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Targeting Oliguria Reversal in Goal-Directed Hemodynamic Management Does Not Reduce Renal Dysfunction in Perioperative and Critically Ill Patients

A Systematic Review and Meta-Analysis

Egal, Mohamud MD*; Erler, Nicole S.†‡; de Geus, Hilde R. H. MD, PhD*; van Bommel, Jasper MD, PhD*; Groeneveld, A. B. Johan MD, PhD, FCCP, FCCM*

doi: 10.1213/ANE.0000000000001027
Critical Care, Trauma, and Resuscitation: Research Report

BACKGROUND: We investigated whether resuscitation protocols to achieve and maintain urine output above a predefined threshold—including oliguria reversal as a target––prevent acute renal failure (ARF).

METHODS: We performed a systematic review and meta-analysis using studies found by searching MEDLINE, EMBASE, and references in relevant reviews and articles. We included all studies that compared “conventional fluid management” (CFM) with “goal-directed therapy” (GDT) using cardiac output, urine output, or oxygen delivery parameters and reported the occurrence of ARF in critically ill or surgical patients. We divided studies into groups with and without oliguria reversal as a target for hemodynamic optimization. We calculated the combined odds ratio (OR) and 95% confidence intervals (CIs) using random-effects meta-analysis.

RESULTS: We based our analyses on 28 studies. In the overall analysis, GDT resulted in less ARF than CFM (OR, 0.58; 95% CI, 0.44–0.76; P < 0.001; I2 = 34.3%; n = 28). GDT without oliguria reversal as a target resulted in less ARF (OR, 0.45; 95% CI, 0.34–0.61; P < 0.001; I2 = 7.1%; n = 7) when compared with CFM with oliguria reversal as a target. The studies comparing GDT with CFM in which the reversal of oliguria was targeted in both or in neither group did not provide enough evidence to conclude a superiority of GDT (targeting oliguria reversal in both protocols: OR, 0.63; 95% CI, 0.36–1.10; P = 0.09; I2 = 48.6%; n = 9, and in neither protocol: OR, 0.66; 95% CI, 0.37–1.16; P = 0.14; I2 = 20.2%; n = 12).

CONCLUSIONS: Current literature favors targeting circulatory optimization by GDT without targeting oliguria reversal to prevent ARF. Future studies are needed to investigate the hypothesis that targeting oliguria reversal does not prevent ARF in critically ill and surgical patients.

Published ahead of print October 26, 2015

From the Departments of *Intensive Care, Biostatistics, and Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.

Accepted for publication August 14, 2015.

Published ahead of print October 26, 2015

Funding: Institutional.

The authors declare no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website.

Reprints will not be available from the authors.

Address correspondence to Mohamud Egal, MD, Department of Intensive Care, Erasmus MC, University Medical Center Rotterdam, Room H-602, Erasmus Medical Centre, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. Address e-mail to

IV fluids are administered to compensate for losses during or after surgery and to increase intravascular volume in hypovolemic patients. Textbooks often recommend using urine output to help guide fluid therapy.1–3 Oliguria is often viewed as a marker of decreased kidney and organ perfusion and as a trigger t o administer fluids to prevent acute renal failure (ARF) and organ damage. However, oliguria may not be caused solely by a suboptimal hemodynamic status but may be attributed to medications or hormonal effects, which reduce its value as a fluid-loading criterion. Large observational studies have found no relation between intraoperative urine output and subsequent ARF.4–6 Even in the critically ill, oliguria lacks cannot predict subsequent ARF.7 Thus, fluids may be administered unnecessarily, which in turn could lead to fluid overloading. Several studies suggest that excess fluid administration is associated with adverse clinical outcomes in patients with ARF.8–11

Goal-directed therapy (GDT) strategies in the perioperative and critical care settings target specific hemodynamic parameters related to cardiac output or oxygen delivery along with intensive monitoring. In high-risk surgical or critically ill patients, such strategies are increasingly being used to guide fluid therapy and have been associated with less morbidity and mortality.12–16 This effect may even be greater when hemodynamic targets are not achieved by additional fluid administration but with inotropic agents.16

We hypothesized that including oliguria reversal as a target—defined as achieving and maintaining urine output above a predefined threshold—does not prevent ARF, especially when used alongside cardiac output or oxygen delivery-related hemodynamic parameters. In this systematic review and meta-analysis, we focused on whether including oliguria reversal as a target in the protocols of studies comparing GDT strategies with conventional fluid management (CFM) strategies reduced the incidence of renal dysfunction in surgical and critically ill patients.

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We performed a systematic literature search to identify all studies comparing GDT with CFM that reported ARF. We excluded all animal studies, articles not in English, studies unavailable as full text, and studies with pediatric patients.

