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Fluid Challenge During Anesthesia: A Systematic Review and Meta-analysis

Messina, Antonio PhD*; Pelaia, Corrado MD; Bruni, Andrea MD; Garofalo, Eugenio MD; Bonicolini, Eleonora MD; Longhini, Federico MD; Dellara, Erica MD§; Saderi, Laura BSc; Romagnoli, Stefano MD; Sotgiu, Giovanni MD, FERS; Cecconi, Maurizio MD, FRCA, FICM*; Navalesi, Paolo MD, FERS

Author Information
doi: 10.1213/ANE.0000000000003834



  • Question: Is the modality of fluid challenge (FC) administration consistent and the dynamic indexes of fluid responsiveness reliable in operating room?
  • Finding: FC in operating room usually consists of a colloid bolus of 250 or 500 mL administered in about 10 minutes; the pooled sensitivity and specificity of pulse pressure variation and stroke volume variation are limited.
  • Meaning: The FC is quite standardized in operating room, with the exception of volume used, and caution is needed when pulse pressure variation or stroke volume variation is used to assess fluid responsiveness.

Perioperative fluid therapy is a key component of the management of surgical patients and dedicated algorithms and protocols are nowadays part of the included into routine intraoperative and perioperative care.1,2 Conventional fluid administration, aimed at balancing fluid intake and output, should be distinguished from the acute treatment of hemodynamically unstable patients.1,3 Several dynamic tests have been proposed to predict whether or not fluid infusion would increase the cardiac output (CO), such as the fluctuations of pulse pressure or stroke volume (SV) during mechanical ventilation or the increase in right preload by modifying the position of the patient4 or interrupting positive pressure ventilation.5

The fluid challenge (FC) consists in assessing the hemodynamic effects of giving fluid in a limited period of time.6 By allowing to restore fluid depletion when indicated, while minimizing the risk of overloading,3 the FC is routinely used to assess fluid depletion in surgical patients.6 In the operating room, fluids may be administered either to correct an unexpected episode of hypotension or hypovolemia1,7–9 or in small aliquots protocolized to optimize hemodynamics, the so-called Goal-Directed Therapy (GDT).10,11

Type, amount and duration of the infusion, interval between FC administration and fluid responsiveness assessment, indices, and relative thresholds for determining the hemodynamic response are all important issues potentially affecting the outcome of the FC. A recent study considering adult critically ill patients, however, highlighted the lack of definite standards for FC administration and evaluation in intensive care unit (ICU).12 It remains unclear, however, what the best approach to FC administration should be and, in fact, wide variability exists at this regard among studies performed both in the perioperative setting and in the ICU.12

Aim of this systematic review is to describe and compare the modality of FC administration in non-GDT and GDT studies performed in patients undergoing surgery, considering indications, hemodynamic targets and thresholds for fluid responsiveness assessment, use of safety limits, fluid type, dose, and time of infusion. In addition, we evaluated the use of 2 dynamic predictors of fluid responsiveness, pulse pressure variation (PPV) and SV variation (SVV), to guide FC administration and performed a meta-analysis to ascertain the reliability of both of these indexes in predicting fluid responsiveness.


Study Selection and Inclusion Criteria

FC was considered as the infusion of a definite quantity of fluid of a specific quality in a period of time (expressed either as span or infusion rate), administered to assess variations of a hemodynamic variable. Studies in whom the FC was not defined or standardized were excluded.

All articles in English language, including adult patients, without restrictions related to type of surgery and surgical risk, and published in indexed scientific journals in the last 20 years were considered (January 1, 1997 to January 1, 2017). Reviews, case reports, and studies published in abstract form were excluded. Only 2-harm GDT studies (treatment–control subgroups) were included.

Search Strategy

Three authors (A.M., E.B., and C.P.) independently searched MEDLINE, EMBASE, and Cochrane Database of Systematic Reviews using the following keywords and their related MeSh terms: “fluid challenge,” “fluid responsiveness,” “stroke volume variation,” “pulse pressure variation,” “dynamic indices OR indexes,” “intraoperative fluid optimization,” “surgery” “directed therapy,” “goal-directed therapy,” “fluid therapy,” “goal oriented,” “goal targeted,” and “fluid optimization.” References of included papers and review articles were also examined to identify additional studies missed during the primary search (Supplemental Digital Content, Document,

Data Extraction

All articles were independently evaluated by couple of researchers who reported all collected data in an EXCEL (Microsoft, Redwood, MS) spreadsheet specifically designed for the study purposes. When data were not available, the corresponding authors were contacted. In case of disagreement for the article selection or variables to be retrieved, it was requested the intervention of a third, senior, expert (P.N., G.S.).

Whenever possible, the mean body surface area and weight of the enrolled samples were used to recalculate the nonindexed variables, reporting the corresponding indexed values (ie, from CO and SV to cardiac index and SV index [SVI]) and the volume/weight (mL/kg) reporting the absolute volume (mL). All the hemodynamic changes associated to FC administration were reported as percentage of variation with respect to baseline values.

Statistical Analysis

Statistical analyses were performed on the statistical figures reported in the selected articles. On this basis, the statistical unit of observation for the variables was the single study. The statistical software STATA13 (StataCorp, College Station, TX), StatsDirect version 3 (StatsDirect Ltd, Altrincham, UK), and Metadisc version 1.4 ( were used to perform all the statistical analyses. Quantitative variables were summarized with means (standard deviations [SDs]) or medians (interquartile ranges [IQRs]) according to their distribution. Student t test or Mann-Whitney test was computed to find differences between non-GDT and GDT studies. Two-tailed P values <.05 were considered significant.

