Acute kidney injury (AKI) after orthotopic liver transplantation (OLT) is a common complication, with reported incidences ranging from 17% to 95%.1 The wide variability in reported AKI incidence after OLT is attributable, in part, to lack of a consensus definition for AKI.2 To address this issue, the Acute Dialysis Quality Initiative Group developed a consensus definition and classification system for AKI identified by the acronym RIFLE (Risk, Injury, Failure, Loss, and End Stage) that specifies the degree and duration of renal dysfunction. This classification system is based on changes in serum creatinine (or glomerular filtration rate) and/or changes in urine output.3 The RIFLE classification system has been validated as an outcome predictor, with worsening RIFLE class being associated with a progressive increase in mortality.4 In patients undergoing OLT, both RIFLE criteria class Injury and Failure result in increased length of hospitalization and in the case of Failure, increased mortality.5
The etiology of AKI after OLT is multifactorial. End-stage liver disease results in a hyperdynamic circulatory syndrome characterized by peripheral vasodilation, hypotension, and high cardiac output.6 Arterial hypotension and splanchnic vasodilation predispose to renal dysfunction through renal circulatory vasoconstriction and hypoperfusion.7 Perioperative risk factors associated with AKI after OLT include blood transfusion, intra- and postoperative hypotension, preoperative hypertension, elevated bilirubin levels, alcoholic cirrhosis, and length of surgery.8–11
The choice of fluid resuscitation in patients with end-stage liver disease may also play a role in AKI. Because hypoalbuminemia and low oncotic pressure cause IV fluids to diffuse into the interstitium, albumin has been the fluid of choice for intravascular volume resuscitation in liver transplantation at many centers. Albumin is a more potent plasma expander than crystalloid and has antioxidant and anti-inflammatory properties.12,13 Albumin has also reduced renal impairment in patients with cirrhosis and spontaneous bacterial peritonitis.14 Despite these observations, however, the Saline versus Albumin Fluid Evaluation Study, which compared the use of albumin to normal saline, demonstrated no difference in mortality and renal replacement therapy (RRT) in a large heterogeneous intensive care unit (ICU) population.15
Increasingly, evidence suggests that 6% hydroxyethyl starch (130/0.4) (henceforth referred to as HES) causes renal injury. The Crystalloid versus Hydroxyethyl Starch Trial (CHEST) prospectively randomized 7000 patients to hetastarch or normal saline and found a 21% relative (1.2% absolute) increase in need for RRT in patients receiving HES.16 A Dutch trial of 800 ICU patients with severe sepsis likewise found an increased likelihood of RRT in patients receiving HES versus Ringer’s acetate solution.17 These studies led the Food and Drug Administration to issue a warning in November 2013 that HES use increases the risk of mortality and renal injury requiring RRT in critically ill adult patients.18–20
At the study institution, the decision to deliver colloid to a transplant recipient is protocol driven. A team of anesthesiologists (5) use arterial-waveform analysis in addition to standard monitors to estimate fluid-responsive hypotension and measure recipient colloid oncotic pressure. The team limits crystalloid administration and empirically administers colloid for fluid deficits unless blood component transfusion is indicated. Additionally, colloids are administered for large-volume ascites drainage, consistent with large-volume paracentesis therapy. The choice of which colloid to administer (albumin versus HES) was optional until 2011, when the hospital’s Pharmacy and Therapeutics Committee decided to exclude albumin from operative cases (including OLTs) after analyzing the literature regarding the safety and efficacy of HES and considering the price advantage. This retrospective study was designed to explore the hypothesis that the type of colloid administered during OLT is associated with AKI.