We defined GDT as any hemodynamic optimization strategy in the perioperative and critical care setting using parameters related to cardiac output and oxygen delivery, regardless of the device or method used to measure these parameters, and either exclusively or in combination with the classical parameters such as blood pressure, heart rate, and urine output. To minimize the bias of protocol effect, the hemodynamic targets used in CFM had to be clearly defined. Because of variability in the definition of renal dysfunction in the studies we evaluated and a very specific definition for the term acute kidney injury defined by the Acute Dialysis Quality Initiative,17 we used the term ARF to include a relative or absolute increase in serum creatinine, need for renal replacement therapy, any severity and duration of oliguria, or any combination of the previous, as defined in the selected studies. We defined targeting oliguria reversal as using fluids or vasoactive medication to achieve and maintain urine output above a previously defined threshold. The use of diuretics to increase urine output was not considered a resuscitation method to reverse oliguria because of the difficulty in using urine output to assess oxygen delivery or blood flow after the administration of diuretics. We used urine output thresholds as set by the selected studies.

We accessed the MEDLINE (1966 to present) database via PubMed and the EMBASE (1980 to present) database (last search March 2014) with no limits for publication date or language (Table 1, Supplemental Digital Content 1,, which shows the search strategy for the MEDLINE database, and a similar strategy was used to search the EMBASE database). We used the “related articles” function in PubMed to identify eligible studies that were not found by the main search queries. References of studies considered for inclusion and references of review articles were hand-searched for eligible studies. We also used the “cited reference search” function of Web of Knowledge (Thomson Reuters) to find potential studies. We screened the title and abstract of the studies found in the search to see whether GDT was compared with CFM and whether the occurrence of ARF was reported. In case of doubt, we screened the full-text article. Using a predefined study form, one author scored the following variables: total study population, group sizes, type of patients, definition of GDT and CFM, treatment targets in both groups, devices used in GDT to assess hemodynamic parameters, timing of intervention, fluid intake and balance during and after the study period, definition of ARF used, and development of ARF. Once included, the studies were scored according to the Jadad scale on the following: reporting whether the study was randomized and by which method; the method and appropriateness of blinding used; and adequate reporting of withdrawals and dropouts.18

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Statistical Analysis

All included studies were grouped depending on whether oliguria reversal was included as a target in the study protocol. Studies comparing GDT and CFM where neither treatment protocol involved oliguria reversal were designated as GDT− versus CFM−, studies comparing GDT without oliguria reversal as a target with CFM with oliguria reversal as a target as GDT− versus CFM, and studies comparing GDT with CFM where both treatment arms had oliguria reversal as a target as GDT+ versus CFM+. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated for each study based on their reported treatment arm, specific sample size, and observed frequencies of ARF.

In the primary analysis, we compared the number of patients with ARF in the 2 treatment arms in all studies as well as separately for each of the 3 study protocol groups (GDT− versus CFM−, GDT− versus CFM+, GDT− versus CFM−) using random-effects meta-analysis. To gain further insight into the role of the treatment period in which the protocol was used (pre-, versus intra- or postoperative), we meta-analyzed studies in which the treatment protocol was used during the preoperative or intraoperative setting separately from those in which the protocol was used during the postoperative or intensive care unit (ICU) setting in a secondary analysis. Studies in which the treatment protocol was used during both periods were included in both analyses. Therefore, we performed a sensitivity analysis in which only studies were included that used the treatment protocols during the postoperative and ICU settings only.

To investigate the potential sources of bias, we also identified subgroups of studies, which were defined based on ARF definition, type of monitoring, differences in fluid intake between GDT and CFM, year of publication, and Jadad score. We compared the ARF definition with the Risk, Injury, Failure, Loss of kidney function, and End-stage kidney disease (RIFLE) and Acute Kidney Injury Network (AKIN) criteria and assigned the studies to 1 of the 3 ARF subgroups: studies defining ARF using RIFLE and AKIN criteria (“exact”), studies defining ARF using a relative increase in serum creatinine near 50% or an absolute serum creatinine increase near 0.3 mg/dL (27 μmol/L) (“similar”), and studies using an absolute cutoff value for serum creatinine or the need for renal replacement therapy without other criteria (“other”). The categories for the type of monitoring were “invasive monitoring,” which included studies using pulmonary artery catheters or esophageal Doppler to guide therapy, “noninvasive,” which included studies using arterial waveform or pulse contour analysis devices to guide therapy, and “metabolic indices,” which included studies using oxygen saturation or lactate to guide therapy without using devices from the 2 other groups. Difference in fluid intake between GDT and CFM was specified as 1 of the 3 categories: studies in which more fluids were infused in GDT than in CFM (“more”), studies in which similar volumes of fluids were infused in GDT and in CFM (“similar”), and studies in which less fluids were infused in GDT than in CFM (“less”). In addition, we created a subgroup including all studies in which more colloids were infused in GDT than in CFM. According to the year of publication, studies were divided into 2 subgroups: published before 2004 and published in or after 2004. The year 2004 was chosen as the cutoff point because the consensus definition and RIFLE criteria by the Acute Dialysis Quality Initiative Group were published in that year. Lastly, studies with a Jadad score >2 formed another subgroup.

