardiac index inadequate for tissue needs, attempt to decrease vasopressor infusion rate) were eligible for the current study.
Patients with cardiac arrhythmias, with known tricuspid insufficiency, or cardiogenic pulmonary edema were excluded. Moribund or parturient patients and those younger than 18 yr were not included. Patients in whom the echocardiography could not be performed also were excluded.
Fluid Challenge Procedure and Fluid Challenge Responsiveness
The fluid challenge was given intravenously via  a specific venous line. The first 100 ml was regularly infused over 1 min. After echographic assessment at 1 min, the remaining 400 ml was infused at a constant rate over 14 min. The fluid challenge was performed with a 6% hydroxyethyl starch solution 130/0.4 (Voluven®; Fresenius-Kabi, Louviers, France). Fluid responsiveness was defined as an increase in the subaortic VTI ≥15% (ΔVTI500≥ 15%) after the infusion of 500 ml hydroxyethyl starch solution, separating the studied population into responders and nonresponders, as described previously.4 
Measured Variables and Time of Measurement
Patient characteristics, including age, sex, height, weight, and Acute Physiology and Chronic Health Evaluation (APACHE) II score,21 were recorded at admission. The ideal body weight (kg) was defined as follows: X + 0.91(height (cm) − 152.4); (X = 50 for male and 45.5 for female). The cause of acute circulatory failure, the inotropic and/or vasopressive support (epinephrine, norepinephrine, dobutamine, and dopamine, expressed as μg · kg−1· min−1), and the number of organ dysfunctions using the Organ Dysfunction and/or Infection (ODIN) score22 were recorded. The following mechanical ventilation variables were recorded: tidal volume (ml · kg−1of ideal body weight), respiratory rate (cycles/min), inspiratory oxygen fraction (FiO2), the level of positive end-expiratory pressure, and plateau pressure (cm H2O). The following hemodynamic variables were recorded: heart rate (beats/min) and mean arterial blood pressure (mmHg). These variables were collected at baseline (T0), after 1 min (i.e.  , infusion of the first 100 ml = T1), and after the end of the fluid challenge (T15).
Echocardiographic assessment was performed by an experienced physician (level 2 or 323), using a General Electric Vivid3 machine (GE Healthcare, Chalfont St. Giles, Buckinghamshire, United Kingdom). The VTI was recorded classically by pulse waved Doppler on a 5-chamber apical view.24 The pictures were stored anonymously to allow the calculation of the VTI and stroke index by another blinded physician experienced in echocardiography (level 3). For each step of the study, VTI was measured in triplicate and averaged for the determination of the VTI value.
When available, CVP (mmHg) and PPV (%) were recorded. The CVP and mean arterial blood pressure were measured invasively with a zero referenced to the middle axillary line. The CVP was measured at end expiration. The PPV value was calculated as initially reported by Michard et al.  ,4 using the recording of invasive arterial pressure on the monitor screen (Intellivue MP 160; Philips, Eindhoven, The Netherlands). Maximal (PPmax) and minimal pulse pressures (PPmin) were calculated as described by Michard et al  .4 The pulse pressure variation (PPV, %) was calculated as follows: PPV = 100 × 2[(PPmax − PPmin)/(PPmax+ PPmin)]. PPV was evaluated in triplicate over each of three consecutive respiratory cycles.
Statistical Analysis
Data are expressed as medians with fifth and ninety-fifth percentiles. For the comparison between responders and nonresponders, Mann–Whitney, Student t  , and Fisher exact tests were performed where appropriate. Receiver operator characteristic (ROC) curves were constructed to evaluate the ability of VTI to predict fluid responsiveness. When the area under the ROC curve (AUC) was greater than 0.5, the best cutoff value was defined by the closest value to the Youden index25 and higher than the reproducibility of echocardiography. We also tested for a correlation between ΔVTI100and ΔVTI500. When available, ROC curves of CVP and PPV were constructed and compared with the ROC curve of the VTI for the same patients using the Hanley test.26 
In previous studies assessing the ability of PPV to predict fluid responsiveness in mechanically ventilated ICU patients with tidal volumes less than 8 ml · kg−1, De Backer et al  .27, Vallée et al.  ,28 and Muller et al  .29 reported AUC of 0.71 ± 0.09, 0.63 [0.45–0.81] and 0.77 [0.65–0.90], respectively. We assumed that ΔVTI100would be clinically relevant if the 95% CI of its AUC was more than 0.75, corresponding to an AUC of a good clinical tool, as reported by Ray et al  .25 For this purpose, 39 patients had to be included. Statistical analysis was performed using SAS version 8.1 software (SAS Institute, Cary, NC). All P  values were two-tailed and a P  value <0.05 was considered significant.