A meta-analysis of the PPV and SVV values before FC administration was performed, using data obtained from those studies evaluating PPV and SVV reliability in predicting fluid responsiveness by means of a receiving operating characteristics (ROCs) curve approach. Random effects models were used. In-between study heterogeneity was assessed through the I2 indicator. Bias assessment graphs were plotted, and Egger regression analysis was used to evaluate the publication bias. The area under the curve (AUC) of pooled ROC curves was reported with 95% confidence interval (95% CI).


Flow of the studies. ED indicates emergency department; FC, fluid challenge; GDT, Goal-Directed Therapy; ICU, intensive care unit.

The electronic search identified 14,378 potentially relevant studies. Detailed description of the selection process flow is provided in the Figure. Two hundred five full-text articles were selected, and only 35 non-GDT studies and 33 GDT studies met criteria for inclusion.

Epidemiological Design and Characteristics of the Population

Only studies published after 2001 met inclusion criteria (Tables 1–2). Overall, non-GDT studies recruited 1436 patients, with a median (IQR) of 38 (31–59) patients enrolled, 35 (21–50) of whom were analyzed. The median (IQR) number of FCs administered was 40 (30–52) for each study. Overall, the mean (SD) number of fluid responders was 57.7% (14.3%).

Table 1.
Table 1.:
Characteristics of the Non-GDT Studies Included in the Systematic Review
Table 2.
Table 2.:
Characteristics of the GDT Studies Included in the Systematic Review

GDT studies were all randomized controlled trials and included 3581 patients with a higher median (IQR) number of enrolled [92 (49–125), P < .0001] and analyzed [81 (48–121), P < .0001] patients per study, as compared to non-GDT studies. Only 3 studies were not conducted in general anesthesia. Not 1 GDT study reported the number of fluid responders to the predefined FC (Supplemental Digital Content, Table 1,

Indications for FC Administration, Hemodynamic Targets, and Thresholds for Fluid Responsiveness Assessment and Use of Safety Limits

In 13 non-GDT (37.1%) studies, FC was infused “after induction” of the general anesthesia, while in 8 (22.8%) studies, FC was infused during a specific surgical timing; in 7 (20.0%), timing was not detailed; finally, in 5 (14.2%), FC was administered following the decision of the attending anesthetist, based on specific16,39 (10%–20% drop in mean arterial pressure or cardiac index) or undefined criteria (Tables 3 and 4).13,15,23

Table 3.
Table 3.:
Modalities of FC Administration in Non-GDT Studies
Table 4.
Table 4.:
Modalities of FC Administration in GDT Studies

In 24 (68.5%) non-GDT studies, either SVI or SV were used to assess fluid responsiveness; in 9 of these studies, a positive response was defined by an increase of ≥15%, in 7 of ≥10%, in 4 of ≥25%, in 2 of ≥20%, in one of ≥12%, and in another one of ≥5%. In the remaining 11 (31.5%) studies, the hemodynamic variables used to assess fluid responsiveness were either cardiac index or CO; in 7 of these studies, a positive response was defined by an increase of ≥15%, in 3 of >15%, and in 1 of ≥10%.

Three (9.1%) GDT studies administered the FC after the sequential evaluation of cardiac index, SVI, and SVV and one of cardiac index and SVI, while in 19 (57.5%), the GDT protocol was guided by a 10% increase of SV or SVI (in 5 of these studies the corrected systolic flow time [FTC] <0.35 seconds was also considered together with SV increase, and in 2 the SVV >10% or >13%); in 5 (15.1%) by SVV values ranging from 10% to 13%, in the remaining 6 (18.1%) by the variability index, PPV, mean arterial pressure, central venous oxygen saturation, or wedge pressure. In 12 of 19 GDT studies assessing an SV increase >10%,50,52,55,56,59,60,63,65–67,73,74 the first bolus was administered regardless of predetermined cutoff hemodynamic values suggesting fluid depletion.

A safety limit indicating the absence of hemodynamic response to FC and risk of futile fluid administration was present in 60.6% and 0% of GDT and non-GDT studies, respectively.

Fluid Type, Dose, and Time of Infusion

Colloids were used in 30 non-GDT and GDT studies (85.7% vs 90.9%, respectively; P = .80) (Tables 3 and 4). In 29 non-GDT studies, the colloid infused was the 6% hydroxyethyl starch (HES 6%, 96.6% of this subgroup), while in 1 study the type of colloid was not specified. In 20 GDT studies, the colloid infused was the HES 6% (66.7% of this subgroup), while in 5 studies was a gelatin (16.7% of this subgroup), in 3 studies an unspecified colloid (10.0% of this subgroup), and in one study albumin (3.3%) or, in another study, both HES 6% and gelatin (3.3%). Overall, the use of HES 6% was not different between non-GDT and GDT studies (82.8% vs 63.6%, respectively; P = .13).

In 16 (45.7%) non-GDT studies, the volume administered was 7.5 mL/kg (7–10 mL/kg). In 11 of these studies reporting the mean body weight of the enrolled population, the median (IQR) volume was 619 mL (655–538 mL). In the remaining 19 non-GDT studies, 12 (34.2%) infused 500 mL.

In 16 (48.8%) GDT studies, FC consisted of 250 mL and the median (IQR) FC volume infused, while in 9 (27.2%), the FC volume administered was 3 mL/kg, but in 2 of these only the first bolus consisted of 7 mL/kg. Only 2 GDT studies reported the mean body weight and the mean (SD) calculated FC volume was 224 mL (24 mL). The median (IQR) volume infused was significantly higher in non-GDT as compared to GDT studies [500 mL (467–551 mL) vs 250 mL (150–250 mL); P < .0001].