All meta-analyses were conducted as random-effects meta-analysis in R (version 3.1.3)19 using the package metafor (version 1.9.5).20 Specifically, the Sidik-Jonkman estimator21 was used in combination with the Knapp and Hartung adjustment22 to get better estimates of the heterogeneity variance. In studies with a count of zero in one of the treatment arms, 0.5 was added to all frequencies of that study. Heterogeneity between studies was analyzed using the I2 statistic and interpreted using thresholds as defined in the Cochrane Handbook.23 Funnel plots were analyzed visually to detect possible publication bias. In the subgroup analysis, pooled OR and CI were calculated without considering heterogeneity between studies, and P values were determined using the Fisher exact test. ORs were considered statistically significant when their 95% CI did not include 1.00 and the corresponding P value was <0.05.

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Table 1

Table 1

Table 2

Table 2

Table 3

Table 3

Table 4

Table 4

Figure 1

Figure 1

Our search strategy resulted in 1062 articles, of which 588 remained after excluding duplicates (Fig. 1). Of those, 525 were animal studies, pediatric studies, not in English, not available as full-text, or compared different fluid types and were excluded. After reading all full-text articles for eligibility, we excluded another 34 studies because either the hemodynamic parameters were not defined in the conventional arm or no data on ARF were presented. One study, which did report ARF,24 was excluded because it was not possible to distinguish new occurrences of ARF in each group from those with ARF at randomization. Table 1 shows the characteristics of the resulting 28 included studies, and Table 2 shows the hemodynamic monitoring used in each of the selected studies. Twelve studies25–36 did not include oliguria reversal as a target in either of the treatment protocols, GDT and CFM, and were allocated to the GDT− versus CFM− group; 7 studies in which only the CFM protocol included oliguria reversal were allocated to the GDT− versus CFM+ group37–43; and 9 studies that included oliguria reversal as a target in both the GDT and the CFM protocol were assigned to the GDT+ versus CFM+ group.44–52 We did not find studies comparing GDT with oliguria reversal as a target with CFM without oliguria reversal as a target, studies comparing GDT with and without oliguria reversal as a target, or studies comparing CFM with and without oliguria reversal as a target. Eight of the 28 studies had a score of <3 on the Jadad scale (Table 3). The allocation of the studies to the subgroups is shown in Table 4. None of the selected studies reported the use of nephrotoxic medication, and only 5 reported the use of diuretics for reasons other than oliguria reversal.36,40,47,49,52

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Primary Analysis

Figure 2

Figure 2

Meta-analysis of all 28 studies showed that overall, GDT was associated with a lower occurrence of ARF than CFM (OR, 0.58; 95% CI, 0.44–0.76; P < 0.001; I2 = 34.3%; n = 28). In the GDT− versus CFM+ group, patients who received GDT were less likely to develop ARF than those treated with CFM (OR, 0.45; 95% CI, 0.34–0.61; P < 0.001; I2 = 7.1%; n = 7). The studies in the other 2 protocol groups did not provide enough evidence to conclude a superiority of GDT compared with CFM. Forest plots of the primary analysis are shown in Figure 2. The heterogeneity in this analysis ranged from low to moderate. The funnel plot of the overall analysis showed no marked asymmetry, suggesting the absence of publication bias (Figure 1, Supplemental Digital Content 2,, showing the funnel plot of studies reporting the occurrence of ARF when comparing GDT with CFM).

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Secondary Analysis

Results from the meta-analysis of those studies that targeted oliguria reversal during the pre- and intraoperative setting are shown in Figure 3. Here, the combined analysis showed that GDT was associated with a lower occurrence of ARF compared with CFM (OR, 0.62; 95% CI, 0.42–0.89; P = 0.01; I2 = 25.1%; n = 21). All 3 protocol group-specific meta- analyses estimated ORs smaller than 1; however, none of the estimates were significantly different from 1.00.

Figure 3

Figure 3

Meta-analysis of the studies that used fluid management protocols during the postoperative and ICU setting showed that GDT reduced the number of ARF cases (OR, 0.56; 95% CI, 0.39–0.80; P = 0.004, I2 = 42.6%; n = 14). The corresponding forest plot is displayed in Figure 4. Here, the OR in the GDT− versus CFM+ group was significantly smaller than 1.00 (OR, 0.46; 95% CI, 0.31–0.70; P = 0.015; I2 = 1.2%; n = 3), whereas results in the other 2 groups were inconclusive. Funnel plots for the secondary analyses showed no asymmetry, and hence suggested no publication bias (Figures 2 and 3, Supplemental Digital Content 3 and 4, and, showing the funnel plots corresponding to the secondary analysis).