Results
During the study period (February–December 2009), 607 patients were admitted to our ICU. Among 211 patients with acute circulatory failure, 169 (80%) were not included because of: cardiac arrhythmia (n = 51) (24%), a decision to withdraw care (n = 30) (14%), or a lack of echocardiographies and thus no assessment of the fluid challenge (n = 19) (9%). In addition, in some patients the fluid challenge was not performed because it was assessed as unnecessary (n = 47) (22%) or hazardous (n = 22) (10%). Thus, 42 patients were eligible for the current study; in 3 patients, echocardiographic exploration could not be performed because of bad echogenicity. Therefore, 39 (18%) patients were included (table 1). The intra- and interobserver variabilities were 4% and 5%, respectively. The causes of circulatory failure were severe sepsis or septic shock (n = 32) (82%), traumatic shock (n = 4) (10%), and systemic inflammatory response syndrome (n = 3) (8%). Among included patients, 30 (77%) were given norepinephrine. After fluid challenge, VTI increased ≥ 15% in 21 patients (54%), who were defined as responders. There were no significant differences in patient characteristics, tidal volume, or severity score between the two groups, except for the plateau pressure, which was higher in the responders (table 1). At baseline, VTI was significantly lower in responders (14 [12–16] cm) than in nonresponders (20 [12–16] cm) (P  = 0.02). Heart rate did not change between T0and T15for either group.
Table 1. Characteristics of the General Population and Comparison between Responders and Nonresponders
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Table 1. Characteristics of the General Population and Comparison between Responders and Nonresponders
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The AUC under the ROC curve of ΔVTI100was 0.92 (95% CI: 0.78–0.98) (fig. 1). Individual values of ΔVTI100according to the fluid responsiveness are shown in figure 2. The best cutoff value of ΔVTI100was 3%, which was lower than the reproducibility of echocardiography (sensitivity = 95%[76–99%], specificity = 78%[52–94%]). Taking into account reproducibility, the best cutoff value was 10% (sensitivity = 95%[87–99], specificity = 78%[59–97], positive predictive value = 0.83 [0.68–0.98], negative predictive value = 0.93 [0.81–0.99], positive likehood ratio = 4.32, and negative likehood ratio = 0.064). A correlation (r = 0.81 [0.66–0.90], P  < 0.0001) between ΔVTI100and ΔVTI500(fig. 3) was found. The AUC for baseline VTI, when predicting fluid responsiveness, was 0.77 [95% CI: 0.61–0.89]. The increase in VTI was always greater in responders than in nonresponders between baseline and T1(3 [3–4]vs.  0 [−0.75 to +0.5] cm, P  < 0.01), between baseline and T15(5 [4–7]vs.  1 [0–1] cm, P  < 0.001), and between T1and T15(2 [1–3]vs.  0 [−1 to +2] cm, P  < 0.04).
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
×
Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
×
Fig. 3. Correlation (A  ) and Bland and Altman diagram (B  ) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
Fig. 3. Correlation (A 
	) and Bland and Altman diagram (B 
	) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
Fig. 3. Correlation (A  ) and Bland and Altman diagram (B  ) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
×
In 29 patients, PPV and CVP were available. The AUCs for ΔVTI100, PPV, and CVP were 0.90 [95% CI: 0.74–0.98], 0.55 [95% CI: 0.35–0.73], and 0.61 [95% CI: 0.41 to 0.79], respectively (fig. 4). There was a significant difference between the AUCs for ΔVTI100and PPV (P  = 0.01) and between the AUCs for ΔVTI100and CVP (P  = 0.07). There was no significant difference between the AUCs for PPV and CVP (P  = 0.65).
Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
×
The individual VTI data at baseline, T1, and T15are shown in figure 5. Figure 5A shows individual VTI data at baseline T1and T15for responders and figure 5B for nonresponders.
Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A  ) and nonresponders (B  ).
Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A 
	) and nonresponders (B 
	).
Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A  ) and nonresponders (B  ).