Three (8.6%) non-GDT studies reported an infusion rate of 1 mL/kg/min. In the remaining 32, the FC was administered in 30 minutes in 7 (21.8%) studies, in 20 minutes in 2 (6.2%) studies, in 13 minutes in 1 (3.1%) study, in 10 minutes, in 15 studies (46.8%), in 5 minutes in 4 (12.5%) studies, in 3 minutes in 1 (3.1%) study, and in 2 minutes in 2 (6.2%) studies. The median (IQR) time of infusion was 10 minutes (5–20 minutes). In 15 (45.4%) GDT studies the FC was administered in a median (IQR) time of 10 minutes (5–15 minutes), while in the others as “bolus”. Mean (SD) infusion time was not significantly different between non-GDT and GDT (14 minutes [9 minutes] vs 9 minutes [5 minutes], respectively; P = .07).

The rate of infusion was calculated in 28 (80.0%) non-GDT studies and in 12 (36.3%) GDT studies reporting both volume and time of FC administration. In non-GDT studies, the mean (SD) rate of infusion was 49.2 mL/min (29.1 mL/min), while in GDT studies was 36.5 mL/min (31.4 mL/min) (P = .07).

Meta-analysis: Pooled ROC Curve of PPV and SVV

PPV and SVV were tested as dynamic indexes of fluid responsiveness only in non-GDT studies. The reported values of the ROC curve analysis fitted the criteria for meta-analysis in 10 non-GDT studies for PPV, including 366 patients and infusing 390 FCs,15,16,22,25,26,28,31,33,35,38,44 and in 16 non-GDT studies for SVV, including 816 patients and infusing 1020 FCs16–19,25–27,29,30,34–38,44,46 (see Table 5).

Table 5.
Table 5.:
Reported Sensitivity and Specificity of PPV and SVV in Non-GDT Studies Included in the Meta-analysis

For the PPV, the pooled AUC (95% CI) was 0.86 (0.80–0.92). The mean (SD) threshold of PPV predicting fluid responsiveness was 10.5% (3.2%), ranging from 8%16 to 15%.28 The pooled (95% CI) sensitivity and specificity were 0.80 (0.74–0.85) and 0.83 (0.73–0.91), respectively. Heterogeneity (I2 [95% CI]) for PPV sensitivity was 0.0% (0.0–52.7), while for PPV specificity (I2 [95% CI]) was 43.5% (0.0–71.4) (Supplemental Digital Content, Figures 1 and 3,

For the SVV, the pooled AUC (95% CI) was 0.87 (0.81–0.93). The mean (SD) threshold of SVV predicting fluid responsiveness was 11.3% (3.1%), ranging from 7.5%26 to 15.5%.17 The pooled (95% CI) sensitivity and specificity were 0.82 (0.75–0.89) and 0.77 (0.71–0.82), respectively. Heterogeneity (I2 (95% CI]) for SVV sensitivity was 68.3% (40.9–79.9), while for SVV specificity (I2 (95% CI]) was 22.0% (0.0–56.8) (Supplemental Digital Content, Figures 2–3, Funnel plots, and associated Egger tests, aimed at assessing publication bias/small study effects show asymmetries (Supplemental Digital Content, Figures 1–2,


The present study shows that in surgical patients FC consists, in the majority of the cases, in the administration of colloids, more frequently in aliquots of 500 mL (single bolus, non-GDT studies) or 250 mL (multiple boluses, GDT studies) administered in about 10 minutes. SVI or SV changes are used to assess fluid responsiveness, but the threshold of >10% is standardized only in GDT studies. The reliability of PPV and SVV in predicting fluid responsiveness is limited.

There is increasing evidence that fluid management affects the outcome of critically ill and surgical patients,80 and the debate regarding the correct fluid management in operating room is still open.7,10,11,81,82 Irrespectively to the applied fluid therapy policy (GDT, zero balance, or fluid restriction), however, intraoperative fluid administration should be titrated on hemodynamic parameters to prevent fluid overload,80 while the absolute volume of fluids administered is less important than the modality of administration.10

Colloids were overall used in the 86% of the studies included in the review. This is somewhat surprising, considering that several studies showed, in critically ill patients, the use of colloids being associated with an increased risk of renal failure and death.83–85 Worth mentioning, however, recent meta-analysis do not confirm these caveats in surgical patients.86,87 In principle, the infusion of colloids should be associated with a long-lasting hemodynamic effect on SV, reducing intraoperative fluid administration,88 and increasing microcirculatory blood flow.89,90 While the hemodynamic effect of 250 mL crystalloids is dissipated within 10 minutes,91 the macromolecules of colloids are retained in the intravascular compartment with a phase of distribution dependent on patient’s volemic status.92 Indeed, a number of GDT studies show that intraoperative SV optimization through colloids, predominantly starch solutions suspended in crystalloids, associated with background crystalloid infusions or inotropes infusion, results in improved postoperative outcomes.88

In 36.3% of the GDT trials,50,52,55,56,59,60,63,65–67,73,74 the first FC was administered regardless of the values of dynamic or static indexes of fluid responsiveness and, then, was repeated according to SV response. The number of fluid responders to the first bolus was not assessed in any GDT trial. However, Bartha et al,93 in a subanalysis of a GDT aimed to SV and oxygen delivery optimization and performed in patients with hip fracture,63 reported a 38.5% and a 8.5% of responders to the first and the second FC (3 mL/kg of colloids) respectively, while only 13.8% of controls responded to clinician-guided FC, consisting of Ringer acetate or colloids, before spinal anesthesia.