Figure 4

Figure 4

Seven studies28,37,39,43,46,49,51 in which the treatment protocol was first used in the postoperative or the ICU setting, and not in the pre- or intraoperative setting, were included in the sensitivity analysis. Here, meta-analysis showed that GDT resulted in less ARF than CFM (OR, 0.58; 95% CI, 0.37–0.90; P = 0.02; I2 = 30.6%; n = 7; Figure 4, Supplemental Digital Content 5,, which show the forest plot of the sensitivity analysis).

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Additional Analysis

Table 5

Table 5

Because we did not find any studies directly comparing targeting oliguria reversal with not targeting oliguria reversal in each treatment, we conducted additional, pooled analyses based on the subgroups of studies described earlier (Table 4). The results from this analysis are reported in detail in Table 5.

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In the present study, we performed meta-analyses on 28 studies and found that GDT is superior to CFM with regard to preventing ARF. This effect was the strongest in studies that included oliguria reversal as a target in CFM but not in GDT. Although the comparison of GDT with CFM where both treatments included or excluded oliguria reversal as a target suggested superiority of GDT, available evidence was inadequate to allow a definite conclusion. This lack of clarity may partially be because of the small number of studies that were available for analysis.

In the additional, pooled analysis (Table 5), GDT and CFM strategies targeting oliguria reversal increased the odds of developing ARF when compared with GDT and CFM strategies not targeting oliguria reversal. This finding may partially explain the larger difference between treatments observed in the primary analysis of GDT− versus CFM+. We found that when GDT− and CFM− groups were compared, the effect on ARF was not different than between GDT+ and CFM+ groups. When combined with the lack of benefit in targeting oliguria reversal in the additional pooled analysis, this difference suggests that targeting oliguria reversal may not reduce the incidence of ARF when compared with strategies that do not target oliguria reversal. Our data support the hypothesis that preventing ARF may not be achieved by striving toward a predefined urine output target.

Several reasons are possible for why urine output may have limited effectiveness as a hemodynamic management goal. Urine output is a parameter that takes time to change and is influenced by factors other than the hemodynamic status. Thus, oliguria can be because of causes that are unaffected by fluid administration or have already been resolved. Therefore, patients may be at risk for fluid overload because of superfluous fluid administration targeted only at urine output. However, strategies that do not target oliguria reversal may limit fluid overload by more precisely targeting variables related to cardiac output or oxygen delivery. Once the hemodynamic status has been optimized, any subsequent occurrence of oliguria is unlikely to be because of hemodynamic causes, favoring the exclusion of oliguria reversal as a target.

GDT patients received a similar or larger volume of fluids than CFM patients in most of the included studies (Table 4); and even in the GDT− versus CFM+ group, most studies used an equal or larger fluid volume in GDT than in CFM. However, in the subset of trials where GDT resulted in less fluid administered than in CFM, targeting oliguria reversal had a larger impact in the CFM than in the GDT group. These data suggest that in GDT trials that focus on limiting fluid administration, targeting oliguria reversal may play a role. For example, additional fluid resuscitation targeted at increasing urine output may result in hypervolemia and subsequent ARF. In contrast, when GDT results in equal or larger fluid volumes than CFM to achieve the predefined hemodynamic targets, any effects of targeting oliguria reversal on the occurrence of ARF may be relatively minor, possibly because of the volume of fluids already administered.

On the basis of our findings, GDT is better suited than CFM for preventing ARF in the preoperative or intraoperative setting. Furthermore, GDT might reduce ARF in the postoperative or ICU setting, but when we excluded studies in which GDT and CFM were already started during the preoperative or intraoperative setting, the data were too limited to draw a definite conclusion. Similar to our findings, the meta-analysis performed by Brienza et al.12 reported that patients treated with GDT in the postoperative setting had less ARF. However, their meta-analysis differed from ours in several ways. First, they assigned studies according to the commencement of hemodynamic optimization. Second, they pooled the intraoperative and postoperative commencement into one analysis.12 Finally, they excluded studies with late optimization (i.e., >12 hours postoperative or after the onset of organ failure). It has been suggested that intraoperative and postoperative optimization should be separated because of differences in etiology and hemodynamic goals.53 Consequently, although our study supports the findings of Brienza et al.12 for the early postoperative phase, our findings also suggest that GDT may prevent ARF when used during the late postoperative phase or in the ICU.