×
Discussion
In the current study, a 10% increase in VTI after a rapid infusion of 100 ml (ΔVTI100) of hydroxyethyl starch accurately predicted a 15% increase in VTI after a 500-ml infusion. The ability of ΔVTI100to predict fluid responsiveness was greater than that of PPV or CVP. Moreover, the relatively high (r = 0.81) correlation coefficient between ΔVTI100and ΔVTI500suggests that the greater the increase in ΔVTI100, the more we can expect a similar increase in (ΔVTI500). It follows that greater and greater fluid volumes can be given, indicating that further fluid challenges can be attempted in patients with large ΔVTI100. This maneuver can be considered as an alternative way to trace Frank-Starling curves, based on a three-point method: baseline VTI, VTI 100 ml, and VTI 500 ml.
Echocardiography is considered a major hemodynamic diagnostic tool for intensivists treating circulatory failure.30 Transthoracic echocardiography provides an accurate and noninvasive measurement of cardiac output with an excellent correlation with thermodilution measurements.24 Cardiac output is the product of stroke volume and heart rate. The stroke volume is calculated by the product of the subaortic VTI recorded with pulse Doppler in the left ventricle outflow chamber on an apical 5-chamber view and the subaortic left ventricular area (following the formula : subaortic left ventricular area = πD2/4, where D is the measured ventricle outflow diameter).24 Assuming that the diameter of the left ventricle outflow chamber is constant in a given patient and that variations of heart rate are low, the variations in cardiac output are related to VTI variations. Thus, the measurement of VTI and its variations are directly correlated with variations in cardiac output, avoiding the potential error in the measurement of the left ventricle outflow diameter chamber. This approach has been used in several studies.31  33 The ability of baseline VTI to predict fluid responsiveness could be questioned. Despite a significant lower value of VTI in the responder group, the AUC of ROC curve for baseline VTI was only 0.77, so baseline VTI remains less pertinent than ΔVTI100.
Historically, volume status was assessed by measuring individual values of preload, such as cardiac filling pressure or volume (static parameters). However, during the last decade numerous studies have demonstrated that an isolated value of preload cannot predict fluid responsiveness.5,34  36 In fact, the relationship between ventricular preload and cardiac output (represented by the Frank-Starling curve) varies according to cardiac function. An intermediate value of preload can correspond to a positive response to fluid infusion in a patient with normal ventricle function and a negative response in a subject with impaired ventricle function. In other words, in a normal subject, the Frank Starling curve has a predominant steep portion, suggesting a frequent positive response to fluid. In contrast, for abnormal ventricle function, the shape of the Frank Starling curve is predominantly flat, suggesting a low probability of positive response to fluid loading. It follows that determining the shape of the Frank Starling curve could be of particular interest. The current study reports a low AUC for CVP, thus confirming its inadequacy for predicting fluid responsiveness.4,5 The dynamic variable approach was promising because, under mechanical ventilation, large respiratory variations (more than 10%) of pulse pressure or stroke volume correspond to the steep portion of the Frank-Starling curve, regardless of ventricle function. Therefore, the dynamic indices were thought to predict accurately the fluid responsiveness in mechanically ventilated ICU patients, regardless of their Frank Starling curve. The drastic condition of dynamic variable measurement (controlled mechanical ventilation with no inspiratory efforts, sinus cardiac rhythm) and the widespread use of low tidal volume (less than 8 ml · kg−1of ideal body weight) to avoid lung barotraumas recently challenged the clinical usefulness of dynamic indices.27,29 In the current study, the mean tidal volume was 6.6 ml · kg−1of ideal body weight, leading to an AUC of PPV of 0.55 in 29 patients in whom PPV was assessed. This finding is lower than that reported in our previous study, in which more patients were responders because more patients with hemorrhagic shock were included.29 
A more recent method for evaluating the steep portion of the Frank Starling curve was to study the real-time increase of cardiac output or stroke volume (recorded by transthoracic echocardiography or esophageal Doppler) after passive leg raising that mimics a 300-ml fluid infusion.15 A 15% increase in aortic or subaortic VTI after passive leg raising was shown to accurately predict fluid responsiveness.15,16,31,33 However, the use of this simple and clever maneuver may be inappropriate in trauma patients or in patients after major surgery.