A range of SVV from 10% to 13% and safety limits between 8% and 13% have been used in 15.1% of the studies (Table 4). The hemodynamic targets and thresholds adopted are variable among studies. Despite 63.3% of the studies evaluated SVV variations after FC administration, a 10% target threshold was adopted in 38.2% of the studies. Indeed, the choice of a predefined threshold could be inaccurate, the “gray zone” of inaccuracy of the dynamic indexes ranging between 9% and 13%.

The lack of a definitive threshold might influence the number of fluid responders because the ROC curve approach is constructed using a reference gold standard test to define the positive or negative result. For example, the definition of fluid responsiveness could be affected by the threshold adopted because a patient considered responder for a >10% increase in SV may not be responder if the threshold is raised up to >15%.94

Regarding the meta-analysis of the dynamic index of fluid responsiveness, in the literature, the reliability of PPV and SVV in operating room has been investigated only in few systematic reviews and, to our knowledge, the present review is the largest ever conducted. Marik et al95 report for PPV an AUC of 0.93 (95% CI, 0.92–0.94) in a subgroup of studies where a mean intraoperative tidal volume >8 mL/kg was delivered. In this meta-analysis, only 5 studies after induction of anesthesia were included, while 10 after surgery. In 2011, Zhang et al96 reported an AUC of 0.94 (95% CI, 0.907–0.945) for SVV in 8 surgical studies. However, as pointed out by the authors, because of the small number of included studies, the cumulative AUC of SVV would drop down to 0.84 by excluding only 1 study reporting an AUC of 0.99.36 Furthermore, as suggested by our findings, publication bias/small study effects should be also considered.

Interestingly, despite most of the validity criteria affecting dynamic indexes reliability, such as tidal volume, heart rate-to-respiratory rate ratio, presence of spontaneous breathing activity, pulmonary and chest wall compliance, and right ventricle function, should be more frequently respected in the operating room rather than in ICU,97 pooled sensitivity and specificity of both PPV (0.79 and 0.84, respectively) and SVV (0.80 and 0.77, respectively) are quite limited. A more recent approach to fluid responsiveness introduced the flexible gray-zone concept98 instead of the simplistic ROC curve application to define fixed cutoffs to discriminate responders and nonresponders. This gray-zone approach identifies a range of inaccuracy, in which up to 25% of PPV values of surgical patients are included.98 The results of this meta-analysis suggest caution in relying on baseline PPV and SVV to assess fluid responsiveness, encouraging the use in operating room of recently introduced hemodynamic tests, such as the end-expiratory occlusion and the mini-FC tests.9,99


In surgical patients, much more than in ICU patients, some FC key components, such as type of fluid (colloids, often 6% HES), volume (500 and 250 mL in non-GDT and GDT studies, respectively), and time of infusion (10 minutes) are quite standardized. In non-GDT studies, thresholds for assessment of fluid responsiveness are not standardized and safety limits are not used, while GDT studies frequently adopt a >10% increase of SV or SVI with safety limits. The pooled sensitivity and specificity of PPV and SVV are limited, suggesting caution when using these indexes of fluid responsiveness in the operating room. E


Name: Antonio Messina, PhD.

Contribution: This author helped design the study, collect the data, perform the data analysis, and write the manuscript.

Conflicts of Interest: None.

Name: Corrado Pelaia, MD.

Contribution: This author helped collect the data, prepare the manuscript, and interpret the data.

Conflicts of Interest: None.

Name: Andrea Bruni, MD.

Contribution: This author helped collect and interpret the data collection and prepare the manuscript.

Conflicts of Interest: None.

Name: Eugenio Garofalo, MD.

Contribution: This author helped collect and interpret the data and prepare the manuscript.

Conflicts of Interest: None.

Name: Eleonora Bonicolini, MD.

Contribution: This author helped collect and interpret the data and prepare the manuscript.

Conflicts of Interest: None.

Name: Federico Longhini, MD.

Contribution: This author helped collect and interpret the data and prepare the manuscript.

Conflicts of Interest: None.

Name: Erica Dellara, MD.

Contribution: This author helped collect and interpret the data and prepare the manuscript.

Conflicts of Interest: None.

Name: Laura Saderi, BSc.

Contribution: This author helped perform the data analysis, interpret the data, and prepare the manuscript.

Conflicts of Interest: None.

Name: Stefano Romagnoli, MD.

Contribution: This author helped design the study, interpret the data, and prepare the manuscript.

Conflicts of Interest: In the 5 past years, S. Romagnoli received speaking fees and travel expenses for scientific meetings from Vygon.

Name: Giovanni Sotgiu, MD, FERS.

Contribution: This author helped perform the data analysis, interpret the data, and prepare the manuscript.

Conflicts of Interest: None.

Name: Maurizio Cecconi, MD, FRCA, FICM.

Contribution: This author helped interpret the data and prepare the manuscript.

Conflicts of Interest: M. Cecconi is a consultant for Edwards Lifesciences, LiDCO, and Cheetah Medical.

Name: Paolo Navalesi, MD, FERS.

Contribution: This author helped design the study, collect the data, perform the data analysis, and write the manuscript.

Conflicts of Interest: P. Navalesi research laboratory has received equipment and grants from Maquet Critical Care, Draeger, and Intersurgical S.p.A. He also received honoraria/speaking fees from Maquet Critical Care, Draeger, Breas, Philips, Resmed, Hill-Rom, MSD, and Novartis. He contributed to the development of the helmet Next, whose license for patent belongs to Intersurgical S.p.A., and receive royalties for that invention.

This manuscript was handled by: Maxime Cannesson, MD, PhD.