We obtained IRB approval to retrospectively query our computerized medical record system for all cases with CPT code 47135 (liver allotransplantation). Our electronic anesthesia medical record system (PICIS, Wakefield, MA) and operative dictation reports were reviewed for the following data points: colloid usage (5% albumin or HES), vital signs (mean arterial blood pressure [MAP], central venous pressure [CVP]), blood product transfusion, administration of recombinant factor VIIa, intraoperative use of vasoactive substances (drug and dose), surgery duration, estimated blood loss, and basic demographics. For each patient, we also identified model for end-stage liver disease (MELD) score, serial serum creatinine and electrolyte values, need for RRT, postoperative complications (thrombus requiring reoperation, biliary leak, or early graft failure), mortality (intraoperative and 30 days), and severity of illness upon admission. The University Health System Consortium (UHC), in which our hospital participates, calculates a severity of illness for every patient admitted based on the APR-DRG (All Patient Refined Diagnosis Related Groups, 3M Health Information Systems). Severity is calculated using a combination of patient demographics, coded comorbidities, and principal and secondary diagnoses and procedures to define different levels of severity and complexity of treatment. The query examined all available records within our operating room electronic health record system (2010–2013). The authors acknowledge that including only the patient records since the institution of the electronic medical record limits the sample size; however, the quality of data on a sample of paper records for liver transplantation was inadequate for collection and reliable analysis.
The primary outcome of interest was the presence of postoperative AKI which was determined using the RIFLE “Injury” criteria of doubling serum creatinine (50% decreased glomerular filtration rate) within 7 days of surgery.3 The primary comparison of interest was to determine whether the use of HES or 5% human albumin was associated with the development of AKI. All patients were assigned to 1 of the 3 groups based on the type of colloid administered intraoperatively: (1) those who received albumin only, (2) those who received albumin and HES, and (3) those who received HES only. Grouping patients in this context provided an ordered ranked assignment, allowing the investigators to conduct both categorical comparisons and tests for linear trends for each outcome variable of interest. The associations among the 3 colloid groups with red blood cell (RBC) and fresh frozen plasma transfusion volume, presence of thrombosis, change in serum creatinine levels, and total colloid volume were examined using 1-way analysis of variance. Associations between colloid group and categorical variables were examined using χ2 and Fisher exact tests when appropriate. We also tested for rank linear trends by colloid group using the Mantel–Haenszel linear-by-linear test for association.
Patients were defined by RIFLE AKI criteria as having “no Risk,” “at Risk,” “Injury,” or “Failure.” By definition, any patient qualifying for a classification would also meet or exceed the criteria for lesser classes. For the multivariate analysis, patients were dichotomized as those with “Injury” or “Failure” versus “no Risk” or “at Risk.” Multivariate logistic regression models of the primary outcome (AKI) were constructed to test the association with colloid type controlling for severity of illness, MELD score, intraoperative hemodynamics (MAP and CVP), baseline characteristics, and interaction terms.
A propensity score matching analysis was also performed to adjust intergroup differences between subjects given albumin only and subjects given HES only due to potential selection bias in the decision to give albumin versus HES. Propensity scores were estimated using a logistic regression model with treatment assignment as the dependent variable and all identifiable confounding variables as independent covariates. Potential confounding variables were defined as those having a P value <0.2 in univariate tests of association with colloid type and/or AKI. Patients in the 2 groups were matched based on their propensity scores using the nearest neighbor approach with replacement and 2-to-1 matching for HES only to albumin only. The maximal difference of propensity score for a match was 0.2 standard deviations of the logit of the propensity score. Sample balance was estimated postmatching using the weighted standardized difference.21 Propensity score analysis was conducted using the Matching Package in R v.188.8.131.52,23 All other analyses were conducted in SPSS v21.0 (IBM Corp., Armonk, NY).
We identified 230 OLTs in our electronic medical record. Of these patients, 174 met our criteria for analysis. Thirty-five patients were excluded for the following reasons: simultaneous dual-organ (liver and kidney) transplant (19), pediatric recipient (8), and incomplete “critical” data (preoperative labs or dictations) (8). An additional 21 patients did not receive any colloid (or none was documented). The final cohort included 168 unique subjects and 174 procedures. Patients were divided into 3 groups based on the type(s) of colloid administered during surgery: 5% albumin, HES, or both. Fifty (28.7%) of the study patients received 5% albumin only (control cohort), 99 (56.9%) received HES only (high-risk cohort), and 25 (14.4%) received both colloids (moderate-risk cohort).
Univariate Analysis Results
Baseline characteristics for the study population are shown in Table 1. The mean age of all study participants at date of transplant was 55 ± 10 years with a median age 57 years. Mean age did not vary significantly among groups. A majority of subjects were male in both groups. The causes of liver failure were evenly distributed among the 3 groups. There were no differences in distribution of patients with minor or moderate severity of illness. However, the distributions of patients with major or extreme severity of illness were significantly different among the cohorts, with more patients with the highest illness acuity (extreme) receiving albumin and more of those with major severity of illness receiving HES (P = 0.003).