Although we found that GDT was associated with less ARF when oliguria reversal was not included as a target, the effects of such strategies on mortality remain unclear. Because of the relatively low numbers of available studies reporting both ARF and mortality, we considered the risk of selection bias too high and therefore did not perform analyses to investigate the effects of targeting oliguria reversal on mortality.

Our study has several limitations. First, as shown in Table 1, not all the included studies shared the same definition for ARF. Although the heterogeneity found in most of the analyses—as assessed by the I2 statistic—is low to moderate, most of the included studies are likely to underestimate the occurrence of ARF. Most definitions included an increase in serum creatinine values, a form of oliguria, some form of renal replacement therapy, or a combination of these criteria and thus are quite similar to the RIFLE or AKIN criteria. However, because of the relatively short observation periods, the relatively high cutoff points for serum creatinine, or the need for renal replacement therapy in most studies, smaller increases in serum creatinine may have been overlooked. These small increases are clinically relevant, because of the associated increase in adverse outcomes,54 and are one of the reasons why the AKIN included small increments in serum creatinine in the RIFLE criteria.55 We found that the definition used for ARF affects the relation between ARF and targeting oliguria reversal. Studies using the RIFLE and AKIN criteria identified less ARF possibly related to targeting oliguria reversal than using the outdated definitions. It is possible that the RIFLE and AKIN criteria diagnosed more patients with less severe ARF, which would have been missed by the outdated definitions.

Second, the hemodynamic parameters targeted in the GDT protocols and the methods used to evaluate them varied greatly among the included studies (Table 2). This variance was partly because of the large timespan between some studies, which has led to pulmonary artery catheters and esophageal Doppler monitoring being replaced by calibrated or uncalibrated arterial pressure-derived continuous cardiac output devices. Our subgroup analyses suggest that although all these methods assess parameters related to cardiac output or oxygen delivery, the differences between these devices and their practical limitations could have affected patient management and treatment options. Even when using similar devices, the correct interpretation of these indices is also important. Starting treatments based on an erroneous interpretation of hemodynamic parameters could result in more harm to patients in terms of ARF or other outcomes rather than the intended benefit. Furthermore, the potential change in the risk of ARF from earlier studies might also be attributable to improvements in conventional health care practice throughout the decades.

Another limitation of our meta-analysis is the different underlying conditions in the included studies. It is likely, for example, that surgical and septic patients differ regarding goals for hemodynamic optimization. Nevertheless, achieving an optimal hemodynamic state through intensive monitoring of cardiac output or oxygen delivery-derived parameters should result in a similar benefit, despite the underlying conditions. Thus, once hemodynamic status has been optimized, the development of ARF should mostly be determined by risk factors associated with the underlying condition. Furthermore, any additional fluids given after the hemodynamic status has been optimized can lead to deleterious effects because of fluid overload, which in turn increases the risk of developing ARF.

Finally, the methods used to optimize hemodynamic status differed among the studies. As shown in Table 2, the use of vasopressors and inotropic drugs as well as the type of fluid was not consistent. Colloids such as hetastarch, for example, have been associated with an increased risk for acute kidney injury.56,57 In most of the selected studies, colloids were used as the primary intervention fluid to achieve and maintain hemodynamic goals, including urine output. Although unlikely, it is possible that asymmetry in colloid use between groups may have affected our results. In recent years, an association between hyperchloremic solutions and an increased risk for acute kidney injury has also been suggested.58,59 This effect also could have influenced our findings because of differences in fluid compositions used within or between studies. Furthermore, it is important to note that standard random-effects meta-analysis methods may not accurately estimate the between-study variation when only few studies are included in the analysis. We attempted to minimize this problem by using a more robust estimator; nevertheless, results from analyses with only few studies should be interpreted with great care.

Collectively, our data favor targeting circulatory optimization by GDT without targeting oliguria reversal to prevent ARF. This effect of GDT on ARF is present even during the perioperative period or in the ICU. Our findings support the hypothesis that ARF is not prevented by striving toward a predefined urine output target. However, randomized controlled trials are needed to investigate whether targeting oliguria reversal has a deleterious effect on the occurrence of ARF and whether—as our findings suggest—resuscitation protocols that prioritize cardiac output and oxygen delivery are better able to reduce the risk of ARF than those including oliguria reversal as a target.

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Name: Mohamud Egal, MD.

Contribution: This author helped design the study, collected data, analyzed the data, and prepared the manuscript.

Attestation: Mohamud Egal attests to the integrity of the original data and the analysis reported in this manuscript and approved the final manuscript.

Name: Nicole S. Erler.

Contribution: This author analyzed the data and prepared the manuscript.

Attestation: Nicole S. Erler attests to the analysis reported in this manuscript and approved the final manuscript.

Name: Hilde R. H. de Geus, MD, PhD.