Because the previous indices have limitations, we postulated that a significant increase in VTI after a very low volume of rapid fluid infusion corresponds to the steep portion of the Franck Starling curve, regardless of cardiac function. The current findings confirm that a rapid infusion of 100 ml fluid induces a significant increase in subaortic VTI, which subsequently predicts a 15% increase in cardiac output after a 500-ml volume infusion. The use of a low fluid volume is expected to limit the deleterious effect of an unnecessary fluid infusion in nonresponders. Although a 3% increase in VTI (ΔVTI100= 3%) was the best cutoff value, this threshold is inferior to the interobserver variability for the measure of VTI, which is usually reported at approximately 3–8%.24,37 A cutoff value of 10% has a sensitivity and a specificity of 95% and 78%, respectively. The use of a 10% cutoff value for ΔVTI100could be more clinically relevant when limiting the influence of interobserver variability in the measurement of subaortic VTI.
Hydroxyethyl starch infusion was chosen to guarantee a sustained plasma volume expansion equal to the volume infused. Experimental and clinical studies have shown that crystalloid infusion induces capillary leaks that limit the increase in cardiac output.38  40 Moreover, plasma expansion is less sustained with a crystalloid than with a colloid.39 The choice of a 500-ml fluid infusion for the fluid challenge also can be discussed. As showed in figure 5, some responders did not have increased VTI between T1and T15. This means that some patients may benefit from 500 ml, but other patients may need smaller volumes. An alternative approach would be repeated administration of 100-ml boluses for as long as there is a significant increase in VTI after each bolus, and then stopping when ΔVTI100no longer increases.41 This hypothesis was not tested in the current study, and additional studies are required to address this point. Our choice of a 100-ml bolus was arbitrary. Because the response to passive leg raising was very rapid, a lower volume could be more accurate and more precisely analyze the dose/response during a fluid challenge.
This study has some limitations, and the current findings can not be extrapolated to patients with cardiac arrhythmias. Cardiac arrhythmias can cause high VTI variability in this setting. One hypothetical way to overcome this problem would be to average ΔVTI100for several cardiac cycles when working with cardiac arrhythmia. This hypothesis should also be tested in future studies. Because all of the patients included in this study were mechanically ventilated, our results should be confirmed in patients with spontaneous ventilation. Another limitation is that few patients had severe ventricular dysfunction. Theoretically, in a patient with significant hypovolemia, the relation between preload and cardiac output remains steep, regardless of the systolic function. In other words, VTI variation probably helps identify the steep portion of Frank Starling curve independent of cardiac function. This deserves to be verified by future studies. Finally, the study design and analytical plan of the current study could be better and allow regression toward the mean to enter into the interpretation: the differences observed in the baseline status on VTI are consistent with what would be expected if these results were at least partially driven by regression to the mean. The use of a control group would be an excellent design to rule out the effect of regression to the mean and to confirm our findings.
In summary, a 10% increase in subaortic VTI after administrations of 100 ml hydroxyethyl starch over 1 min accurately predicted fluid responsiveness in patients with acute circulatory failure and mechanical ventilation with low tidal volume.
References
Wang P, Zhou M, Rana MW, Ba ZF, Chaudry IH: Differential alterations in microvascular perfusion in various organs during early and late sepsis. Am J Physiol 1992; 263:G38–43
Ferguson ND, Meade MO, Hallett DC, Stewart TE: High values of the pulmonary artery wedge pressure in patients with acute lung injury and acute respiratory distress syndrome. Intensive Care Med 2002; 28:1073–7
Tavernier B, Makhotine O, Lebuffe G, Dupont J, Scherpereel P: Systolic pressure variation as a guide to fluid therapy in patients with sepsis-induced hypotension. ANESTHESIOLOGY 1998; 89:1313–21