Intraoperative characteristics of the groups based on the type of colloid(s) received are shown in Table 2. The mean volumes of colloids administered by group are shown in Table 2. The HES-only group received 81% more HES than the albumin and HES group (740 vs 1342 mL). Mean MELD scores (at the time of transplant with exception points included) were nearly identical among all 3 groups (22 ± 5 vs 22 ± 4 vs 21 ± 5, P = 0.127, respectively). The individual MELD components are shown with ranges among the 3 groups: serum creatinine 1.1 to 1.2 mg/dL (P > 0.80), international normalized ratio 1.6 to 1.7 (P > 0.93), and serum bilirubin 5.0 to 8.2 mg/dL (P > 0.129). Surgical durations were similar among the groups as were the blood pressure values (mean CVP and MAP). Estimated blood loss was larger in the albumin-only group (P = 0.049). There were no differences in administration of vasoactive drugs or antifibrinolytic drug administration. With the exception of platelet use, blood product administration was similar among the groups with a mean RBC requirement of 2342 mL for the entire cohort. Blood product usage among the albumin-only, both colloid, and HES-only cohorts was as follows: RBCs: 2706 ± 2449 mL vs 3059 ± 3714 vs 2042 ± 2276, respectively; P = 0.123; fresh frozen plasma: 2424 ± 1870 vs 2823 ± 2934 vs 2072 ± 2224, respectively; P = 0.287; and platelets: 427 ± 480 vs 472 ± 791 vs 248 ± 394, respectively; P = 0.037. Neither the administration of intraoperative platelets nor the volume of platelets transfused was associated with the development of AKI “Injury” (P = 0.76 and 0.94, respectively). The presence of ascites before transplantation across the entire study cohort was 43.2%. The proportion of ascites presence ranged among the 3 groups from 36% (HES only) to 53% (albumin) (P = 0.14). Preoperative ascites was not associated with AKI regardless of colloid group.
Postoperative outcomes are displayed in Table 3. Other than AKI, there were no associations between type of colloid(s) administered and any reported postoperative complication. There was also no appreciable difference in ICU or hospital length of stay. No patients included in the analysis required dialysis preoperatively (all dual-organ transplants were excluded). As mentioned above, AKI was assessed in terms of changes in serum creatinine values and classified kidney damage by RIFLE Criteria.3 The “Risk” group constituted patients with a 50% increase in serum creatinine from baseline, whereas the “Injury” group required at least a doubling of the baseline creatinine and “Failure” group at least tripling in serum creatinine or receiving post-transplant dialysis. There were no statistically significant differences in the percentage of patients meeting these criteria. The HES-only group had the highest percentage of patients in all 3 AKI stages, followed by the combination of 5% albumin/HES group, while the 5% albumin-only group demonstrated the lowest incidence of each stage of AKI.
Results of Linear-by-Linear and Multivariate Analyses
The linear association between colloidal use (5% albumin only versus albumin/HES versus HES only, ranked ordering) and “Injury” was statistically significant (P = 0.048). There was not a significant linear trend of increasing odds of either “Risk” or “Failure” by colloid use (P = 0.221 and 0.622, respectively, Fig. 1). Eighteen patients required RRT (continuous venous–venous hemodialysis or interval hemodialysis) within 30 days of transplant. There was no correlation among the 3 cohorts and the need for dialysis or the need for RRT. The only 2 deaths by 30-day post-transplant were in the HES group (2.0%); however, the scarcity of mortality in the entire cohort precluded the determination of any statistical associations between HES use and death.
Table 4 displays a multivariate logistic regression model of AKI (“no risk” or “at risk” versus “injury” or “failure”), demonstrating that after controlling for baseline differences among groups, patients receiving only HES had significantly increased odds of developing AKI “Injury” compared with those receiving only 5% albumin (adjusted odds ratio 2.94, 95% confidence interval, 1.13–7.7, P = 0.027). Severity of illness, blood product administration, and mean CVP (corollary of volume status) were not associated with AKI.