Contribution: This author helped design the study and prepared the manuscript.

Attestation: Hilde R. H. de Geus approved the final manuscript.

Name: Jasper van Bommel, MD, PhD.

Contribution: This author helped design the study, analyzed the data, and prepared the manuscript.

Attestation: Jasper van Bommel is the archival author and approved the final manuscript.

Name: A. B. Johan Groeneveld, MD, PhD, FCCP, FCCM.

Contribution: This author helped design the study, collected data, data analysis, and prepared the manuscript.

Attestation: A. B. Johan Groeneveld attests to the integrity of the original data and the analysis reported in this manuscript and approved the final manuscript.

This manuscript was handled by: Avery Tung, MD.

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1. Morgan GE, Mikhail MS, Murray MJ Clinical Anesthesiology. 20064th ed New York, NY; London, UK Lange Medical Books/McGraw Hill, Medical Publishing Division
2. Marino PL, Sutin KM The ICU Book. 20073rd ed Philadelphia, PA; London, UK Lippincott Williams & Wilkins
3. Dellinger RP, Levy MM, Rhodes A, Annane D, Gerlach H, Opal SM, Sevransky JE, Sprung CL, Douglas IS, Jaeschke R, Osborn TM, Nunnally ME, Townsend SR, Reinhart K, Kleinpell RM, Angus DC, Deutschman CS, Machado FR, Rubenfeld GD, Webb SA, Beale RJ, Vincent JL, Moreno RSurviving Sepsis Campaign Guidelines Committee including the Pediatric Subgroup. . Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit Care Med. 2013;41:580–637
4. Kheterpal S, Tremper KK, Englesbe MJ, O’Reilly M, Shanks AM, Fetterman DM, Rosenberg AL, Swartz RD. Predictors of postoperative acute renal failure after noncardiac surgery in patients with previously normal renal function. Anesthesiology. 2007;107:892–902
5. Brito DJ, Nina VJ, Nina RV, Figueiredo Neto JA, Oliveira MI, Salgado JV, Lages JS, Salgado Filho N. Prevalence and risk factors for acute renal failure in the postoperative of coronary artery bypass grafting. Rev Bras Cir Cardiovasc. 2009;24:297–304
6. Ho J, Reslerova M, Gali B, Nickerson PW, Rush DN, Sood MM, Bueti J, Komenda P, Pascoe E, Arora RC, Rigatto C. Serum creatinine measurement immediately after cardiac surgery and prediction of acute kidney injury. Am J Kidney Dis. 2012;59:196–201
7. Prowle JR, Liu YL, Licari E, Bagshaw SM, Egi M, Haase M, Haase-Fielitz A, Kellum JA, Cruz D, Ronco C, Tsutsui K, Uchino S, Bellomo R. Oliguria as predictive biomarker of acute kidney injury in critically ill patients. Crit Care. 2011;15:R172
8. Bagshaw SM, Bellomo R, Kellum JA. Oliguria, volume overload, and loop diuretics. Crit Care Med. 2008;36:S172–8
9. Payen D, de Pont AC, Sakr Y, Spies C, Reinhart K, Vincent JLSepsis Occurrence in Acutely Ill Patients (SOAP) Investigators. . A positive fluid balance is associated with a worse outcome in patients with acute renal failure. Crit Care. 2008;12:R74
10. Bouchard J, Soroko SB, Chertow GM, Himmelfarb J, Ikizler TA, Paganini EP, Mehta RLProgram to Improve Care in Acute Renal Disease (PICARD) Study Group. . Fluid accumulation, survival and recovery of kidney function in critically ill patients with acute kidney injury. Kidney Int. 2009;76:422–7
11. Bellomo R, Cass A, Cole L, Finfer S, Gallagher M, Lee J, Lo S, McArthur C, McGuiness S, Norton R, Myburgh J, Scheinkestel C, Su SRENAL Replacement Therapy Study Investigators. . An observational study fluid balance and patient outcomes in the Randomized Evaluation of Normal vs. Augmented Level of Replacement Therapy trial. Crit Care Med. 2012;40:1753–60
12. Brienza N, Giglio MT, Marucci M, Fiore T. Does perioperative hemodynamic optimization protect renal function in surgical patients? A meta-analytic study. Crit Care Med. 2009;37:2079–90
13. Giglio MT, Marucci M, Testini M, Brienza N. Goal-directed haemodynamic therapy and gastrointestinal complications in major surgery: a meta-analysis of randomized controlled trials. Br J Anaesth. 2009;103:637–46
14. Rahbari NN, Zimmermann JB, Schmidt T, Koch M, Weigand MA, Weitz J. Meta-analysis of standard, restrictive and supplemental fluid administration in colorectal surgery. Br J Surg. 2009;96:331–41
15. Dalfino L, Giglio MT, Puntillo F, Marucci M, Brienza N. Haemodynamic goal-directed therapy and postoperative infections: earlier is better. A systematic review and meta-analysis. Crit Care. 2011;15:R154