1. Navarro LH, Bloomstone JA, Auler JO Jr, et al. Perioperative fluid therapy: a statement from the international Fluid Optimization Group. Perioper Med (Lond). 2015;4:3.
2. Loftus TJ, Stelton S, Efaw BW, Bloomstone J. A system-wide enhanced recovery program focusing on two key process steps reduces complications and readmissions in patients undergoing bowel surgery. J Healthc Qual. 2017;39:129–135.
3. Vincent JL, Weil MH. Fluid challenge revisited. Crit Care Med. 2006;34:1333–1337.
4. Monnet X, Teboul JL. Passive leg raising: five rules, not a drop of fluid! Crit Care. 2015;19:18.
5. Monnet X, Osman D, Ridel C, Lamia B, Richard C, Teboul JL. Predicting volume responsiveness by using the end-expiratory occlusion in mechanically ventilated intensive care unit patients. Crit Care Med. 2009;37:951–956.
6. Cecconi M, Parsons AK, Rhodes A. What is a fluid challenge? Curr Opin Crit Care. 2011;17:290–295.
7. Lobo SM, de Oliveira NE. Clinical review: what are the best hemodynamic targets for noncardiac surgical patients? Crit Care. 2013;17:210.
8. Guinot PG, Bernard E, Defrancq F, et al. Mini-fluid challenge predicts fluid responsiveness during spontaneous breathing under spinal anaesthesia: an observational study. Eur J Anaesthesiol. 2015;32:645–649.
9. Biais M, de Courson H, Lanchon R, et al. Mini-fluid challenge of 100 ml of crystalloid predicts fluid responsiveness in the operating room. Anesthesiology. 2017;127:450–456.
10. Cecconi M, Corredor C, Arulkumaran N, et al. Clinical review: goal-directed therapy-what is the evidence in surgical patients? The effect on different risk groups. Crit Care. 2013;17:209.
11. Hamilton MA, Cecconi M, Rhodes A. A systematic review and meta-analysis on the use of preemptive hemodynamic intervention to improve postoperative outcomes in moderate and high-risk surgical patients. Anesth Analg. 2011;112:1392–1402.
12. Messina A, Longhini F, Coppo C, et al. Use of the fluid challenge in critically Ill adult patients: a systematic review. Anesth Analg. 2017;125:1532–1543.
13. Blanié A, Soued M, Benhamou D, Mazoit JX, Duranteau J. A comparison of photoplethysmography versus esophageal Doppler for the assessment of cardiac index during major noncardiac surgery. Anesth Analg. 2016;122:430–436.
14. Kang WS, Oh CS, Park C, et al. Diagnosis accuracy of mean arterial pressure variation during a lung recruitment maneuver to predict fluid responsiveness in thoracic surgery with one-lung ventilation. Biomed Res Int. 2016;2016:3623710.
    15. Jacquet-Lagrèze M, Baudin F, David JS, et al. End-tidal carbon dioxide variation after a 100- and a 500-ml fluid challenge to assess fluid responsiveness. Ann Intensive Care. 2016;6:37.
    16. Konur H, Erdogan Kayhan G, Toprak HI, et al. Evaluation of pleth variability index as a predictor of fluid responsiveness during orthotopic liver transplantation. Kaohsiung J Med Sci. 2016;32:373–380.
    17. Zhang X, Feng J, Zhu P, Luan H, Wu Y, Zhao Z. Ultrasonographic measurements of the inferior vena cava variation as a predictor of fluid responsiveness in patients undergoing anesthesia for surgery. J Surg Res. 2016;204:118–122.
    18. Li J, Ji FH, Yang JP. Evaluation of stroke volume variation obtained by the FloTrac™/Vigileo™ system to guide preoperative fluid therapy in patients undergoing brain surgery. J Int Med Res. 2012;40:1175–1181.
    19. Berger K, Francony G, Bouzat P, et al. Prone position affects stroke volume variation performance in predicting fluid responsiveness in neurosurgical patients. Minerva Anestesiol. 2015;81:628–635.
    20. Tusman G, Groisman I, Maidana GA, et al. The sensitivity and specificity of pulmonary carbon dioxide elimination for noninvasive assessment of fluid responsiveness. Anesth Analg. 2016;122:1404–1411.
    21. Siswojo AS, Wong DM, Phan TD, Kluger R. Pleth variability index predicts fluid responsiveness in mechanically ventilated adults during general anesthesia for noncardiac surgery. J Cardiothorac Vasc Anesth. 2014;28:1505–1509.
    22. Song Y, Kwak YL, Song JW, Kim YJ, Shim JK. Respirophasic carotid artery peak velocity variation as a predictor of fluid responsiveness in mechanically ventilated patients with coronary artery disease. Br J Anaesth. 2014;113:61–66.
    23. Fu Q, Zhao F, Mi W, Zhang H. Stroke volume variation fail to predict fluid responsiveness in patients undergoing pulmonary lobectomy with one-lung ventilation using thoracotomy. Biosci Trends. 2014;8:59–63.
    24. Guinot PG, de Broca B, Abou Arab O, et al. Ability of stroke volume variation measured by oesophageal Doppler monitoring to predict fluid responsiveness during surgery. Br J Anaesth. 2013;110:28–33.
    25. Chin JH, Lee EH, Hwang GS, Choi WJ. Prediction of fluid responsiveness using dynamic preload indices in patients undergoing robot-assisted surgery with pneumoperitoneum in the Trendelenburg position. Anaesth Intensive Care. 2013;41:515–522.
    26. Kim KM, Gwak MS, Choi SJ, Kim MH, Park MH, Heo BY. Pulse pressure variation and stroke volume variation to predict fluid responsiveness in patients undergoing carotid endarterectomy. Korean J Anesthesiol. 2013;65:237–243.