Table 5 displays a second multivariate logistic regression model for AKI. In this model, HES use for each subject was redefined as none, ≤500 mL, HES, or >500 mL HES, mean intraoperative CVP was redefined as an ordinal variable, and intraoperative blood loss was included in the model. The results demonstrate similar trends in association between the dependent outcomes and independent covariates, when compared with the continuous variable multivariate model (Table 4). Patients who received >500 mL of HES, compared with those receiving only intraoperative albumin, showed a trend toward developing AKI “Injury” that approached statistical significance (P = 0.059) after controlling for severity of illness, CVP, and blood loss. Smaller amounts of intraoperative HES did not show an increased risk of AKI “Injury” (odds ratio 2.39, P = 0.190).
Results of Propensity Score Analysis
Variables selected for inclusion in the propensity score model included severity of illness at admission, MELD score, and nonalcoholic steatohepatitis cirrhosis as the primary reason for liver failure. Comparable patient groups included 37 patients who received albumin only and 74 patients who received HES only. Baseline characteristics and the weighted standardized mean difference between the 2 groups of the complete sample and of the propensity-matched sample are shown in Table 6. Similar to the multivariate model in Table 4, there was a significant difference in the propensity-matched sample in AKI incidence between subjects treated with albumin only compared with subjects treated with HES only (P = 0.044). In matched data, patients treated with HES had increased odds (1.18) of AKI compared with patients given albumin only (95% confidence interval, 1.01–1.39).
This retrospective longitudinal cohort study demonstrates the benefit of continual quality assessment and improvement efforts by multidisciplinary clinical care teams. This project originated from an internal observation of increased AKI in OLT recipients after changing the type of colloid used from 5% albumin to HES in 2011. This change in practice was encouraged as a cost saving in light of literature, suggesting no difference in renal outcomes between patients randomized to receive either 5% albumin or 6% HES.24 In contrast, our results suggest that HES likely is associated with AKI, supported by the statistically significant linear-by-linear association between the type of colloid(s) administered and incidence of AKI by RIFLE “Injury” classification. The data presented above caused our interdisciplinary team to revert to exclusively using albumin during OLT for colloidal volume expansion. Use of HES in the perioperative setting has been cautioned within our institution, awaiting validation of its safety.
The 3 compared colloid groups (albumin only, HES/albumin, and HES only) had similar demographics, causes of liver failure, and MELD scores. Within the limits of retrospective analysis, there does not appear to be a confounding variable associated with AKI that was disproportionately present within either of the HES groups. In fact, patients in the albumin-only group were more likely to be admitted with an APR-DRG classification of extreme severity of illness. Our measured surrogates for ischemia and hypoperfusion included length of surgery, mean MAP, CVP, estimated blood loss, and RBC transfusion requirement. These findings did not differ among colloid groups, indicating that the HES group did not undergo more complicated surgery or require more blood transfusions. Additionally, vasopressor use, antifibrinolytic use, and bilirubin levels were similar within all 3 colloid groups. The fundamental basis of the linear-by-linear association analysis was grounded on the assumption that an increased volume of HES administration would create a ranking risk of AKI. This assumption was feasible because the volume of HES administered in the HES-only group was nearly twice that in the albumin and HES group, while patients in the albumin-only group did not receive any HES. This finding is consistent with the dose–effect relationship between HES administration and AKI shown by Brunkhorst et al.25 Our results cannot comment on the safety of relatively low-volume HES administration within the OLT populations as has been demonstrated within the general critical care population because the average volumes of HES administered in both HES groups exceeded “low threshold” definitions for immediate resuscitation (HES volumes in HES and albumin- and HES-only cohorts: 740 ± 702 mL and 1342 ± 570 mL).26
Our retrospective review could not a priori control for confounding variables and thus required the use of multivariate analysis for HES-induced AKI. When the multivariate analysis included covariates in a continuous fashion, patients who received HES had significantly higher odds of developing AKI. When covariates were included in a transformed categorical ranked analysis, this trend continued but did not reach statistical significance (P = 0.059). This discrepancy may have been due to converting variables from continuous to categorical form, which reduced the ability of the model to detect differences, or because our categories for HES volume (none, <500 mL, >500 mL) were not optimally defined. We categorized HES by discrete volume increments (rather than continuously) because nearly all patients received HES in 500 mL. A few patients received <500 mL, but almost no patients received doses larger than 500 mL that were not in multiples of 500 mL.