16. Prowle JR, Chua HR, Bagshaw SM, Bellomo R. Clinical review: volume of fluid resuscitation and the incidence of acute kidney injury—a systematic review. Crit Care. 2012;16:230
17. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky PAcute Dialysis Quality Initiative Workgroup. . Acute renal failure—definition, outcome measures, animal models, fluid therapy and information technology needs: the Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit Care. 2004;8:R204–12
18. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, McQuay HJ. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17:1–12
19. R Core Team. R: A Language and Environment for Statistical Computing. 2015 Vienna, Austria R Foundation for Statistical Computing
20. Viechtbauer W. Conducting meta-analysis in R with the metafor package. J Stat Soft. 2010;36:1–48
21. Sidik K, Jonkman JN. A comparison of heterogeneity variance estimators in combining results of studies. Stat Med. 2007;26:1964–81
22. Knapp G, Hartung J. Improved tests for a random effects meta-regression with a single covariate. Stat Med. 2003;22:2693–710
23. Deeks J, Higgins J, Altman D 9.5.2 Identifying and Measuring Heterogeneity Cochrane Handbook for Systematic Reviews of Interventions. 2011 Version 5-1-0: The Cochrane Collaboration
24. Rhodes A, Cusack RJ, Newman PJ, Grounds RM, Bennett ED. A randomised, controlled trial of the pulmonary artery catheter in critically ill patients. Intensive Care Med. 2002;28:256–64
25. Berlauk JF, Abrams JH, Gilmour IJ, O’Connor SR, Knighton DR, Cerra FB. Preoperative optimization of cardiovascular hemodynamics improves outcome in peripheral vascular surgery. A prospective, randomized clinical trial. Ann Surg. 1991;214:289–97
26. Valentine RJ, Duke ML, Inman MH, Grayburn PA, Hagino RT, Kakish HB, Clagett GP. Effectiveness of pulmonary artery catheters in aortic surgery: a randomized trial. J Vasc Surg. 1998;27:203–11
27. Wilson J, Woods I, Fawcett J, Whall R, Dibb W, Morris C, McManus E. Reducing the risk of major elective surgery: randomised controlled trial of preoperative optimisation of oxygen delivery. BMJ. 1999;318:1099–103
28. Pölönen P, Ruokonen E, Hippeläinen M, Pöyhönen M, Takala J. A prospective, randomized study of goal-oriented hemodynamic therapy in cardiac surgical patients. Anesth Analg. 2000;90:1052–9
29. Bonazzi M, Gentile F, Biasi GM, Migliavacca S, Esposti D, Cipolla M, Marsicano M, Prampolini F, Ornaghi M, Sternjakob S, Tshomba Y. Impact of perioperative haemodynamic monitoring on cardiac morbidity after major vascular surgery in low risk patients. A randomised pilot trial. Eur J Vasc Endovasc Surg. 2002;23:445–51
30. Wakeling HG, McFall MR, Jenkins CS, Woods WG, Miles WF, Barclay GR, Fleming SC. Intraoperative oesophageal Doppler guided fluid management shortens postoperative hospital stay after major bowel surgery. Br J Anaesth. 2005;95:634–42
31. 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;111:910–4
32. Wenkui Y, Ning L, Jianfeng G, Weiqin L, Shaoqiu T, Zhihui T, Tao G, Juanjuan Z, Fengchan X, Hui S, Weiming Z, Jie-Shou L. Restricted peri-operative fluid administration adjusted by serum lactate level improved outcome after major elective surgery for gastrointestinal malignancy. Surgery. 2010;147:542–52
33. Cecconi M, Fasano N, Langiano N, Divella M, Costa MG, Rhodes A, Della Rocca G. Goal-directed haemodynamic therapy during elective total hip arthroplasty under regional anaesthesia. Crit Care. 2011;15:R132
34. 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;110:545–53
35. 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;57:178–88
36. Goepfert MS, Richter HP, Zu Eulenburg C, Gruetzmacher J, Rafflenbeul E, Roeher K, von Sandersleben A, Diedrichs S, Reichenspurner H, Goetz AE, Reuter DA. Individually optimized hemodynamic therapy reduces complications and length of stay in the intensive care unit: a prospective, randomized controlled trial. Anesthesiology. 2013;119:824–36
37. Bishop MH, Shoemaker WC, Appel PL, Meade P, Ordog GJ, Wasserberger J, Wo CJ, Rimle DA, Kram HB, Umali R. Prospective, randomized trial of survivor values of cardiac index, oxygen delivery, and oxygen consumption as resuscitation endpoints in severe trauma. J Trauma. 1995;38:780–7