Michard F, Boussat S, Chemla D, Anguel N, Mercat A, Lecarpentier Y, Richard C, Pinsky MR, Teboul JL: Relation between respiratory changes in arterial pulse pressure and fluid responsiveness in septic patients with acute circulatory failure. Am J Respir Crit Care Med 2000; 162:134–8
Michard F, Teboul JL: Predicting fluid responsiveness in ICU patients: A critical analysis of the evidence. Chest 2002; 121:2000–8
Coriat P, Vrillon M, Perel A, Baron JF, Le Bret F, Saada M, Viars P: A comparison of systolic blood pressure variations and echocardiographic estimates of end-diastolic left ventricular size in patients after aortic surgery. Anesth Analg 1994; 78:46–53
Kramer A, Zygun D, Hawes H, Easton P, Ferland A: Pulse pressure variation predicts fluid responsiveness following coronary artery bypass surgery. Chest 2004; 126:1563–8
Vieillard-Baron A, Chergui K, Rabiller A, Peyrouset O, Page B, Beauchet A, Jardin F: Superior vena caval collapsibility as a gauge of volume status in ventilated septic patients. Intensive Care Med 2004; 30:1734–9
Hofer CK, Müller 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; 128:848–54
Auler JO Jr, Galas F, Hajjar L, Santos L, Carvalho T, Michard F: Online monitoring of pulse pressure variation to guide fluid therapy after cardiac surgery. Anesth Analg 2008; 106:1201–6
Cannesson M, Slieker J, Desebbe O, Bauer C, Chiari P, Hénaine R, Lehot JJ: The ability of a novel algorithm for automatic estimation of the respiratory variations in arterial pulse pressure to monitor fluid responsiveness in the operating room. Anesth Analg 2008; 106:1195–200
Monnet X, Rienzo M, Osman D, Anguel N, Richard C, Pinsky MR, Teboul JL: Esophageal Doppler monitoring predicts fluid responsiveness in critically ill ventilated patients. Intensive Care Med 2005; 31:1195–201
Michard F: Changes in arterial pressure during mechanical ventilation. ANESTHESIOLOGY 2005; 103:419–28
Monnet X, Teboul JL: Passive leg raising. Intensive Care Med 2008; 34:659–63
Monnet X, Rienzo M, Osman D, Anguel N, Richard C, Pinsky MR, Teboul JL: Passive leg raising predicts fluid responsiveness in the critically ill. Crit Care Med 2006; 34:1402–7
Caille V, Jabot J, Belliard G, Charron C, Jardin F, Vieillard-Baron A: Hemodynamic effects of passive leg raising: An echocardiographic study in patients with shock. Intensive Care Med 2008; 34:1239–45
Monnet X, Teboul JL: Volume responsiveness. Curr Opin Crit Care 2007; 13:549–53
Ramsay MA, Savege TM, Simpson BR, Goodwin R: Controlled sedation with alphaxalone-alphadolone. Br Med J 1974; 2(5920):656–9
Muller L, Chanques G, Bourgaux C, Louart G, Jaber S, Fabbro-Peray P, Ripart J, de La Coussaye JE, Lefrant JY: Impact of the use of propofol remifentanil goal-directed sedation adapted by nurses on the time to extubation in mechanically ventilated ICU patients: The experience of a French ICU. Ann Fr Anesth Reanim 2008; 27:481.e1–8
Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, Schein RM, Sibbald WJ: Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest 1992; 101:1644–55
Knaus WA, Draper EA, Wagner DP, Zimmerman JE: APACHE II: A severity of disease classification system. Crit Care Med 1985; 13:818–29
Fagon JY, Chastre J, Novara A, Medioni P, Gibert C: Characterization of intensive care unit patients using a model based on the presence or absence of organ dysfunctions and/or infection: The ODIN model. Intensive Care Med 1993; 19:137–44
Mayo PH, Beaulieu Y, Doelken P, Feller-Kopman D, Harrod C, Kaplan A, Oropello J, Vieillard-Baron A, Axler O, Lichtenstein D, Maury E, Slama M, Vignon P: American College of Chest Physicians/La Société de Réanimation de Langue Française statement on competence in critical care ultrasonography. Chest 2009; 135:1050–60
Lewis JF, Kuo LC, Nelson JG, Limacher MC, Quinones MA: Pulsed Doppler echocardiographic determination of stroke volume and cardiac output: Clinical validation of two new methods using the apical window. Circulation 1984; 70:425–31
Ray P, Le Manach Y, Riou B, Houle TT: Statistical evaluation of a biomarker. ANESTHESIOLOGY 2010; 112:1023–40
Hanley JA, McNeil BJ: A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983; 148:839–43
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; 31:517–23
Vallée F, Richard JC, Mari A, Gallas T, Arsac E, Verlaan PS, Chousterman B, Samii K, Genestal M, Fourcade O: Pulse pressure variations adjusted by alveolar driving pressure to assess fluid responsiveness. Intensive Care Med 2009; 35:1004–10