    27. Guinot PG, de Broca B, Bernard E, Abou Arab O, Lorne E, Dupont H. Respiratory stroke volume variation assessed by oesophageal Doppler monitoring predicts fluid responsiveness during laparoscopy. Br J Anaesth. 2014;112:660–664.
    28. Yang SY, Shim JK, Song Y, Seo SJ, Kwak YL. Validation of pulse pressure variation and corrected flow time as predictors of fluid responsiveness in patients in the prone position. Br J Anaesth. 2013;110:713–720.
    29. Lee JY, Park HY, Jung WS, Jo YY, Kwak HJ. Comparative study of pressure- and volume-controlled ventilation on stroke volume variation as a predictor of fluid responsiveness in patients undergoing major abdominal surgery. J Crit Care. 2012;27:531.e9–514.e9.
    30. Suehiro K, Okutani R. Influence of tidal volume for stroke volume variation to predict fluid responsiveness in patients undergoing one-lung ventilation. J Anesth. 2011;25:777–780.
    31. Lee JH, Jeon Y, Bahk JH, et al. Pulse-pressure variation predicts fluid responsiveness during heart displacement for off-pump coronary artery bypass surgery. J Cardiothorac Vasc Anesth. 2011;25:1056–1062.
    32. Li C, Lin FQ, Fu SK, et al. Stroke volume variation for prediction of fluid responsiveness in patients undergoing gastrointestinal surgery. Int J Med Sci. 2013;10:148–155.
    33. Biais M, Stecken L, Ottolenghi L, et al. The ability of pulse pressure variations obtained with CNAP™ device to predict fluid responsiveness in the operating room. Anesth Analg. 2011;113:523–528.
    34. Shin YH, Ko JS, Gwak MS, Kim GS, Lee JH, Lee SK. Utility of uncalibrated femoral stroke volume variation as a predictor of fluid responsiveness during the anhepatic phase of liver transplantation. Liver Transpl. 2011;17:53–59.
    35. Biais M, Bernard O, Ha JC, Degryse C, Sztark F. Abilities of pulse pressure variations and stroke volume variations to predict fluid responsiveness in prone position during scoliosis surgery. Br J Anaesth. 2010;104:407–413.
    36. Zimmermann M, Feibicke T, Keyl C, et al. Accuracy of stroke volume variation compared with pleth variability index to predict fluid responsiveness in mechanically ventilated patients undergoing major surgery. Eur J Anaesthesiol. 2010;27:555–561.
    37. Suehiro K, Okutani R. Stroke volume variation as a predictor of fluid responsiveness in patients undergoing one-lung ventilation. J Cardiothorac Vasc Anesth. 2010;24:772–775.
    38. de Waal EE, Rex S, Kruitwagen CL, Kalkman CJ, Buhre WF. Dynamic preload indicators fail to predict fluid responsiveness in open-chest conditions. Crit Care Med. 2009;37:510–515.
    39. Gouvêa G, Diaz R, Auler L, Toledo R, Martinho JM. Evaluation of the pulse pressure variation index as a predictor of fluid responsiveness during orthotopic liver transplantation. Br J Anaesth. 2009;103:238–243.
    40. Jørgensen CC, Bundgaard-Nielsen M, Skovgaard LT, Secher NH, Kehlet H. Stroke volume averaging for individualized goal-directed fluid therapy with oesophageal Doppler. Acta Anaesthesiol Scand. 2009;53:34–38.
    41. Belloni L, Pisano A, Natale A, et al. Assessment of fluid-responsiveness parameters for off-pump coronary artery bypass surgery: a comparison among LiDCO, transesophageal echochardiography, and pulmonary artery catheter. J Cardiothorac Vasc Anesth. 2008;22:243–248.
    42. Wiesenack C, Fiegl C, Keyser A, Prasser C, Keyl C. Assessment of fluid responsiveness in mechanically ventilated cardiac surgical patients. Eur J Anaesthesiol. 2005;22:658–665.
    43. Wiesenack C, Fiegl C, Keyser A, Laule S, Prasser C, Keyl C. Continuously assessed right ventricular end-diastolic volume as a marker of cardiac preload and fluid responsiveness in mechanically ventilated cardiac surgical patients. Crit Care. 2005;9:R226–R233.
    44. 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;128:848–854.
    45. 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.
    46. Berkenstadt H, Margalit N, Hadani M, et al. Stroke volume variation as a predictor of fluid responsiveness in patients undergoing brain surgery. Anesth Analg. 2001;92:984–989.
    47. Osawa EA, Rhodes A, Landoni G, et al. Effect of perioperative goal-directed hemodynamic resuscitation therapy on outcomes following cardiac surgery: a randomized clinical trial and systematic review. Crit Care Med. 2016;44:724–733.
    48. Funk DJ, HayGlass KT, Koulack J, Harding G, Boyd A, Brinkman R. A randomized controlled trial on the effects of goal-directed therapy on the inflammatory response open abdominal aortic aneurysm repair. Crit Care. 2015;19:247.
    49. Colantonio L, Claroni C, Fabrizi L, et al. A randomized trial of goal directed vs standard fluid therapy in cytoreductive surgery with hyperthermic intraperitoneal chemotherapy. J Gastrointest Surg. 2015;19:722–729.
    50. Moppett IK, Rowlands M, Mannings A, Moran CG, Wiles MD; NOTTS Investigators. LiDCO-based fluid management in patients undergoing hip fracture surgery under spinal anaesthesia: a randomized trial and systematic review. Br J Anaesth. 2015;114:444–459.
    51. Fellahi JL, Brossier D, Dechanet F, et al. Early goal-directed therapy based on endotracheal bioimpedance cardiography: a prospective, randomized controlled study in coronary surgery. J Clin Monit Comput. 2015;29:351–358.