The propensity analysis described above and shown in Table 6 further demonstrates that confounding covariates did not appreciably influence the impact of colloid type on the incidence of AKI. No model could be developed for the decision to administer HES instead of albumin because that decision was largely made by hospital administration and therefore unlikely to be confounded by pathophysiologic factors which may, coincidently, also affect AKI. As an example, thrombocytopenia might have caused the anesthesiologist to administer albumin instead of HES due to fear of subtle platelet dysfunction associated with HES. We found, however, that platelet use did not differ among categories of HES use.
Because of our relatively small sample size, we were unable to demonstrate an association between HES and the need for RRT in OLT. While recent literature suggests an association between renal failure and HES use in septic patients, the association in OLT patients may be different in magnitude. In light of the recent Food and Drug Administration warning, a prospective randomized trial comparing HES with albumin in OLT may not be feasible.18–20 However, future large-scale multicenter analyses using retrospective or registry data may better define the risk of AKI associated with these products in OLT patients.
Our research likely shows a retrospective linear-by-linear trend between 6% HES (130/0.4) administration in OLT and RIFLE “Injury”-stage AKI. Clinicians managing patients undergoing high-risk surgery or in critical condition should consider alternative colloids to 6% HES (130/0.4) until more definitive evidence is published.
Name: William R. Hand, MD.
Contribution: This author helped in design, data acquisition, data analysis, and manuscript preparation and is the corresponding author.
Attestation: William R. Hand has seen the original study data, reviewed the analysis of the data, and approved the final manuscript and is the author responsible for archiving the study files.
Name: Joseph R. Whiteley, DO.
Contribution: This author helped in design, data acquisition, data analysis, and manuscript preparation.
Attestation: Joseph R. Whiteley has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Tom I. Epperson, MD.
Contribution: This author helped in data analysis and manuscript preparation.
Attestation: Tom I. Epperson has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Lauren Tam, BS.
Contribution: This author helped in data acquisition, data analysis, and manuscript preparation.
Attestation: Lauren Tam has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Heather Crego, RN, BSN, CCTC.
Contribution: This author helped in data acquisition and manuscript preparation.
Attestation: Heather Crego has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Bethany Wolf, PhD.
Contribution: This author helped in statistical analysis and manuscript revision.
Attestation: Bethany Wolf has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Kenneth D. Chavin, MD, PhD.
Contribution: This author helped in manuscript preparation.
Attestation: Kenneth D. Chavin has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: David J. Taber, PharmD.
Contribution: This author helped in design, data acquisition, data analysis, and manuscript preparation.
Attestation: David J. Taber has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
This manuscript was handled by: Avery Tung, MD.
1. Barri YM, Sanchez EQ, Jennings LW, Melton LB, Hays S, Levy MF, Klintmalm GB. Acute kidney injury following liver transplantation: definition and outcome. Liver Transpl. 2009;15:475–83
2. 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
3. Bellomo R, Ronco C, Kellum JA, Mehta RL, Palevsky P. 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;8.4:R204
4. Ricci Z, Cruz D, Ronco C. The RIFLE criteria and mortality in acute kidney injury: a systematic review. Kidney Int. 2008;73:538–46
5. O’Riordan A, Wong V, McQuillan R, McCormick PA, Hegarty JE, Watson AJ. Acute renal disease, as defined by the RIFLE criteria, post-liver transplantation. Am J Transplant. 2007;7:168–76