38. Gan TJ, Soppitt A, Maroof M, el-Moalem H, Robertson KM, Moretti E, Dwane P, Glass PS. Goal-directed intraoperative fluid administration reduces length of hospital stay after major surgery. Anesthesiology. 2002;97:820–6
39. McKendry M, McGloin H, Saberi D, Caudwell L, Brady AR, Singer M. Randomised controlled trial assessing the impact of a nurse delivered, flow monitored protocol for optimisation of circulatory status after cardiac surgery. BMJ. 2004;329:258
40. Benes J, Chytra I, Altmann P, Hluchy M, Kasal E, Svitak R, Pradl R, Stepan M. Intraoperative fluid optimization using stroke volume variation in high risk surgical patients: results of prospective randomized study. Crit Care. 2010;14:R118
41. 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
42. 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;68:1065–70
43. ProCESS Investigators. . A randomized trial of protocol-based care for early septic shock. N Engl J Med. 2014;370:1689–93
44. Shoemaker WC, Appel PL, Kram HB, Waxman K, Lee TS. Prospective trial of supranormal values of survivors as therapeutic goals in high-risk surgical patients. Chest. 1988;94:1176–86
45. Boyd O, Grounds RM, Bennett ED. A randomized clinical trial of the effect of deliberate perioperative increase of oxygen delivery on mortality in high-risk surgical patients. JAMA. 1993;270:2699–707
46. Gattinoni L, Brazzi L, Pelosi P, Latini R, Tognoni G, Pesenti A, Fumagalli R. A trial of goal-oriented hemodynamic therapy in critically ill patients. SvO2 Collaborative Group. N Engl J Med. 1995;333:1025–32
47. Lobo SM, Salgado PF, Castillo VG, Borim AA, Polachini CA, Palchetti JC, Brienzi SL, de Oliveira GG. Effects of maximizing oxygen delivery on morbidity and mortality in high-risk surgical patients. Crit Care Med. 2000;28:3396–404
48. Donati A, Loggi S, Preiser JC, Orsetti G, Münch C, Gabbanelli V, Pelaia P, Pietropaoli P. Goal-directed intraoperative therapy reduces morbidity and length of hospital stay in high-risk surgical patients. Chest. 2007;132:1817–24
49. Kapoor PM, Kakani M, Chowdhury U, Choudhury M, Lakshmy, Kiran U. Early goal-directed therapy in moderate to high-risk cardiac surgery patients. Ann Card Anaesth. 2008;11:27–34
50. 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;113:1072–80
51. Jhanji S, Vivian-Smith A, Lucena-Amaro S, Watson D, Hinds CJ, Pearse RM. Haemodynamic optimisation improves tissue microvascular flow and oxygenation after major surgery: a randomised controlled trial. Crit Care. 2010;14:R151
52. Brandstrup B, Svendsen PE, Rasmussen M, Belhage B, Rodt SÅ, Hansen B, Møller DR, Lundbech LB, Andersen N, Berg V, Thomassen N, Andersen ST, Simonsen L. 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;109:191–9
53. Poeze M, Greve JW, Ramsay G. Goal-oriented haemodynamic therapy: a plea for a closer look at using peri-operative oxygen transport optimisation. Intensive Care Med. 2000;26:635–7
54. Lassnigg A, Schmidlin D, Mouhieddine M, Bachmann LM, Druml W, Bauer P, Hiesmayr M. Minimal changes of serum creatinine predict prognosis in patients after cardiothoracic surgery: a prospective cohort study. J Am Soc Nephrol. 2004;15:1597–605
55. Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C, Warnock DG, Levin AAcute Kidney Injury Network. . Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care. 2007;11:R31
56. Wiedermann CJ, Dunzendorfer S, Gaioni LU, Zaraca F, Joannidis M. Hyperoncotic colloids and acute kidney injury: a meta-analysis of randomized trials. Crit Care. 2010;14:R191
57. Mutter TC, Ruth CA, Dart AB. Hydroxyethyl starch (HES) versus other fluid therapies: effects on kidney function. Cochrane Database Syst Rev. 2013;7:CD007594
58. Shaw AD, Bagshaw SM, Goldstein SL, Scherer LA, Duan M, Schermer CR, Kellum JA. Major complications, mortality, and resource utilization after open abdominal surgery: 0.9% saline compared to Plasma-Lyte. Ann Surg. 2012;255:821–9
59. Yunos NM, Bellomo R, Hegarty C, Story D, Ho L, Bailey M. Association between a chloride-liberal vs chloride-restrictive intravenous fluid administration strategy and kidney injury in critically ill adults. JAMA. 2012;308:1566–72

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