    52. Pearse RM, Harrison DA, MacDonald N, et al.; OPTIMISE Study Group. Effect of a perioperative, cardiac output-guided hemodynamic therapy algorithm on outcomes following major gastrointestinal surgery: a randomized clinical trial and systematic review. JAMA. 2014;311:2181–2190.
    53. Pestaña D, Espinosa E, Eden A, et al. Perioperative goal-directed hemodynamic optimization using noninvasive cardiac output monitoring in major abdominal surgery: a prospective, randomized, multicenter, pragmatic trial: POEMAS Study (PeriOperative goal-directed thErapy in Major Abdominal Surgery). Anesth Analg. 2014;119:579–587.
    54. Zeng K, Li Y, Liang M, Gao Y, Cai H, Lin C. The influence of goal-directed fluid therapy on the prognosis of elderly patients with hypertension and gastric cancer surgery. Drug Des Devel Ther. 2014;8:2113–2119.
      55. McKenny M, Conroy P, Wong A, et al. A randomised prospective trial of intra-operative oesophageal Doppler-guided fluid administration in major gynaecological surgery. Anaesthesia. 2013;68:1224–1231.
      56. Bundgaard-Nielsen M, Jans Ø, Müller RG, et al. Does goal-directed fluid therapy affect postoperative orthostatic intolerance? A randomized trial. Anesthesiology. 2013;119:813–823.
      57. Zhang J, Chen CQ, Lei XZ, Feng ZY, Zhu SM. Goal-directed fluid optimization based on stroke volume variation and cardiac index during one-lung ventilation in patients undergoing thoracoscopy lobectomy operations: a pilot study. Clinics (Sao Paulo). 2013;68:1065–1070.
        58. Scheeren TW, Wiesenack C, Gerlach H, Marx G. Goal-directed intraoperative fluid therapy guided by stroke volume and its variation in high-risk surgical patients: a prospective randomized multicentre study. J Clin Monit Comput. 2013;27:225–233.
        59. Bisgaard J, Gilsaa T, Rønholm E, Toft P. Haemodynamic optimisation in lower limb arterial surgery: room for improvement? Acta Anaesthesiol Scand. 2013;57:189–198.
        60. Bisgaard J, Gilsaa T, Rønholm E, Toft P. Optimising stroke volume and oxygen delivery in abdominal aortic surgery: a randomised controlled trial. Acta Anaesthesiol Scand. 2013;57:178–188.
        61. Ramsingh DS, Sanghvi C, Gamboa J, Cannesson M, Applegate RL II. Outcome impact of goal directed fluid therapy during high risk abdominal surgery in low to moderate risk patients: a randomized controlled trial. J Clin Monit Comput. 2013;27:249–257.
        62. Srinivasa S, Taylor MH, Singh PP, Yu TC, Soop M, Hill AG. Randomized clinical trial of goal-directed fluid therapy within an enhanced recovery protocol for elective colectomy. Br J Surg. 2013;100:66–74.
        63. Bartha E, Arfwedson C, Imnell A, Fernlund ME, Andersson LE, Kalman S. Randomized controlled trial of goal-directed haemodynamic treatment in patients with proximal femoral fracture. Br J Anaesth. 2013;110:545–553.
        64. Forget P, Lois F, Kartheuser A, Leonard D, Remue C, De Kock M. The concept of titration can be transposed to fluid management. but does is change the volumes? Randomised trial on pleth variability index during fast-track colonic surgery. Curr Clin Pharmacol. 2013;8:110–114.
        65. Challand C, Struthers R, Sneyd JR, et al. Randomized controlled trial of intraoperative goal-directed fluid therapy in aerobically fit and unfit patients having major colorectal surgery. Br J Anaesth. 2012;108:53–62.
        66. Brandstrup B, Svendsen PE, Rasmussen M, et al. Which goal for fluid therapy during colorectal surgery is followed by the best outcome: near-maximal stroke volume or zero fluid balance? Br J Anaesth. 2012;109:191–199.
        67. Cecconi M, Fasano N, Langiano N, et al. Goal-directed haemodynamic therapy during elective total hip arthroplasty under regional anaesthesia. Crit Care. 2011;15:R132.
        68. Jammer I, Ulvik A, Erichsen C, Lødemel O, Ostgaard G. Does central venous oxygen saturation-directed fluid therapy affect postoperative morbidity after colorectal surgery? A randomized assessor-blinded controlled trial. Anesthesiology. 2010;113:1072–1080.
        69. Forget P, Lois F, de Kock M. Goal-directed fluid management based on the pulse oximeter-derived pleth variability index reduces lactate levels and improves fluid management. Anesth Analg. 2010;111:910–914.
        70. Benes J, Chytra I, Altmann P, et al. Intraoperative fluid optimization using stroke volume variation in high risk surgical patients: results of prospective randomized study. Crit Care. 2010;14:R118.
        71. Harten J, Crozier JE, McCreath B, et al. Effect of intraoperative fluid optimisation on renal function in patients undergoing emergency abdominal surgery: a randomised controlled pilot study (ISRCTN 11799696). Int J Surg. 2008;6:197–204.
          72. Noblett SE, Snowden CP, Shenton BK, Horgan AF. Randomized clinical trial assessing the effect of Doppler-optimized fluid management on outcome after elective colorectal resection. Br J Surg. 2006;93:1069–1076.
          73. Pearse R, Dawson D, Fawcett J, Rhodes A, Grounds RM, Bennett ED. Early goal-directed therapy after major surgery reduces complications and duration of hospital stay. A randomised, controlled trial [ISRCTN38797445]. Crit Care. 2005;9:R687–R693.