6. Iwakiri Y, Groszmann RJ. The hyperdynamic circulation of chronic liver diseases: from the patient to the molecule. Hepatology. 2006;43:S121–31
7. Arroyo V, Jiménez W. Complications of cirrhosis. II. Renal and circulatory dysfunction. Lights and shadows in an important clinical problem. J Hepatol. 2000;32:157–70
8. Davis CL, Gonwa TA, Wilkinson AH. Pathophysiology of renal disease associated with liver disorders: implications for liver transplantation. Part I. Liver Transpl. 2002;8:91–109
9. Lima EQ, Zanetta DM, Castro I, Massarollo PC, Mies S, Machado MM, Yu L. Risk factors for development of acute renal failure after liver transplantation. Ren Fail. 2003;25:553–60
10. Paramesh AS, Roayaie S, Doan Y, Schwartz ME, Emre S, Fishbein T, Florman S, Gondolesi GE, Krieger N, Ames S, Bromberg JS, Akalin E. Post-liver transplant acute renal failure: factors predicting development of end-stage renal disease. Clin Transplant. 2004;18:94–9
11. Pawarode A, Fine DM, Thuluvath PJ. Independent risk factors and natural history of renal dysfunction in liver transplant recipients. Liver Transpl. 2003;9:741–7
12. Ernest D, Belzberg AS, Dodek PM. Distribution of normal saline and 5% albumin infusions in septic patients. Crit Care Med. 1999;27:46–50
13. Quinlan GJ, Martin GS, Evans TW. Albumin: biochemical properties and therapeutic potential. Hepatology. 2005;41:1211–9
14. Sort P, Navasa M, Arroyo V, Aldeguer X, Planas R, Ruiz-del-Arbol L, Castells L, Vargas V, Soriano G, Guevara M, Ginès P, Rodés J. Effect of intravenous albumin on renal impairment and mortality in patients with cirrhosis and spontaneous bacterial peritonitis. N Engl J Med. 1999;341:403–9
15. Finfer S, Bellomo R, Boyce N, French J, Myburgh J, Norton RSAFE Study Investigators. . A comparison of albumin and saline for fluid resuscitation in the intensive care unit. N Engl J Med. 2004;350:2247–56
16. Myburgh JA, Finfer S, Bellomo R, Billot L, Cass A, Gattas D, Glass P, Lipman J, Liu B, McArthur C, McGuinness S, Rajbhandari D, Taylor CB, Webb SACHEST 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;367:1901–11
17. Perner A, Haase N, Guttormsen AB, Tenhunen J, Klemenzson G, Åneman A, Madsen KR, Møller MH, Elkjær JM, Poulsen LM, Bendtsen A, Winding R, Steensen M, Berezowicz P, Søe-Jensen P, Bestle M, Strand K, Wiis J, White JO, Thornberg KJ, Quist L, Nielsen J, Andersen LH, Holst LB, Thormar K, Kjældgaard AL, Fabritius ML, Mondrup F, Pott FC, Møller TP, Winkel P, Wetterslev J6S Trial Group; Scandinavian Critical Care Trials Group. . Hydroxyethyl starch 130/0.42 versus Ringer’s acetate in severe sepsis. N Engl J Med. 2012;367:124–34
19. Reinhart K, Takala J. Hydroxyethyl starches: what do we still know? Anesth Analg. 2011;112:507–11
20. Shafer SL. Shadow of doubt. Anesth Analg. 2011;112:498–500
21. Ausin PC. Assessing balance in measured baseline covariates when using many-to-one matching on the propensity score. Pharamcoepidemiol Drug Saf. 2008;17:1218–25
22. Sekhon JS. Multivariate Propensity Score Matching Software with Automated Balance Optimization: The Matching Package for R. J Stat Soft. 2011;42.7:1–52
23. R Core Development Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing Available at: http://www.R-project.org
24. Mukhtar A, Aboulfetouh F, Obayah G, Salah M, Emam M, Khater Y, Akram R, Hoballah A, Bahaa M, Elmeteini M, Hamza A. The safety of modern hydroxyethyl starch in living donor liver transplantation: a comparison with human albumin. Anesth Analg. 2009;109:924–30
25. Brunkhorst FM, Engel C, Bloos F, Meier-Hellmann A, Ragaller M, Weiler N, Moerer O, Gruendling M, Oppert M, Grond S, Olthoff D, Jaschinski U, John S, Rossaint R, Welte T, Schaefer M, Kern P, Kuhnt E, Kiehntopf M, Hartog C, Natanson C, Loeffler M, Reinhart KGerman Competence Network Sepsis (SepNet). . Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N Engl J Med. 2008;358:125–39
26. Boussekey N, Darmon R, Langlois J, Alfandari S, Devos P, Meybeck A, Chiche A, Georges H, Leroy O. Resuscitation with low volume hydroxyethylstarch 130 kDa/0.4 is not associated with acute kidney injury. Crit Care. 2010;14:R40