Muller L, Louart G, Bousquet PJ, Candela D, Zoric L, de La Coussaye JE, Jaber S, Lefrant JY: The influence of the airway driving pressure on pulsed pressure variation as a predictor of fluid responsiveness. Intensive Care Med 2010; 36:496–503
Vieillard-Baron A, Slama M, Cholley B, Janvier G, Vignon P: Echocardiography in the intensive care unit: From evolution to revolution? Intensive Care Med 2008; 34:243–9
Maizel J, Airapetian N, Lorne E, Tribouilloy C, Massy Z, Slama M: Diagnosis of central hypovolemia by using passive leg raising. Intensive Care Med 2007; 33:1133–8
Slama M, Masson H, Teboul JL, Arnout ML, Susic D, Frohlich E, Andrejak M: Respiratory variations of aortic VTI: A new index of hypovolemia and fluid responsiveness. Am J Physiol Heart Circ Physiol 2002; 283:H1729–33
Lamia B, Ochagavia A, Monnet X, Chemla D, Richard C, Teboul JL: Echocardiographic prediction of volume responsiveness in critically ill patients with spontaneously breathing activity. Intensive Care Med 2007; 33:1125–32
Bendjelid K, Romand JA: Fluid responsiveness in mechanically ventilated patients: A review of indices used in intensive care. Intensive Care Med 2003; 29:352–60
Osman D, Ridel C, Ray P, Monnet X, Anguel N, Richard C, Teboul JL: Cardiac filling pressures are not appropriate to predict hemodynamic response to volume challenge. Crit Care Med 2007; 35:64–8
Marik PE, Cavallazzi R, Vasu T, Hirani A: Dynamic changes in arterial waveform derived variables and fluid responsiveness in mechanically ventilated patients: A systematic review of the literature. Crit Care Med 2009; 37:2642–7
Oren-Grinberg A, Park KW: Assessment of myocardial systolic function by TEE. Int Anesthesiol Clin 2008; 46:31–49
Verheij J, van Lingen A, Beishuizen A, Christiaans HM, de Jong JR, Girbes AR, Wisselink W, Rauwerda JA, Huybregts MA, Groeneveld AB: Cardiac response is greater for colloid than saline fluid loading after cardiac or vascular surgery. Intensive Care Med 2006; 32:1030–8
McIlroy DR, Kharasch ED: Acute intravascular volume expansion with rapidly administered crystalloid or colloid in the setting of moderate hypovolemia. Anesth Analg 2003; 96:1572–7
Trof RJ, Sukul SP, Twisk JW, Girbes AR, Groeneveld AB: Greater cardiac response of colloid than saline fluid loading in septic and non-septic critically ill patients with clinical hypovolaemia. Intensive Care Med 2010; 36:697–701
Cholley BP, Singer M: Esophageal Doppler: Noninvasive cardiac output monitor. Echocardiography 2003; 20:763–9
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
Fig. 1. Receiver operator characteristic (ROC) curves for variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%).
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Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
Fig. 2. Individual values of variation of velocity time index (VTI) after infusion of 100 ml fluid over 1 min (ΔVTI100) (%) with the best cutoff value. Sp = specificity; Se = sensitivity.
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Fig. 3. Correlation (A  ) and Bland and Altman diagram (B  ) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
Fig. 3. Correlation (A 
	) and Bland and Altman diagram (B 
	) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
Fig. 3. Correlation (A  ) and Bland and Altman diagram (B  ) between variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100) and variation of VTI after infusion of 500 ml fluid over 15 min (ΔVTI500).
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Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
Fig. 4. Receiver operator characteristic (ROC) curves of variation of velocity time index (VTI) (cm) after infusion of 100 ml fluid over 1 min (ΔVTI100), pulse pressure variation (PPV) (%), and central venous pressure (CVP) (mmHg) in 29 patients in whom VTI, PPV, and CVP were measured.
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Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A  ) and nonresponders (B  ).
Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A 
	) and nonresponders (B 
	).
Fig. 5. Individual data for velocity time index (VTI) at baseline (T0), 1 min (T1), and 15 min (T15) in responders (A  ) and nonresponders (B  ).
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Table 1. Characteristics of the General Population and Comparison between Responders and Nonresponders
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Table 1. Characteristics of the General Population and Comparison between Responders and Nonresponders
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