          74. Wakeling HG, McFall MR, Jenkins CS, et al. Intraoperative oesophageal Doppler guided fluid management shortens postoperative hospital stay after major bowel surgery. Br J Anaesth. 2005;95:634–642.
          75. Gan TJ, Soppitt A, Maroof M, et al. Goal-directed intraoperative fluid administration reduces length of hospital stay after major surgery. Anesthesiology. 2002;97:820–826.
          76. Conway DH, Mayall R, Abdul-Latif MS, Gilligan S, Tackaberry C. Randomised controlled trial investigating the influence of intravenous fluid titration using oesophageal Doppler monitoring during bowel surgery. Anaesthesia. 2002;57:845–849.
          77. Valentine RJ, Duke ML, Inman MH, et al. Effectiveness of pulmonary artery catheters in aortic surgery: a randomized trial. J Vasc Surg. 1998;27:203–211.
          78. Sinclair S, James S, Singer M. Intraoperative intravascular volume optimisation and length of hospital stay after repair of proximal femoral fracture: randomised controlled trial. BMJ. 1997;315:909–912.
          79. Mayer J, Boldt J, Mengistu AM, Röhm KD, Suttner S. Goal-directed intraoperative therapy based on autocalibrated arterial pressure waveform analysis reduces hospital stay in high-risk surgical patients: a randomized, controlled trial. Crit Care. 2010;14:R18.
          80. Strunden MS, Heckel K, Goetz AE, Reuter DA. Perioperative fluid and volume management: physiological basis, tools and strategies. Ann Intensive Care. 2011;1:2.
          81. Marik PE. Perioperative hemodynamic optimization: a revised approach. J Clin Anesth. 2014;26:500–505.
          82. Voldby AW, Brandstrup B. Fluid therapy in the perioperative setting-a clinical review. J Intensive Care. 2016;4:27.
          83. Myburgh JA, Finfer S, Bellomo R, et al.; CHEST Investigators; Australian and New Zealand Intensive Care Society Clinical Trials Group. Hydroxyethyl starch or saline for fluid resuscitation in intensive care. N Engl J Med. 2012;367:1901–1911.
          84. Perner A, Haase N, Guttormsen AB, et al.; 6S Trial Group; Scandinavian Critical Care Trials Group. Hydroxyethyl starch 130/0.42 versus Ringer’s acetate in severe sepsis. N Engl J Med. 2012;367:124–134.
          85. Gattas DJ, Dan A, Myburgh J, Billot L, Lo S, Finfer S; CHEST Management Committee. Fluid resuscitation with 6 % hydroxyethyl starch (130/0.4 and 130/0.42) in acutely ill patients: systematic review of effects on mortality and treatment with renal replacement therapy. Intensive Care Med. 2013;39:558–568.
          86. Martin C, Jacob M, Vicaut E, Guidet B, Van Aken H, Kurz A. Effect of waxy maize-derived hydroxyethyl starch 130/0.4 on renal function in surgical patients. Anesthesiology. 2013;118:387–394.
          87. Gillies MA, Habicher M, Jhanji S, et al. Incidence of postoperative death and acute kidney injury associated with i.v. 6% hydroxyethyl starch use: systematic review and meta-analysis. Br J Anaesth. 2014;112:25–34.
          88. Miller TE, Raghunathan K, Gan TJ. State-of-the-art fluid management in the operating room. Best Pract Res Clin Anaesthesiol. 2014;28:261–273.
          89. Hiltebrand LB, Kimberger O, Arnberger M, Brandt S, Kurz A, Sigurdsson GH. Crystalloids versus colloids for goal-directed fluid therapy in major surgery. Crit Care. 2009;13:R40.
          90. Kimberger O, Arnberger M, Brandt S, et al. Goal-directed colloid administration improves the microcirculation of healthy and perianastomotic colon. Anesthesiology. 2009;110:496–504.
          91. Aya HD, Ster IC, Fletcher N, Grounds RM, Rhodes A, Cecconi M. Pharmacodynamic analysis of a fluid challenge. Crit Care Med. 2015;44:880–891.
          92. Chappell D, Jacob M, Hofmann-Kiefer K, Conzen P, Rehm M. A rational approach to perioperative fluid management. Anesthesiology. 2008;109:723–740.
          93. Bartha E, Arfwedson C, Imnell A, Kalman S. Towards individualized perioperative, goal-directed haemodynamic algorithms for patients of advanced age: observations during a randomized controlled trial (NCT01141894). Br J Anaesth. 2016;116:486–492.
          94. Hanley JA. Receiver operating characteristic (ROC) methodology: the state of the art. Crit Rev Diagn Imaging. 1989;29:307–335.
          95. 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;37:2642–2647.
          96. Zhang Z, Lu B, Sheng X, Jin N. Accuracy of stroke volume variation in predicting fluid responsiveness: a systematic review and meta-analysis. J Anesth. 2011;25:904–916.
          97. Mahjoub Y, Lejeune V, Muller L, et al. Evaluation of pulse pressure variation validity criteria in critically ill patients: a prospective observational multicentre point-prevalence study. Br J Anaesth. 2014;112:681–685.
          98. Cannesson M, Le Manach Y, Hofer CK, et al. Assessing the diagnostic accuracy of pulse pressure variations for the prediction of fluid responsiveness: a “gray zone” approach. Anesthesiology. 2011;115:231–241.
          99. Biais M, Larghi M, Henriot J, de Courson H, Sesay M, Nouette-Gaulain K. End-expiratory occlusion test predicts fluid responsiveness in patients with protective ventilation in the operating room. Anesth Analg. 2017;125:1889–1895.

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