{"paper_id":"303862b1-da43-4470-9d63-9250a67ef4c4","body_text":"Intraoperative Hypotension during Liver Transplant Surgery is Associated with Postoperative Acute Kidney: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article Intraoperative Hypotension during Liver Transplant Surgery is Associated with Postoperative Acute Kidney: A Retrospective Cohort Study Alexandre JOOSTEN, Valerio Lucidi, Brigitte Ickx, Luc Van Obbergh, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-102671/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Jan, 2021 Read the published version in BMC Anesthesiology → Version 1 posted 12 You are reading this latest preprint version Abstract BACKGROUND : Acute kidney injury (AKI) occurs frequently after liver transplant surgery and is associated with significant morbidity and mortality. While the impact of intraoperative hypotension (IOH) on postoperative AKI has been well demonstrated in patients undergoing a wide variety of non-cardiac surgeries, it remains poorly studied in liver transplant surgery. We tested the hypothesis that IOH is associated with AKI following liver transplant surgery. METHODS : This historical cohort study included all consecutive patients who underwent liver transplant surgery between 2014 and 2019 except those with a preoperative creatinine > 1.5 mg/dl and/or who had combined transplantation surgery. IOH was defined as any mean arterial pressure (MAP) < 65 mmHg and was classified according to the percentage of case time during which the MAP was < 65 mmHg into three groups, based on the interquartile range of the study cohort: “short” (Quartile 1, < 8.6% of case time), “ intermediate” (Quartiles 2-3, 8.6-39.5%) and “ long” (Quartile 4, > 39.5%) duration. AKI stages were classified according to a “modified” “Kidney Disease: Improving Global Outcomes” (KDIGO) criteria. Logistic regression modelling was conducted to assess the association between IOH and postoperative AKI. The model was run both as a univariate and with multiple perioperative covariates to test for robustness to confounders. RESULTS : Of the 205 patients who met our inclusion criteria, 117 (57.1%) developed AKI. Fifty-two (25%), 102 (50%) and 51 (25%) patients had short, intermediate and long duration of IOH respectively. In multivariate analysis, IOH was independently associated with an increased risk of AKI (adjusted odds ratio [OR] 1.05; 95%CI 1.02-1.09; P < 0.001). Compared to “ short duration ” of IOH, “ intermediate duration” was associated with a 10-fold increased risk of developing AKI (OR 9.7; 95%CI 4.1-22.7; P < 0.001). “ Long duration” was associated with an even greater risk of AKI compared to “ short duration ” (OR 34.6; 95%CI 11.5-108.6; P < 0.001). CONCLUSION : Intraoperative hypotension is independently associated with the development of AKI after liver transplant surgery. The longer the MAP stays < 65 mmHg, the higher the risk the patient will develop AKI in the immediate postoperative period, and the greater the likely severity. Trial Registration: Not Applicable Anesthesiology & Pain Medicine Acute kidney disease renal failure Chronic kidney disease Hemodynamic Postoperative complications Figures Figure 1 Figure 1 Figure 2 Figure 2 Background Acute kidney injury (AKI) is a common postoperative complication following liver transplantation and is associated with increased morbidity, mortality and development of chronic kidney disease.[ 1 – 5 ] One of the most common diagnostic criteria used to classify AKI is the “Kidney Disease: Improving Global Outcomes” (KDIGO) system, which is based on changes in serum creatinine and urine output.[ 6 ] However, as urine output is rarely documented accurately in the perioperative setting, increases in serum creatinine are frequently used independently to define postoperative AKI (“modified” KDIGO classification). Multiple studies have identified patient and donor risk factors for AKI following liver transplant surgery including among others, female sex, obesity, diabetes, high model for end-stage liver disease (MELD) score, large amounts of blood loss, use of hydroxyethyl starch solution, perioperative blood glucose variability, cold and warm ischaemia times, donor age and graft sizes.[ 7 – 12 ] Haemodynamic variable such as intraoperative hypotension (IOH), most often defined as a mean arterial pressure (MAP) ≤ 65 mmHg, has been shown to be one of the most important factors associated with postoperative AKI.[ 13 ] Numerous large retrospective studies have shown that IOH is associated with postoperative AKI after various types of non-cardiac surgery, [ 14 – 19 ] but data on such an association in liver transplantation remain scarce.[ 20 ] We therefore conducted a historical cohort analysis to evaluate the association between IOH and the development of postoperative AKI in patients undergoing liver transplant surgery. Methods This single centre historical cohort study was approved by our Institutional Review Board on December 14, 2018 under the reference P2018/555 with a waiver of informed consent because of the observational and retrospective nature of the study. We identified all liver transplant patients from 2014 (when the anaesthetic data for our patients started to be computerised) to 2019 with our dedicated operating room softwares (TrackPro® and UltraGenda®, Belgium). We then retrospectively analysed the patients’ electronic medical records, which include a continuous intraoperative recording of vital signs (Innovian® Perioperative Care, Dräger, Lübeck, Germany). All patients who underwent a liver transplant between January 1, 2014 and December 30, 2019 were included except those. With a preoperative serum creatinine value > 1.5 mg/dL, and any patient who underwent a combined transplantation procedure (liver-kidney, liver-heart or liver-lung). Anaesthetic protocol Intraoperative anaesthesia was standardised according to institutional guidelines. Patients arrived in the operating room and were placed under an infrared heating lamp. Several non-invasive monitors were then applied: a 5-lead electrocardiogram (ECG), non-invasive blood pressure, rectal temperature probe, and a frontal electroencephalogram using bispectral index (BIS) monitoring (Aspect Medical System Inc, Natick, MA, USA). A bladder catheter was inserted. Vascular access consisted of one or two large bore peripheral venous catheters, right femoral artery and vein catheters, and right jugular vein catheter. The left femoral and internal jugular veins were not cannulated in case veno-venous bypass was required. A Swan-Ganz catheter (Edwards Lifesciences, Irvine, CA, USA) was inserted and use of haemodynamic agents was guided using continuous cardiac index, mixed venous oxygen saturation, central venous pressure, and arterial pressure. Rapid infusers, perfusion heaters, and a cell saver were ready for use prior to induction. In case of active haemorrhage, anaesthetists typically guided blood product administration using ROTEM monitoring. General anaesthesia was induced with propofol or etomidate. Antinociception was achieved with a remifentanil infusion and anaesthesia was maintained with sevoflurane or desflurane depending on physician preference. Rapid sequence intubation was performed if patients had not fasted appropriately or if they had abdominal ascites. Neuromuscular blockade was achieved in all patients and controlled with a train-of-four monitor (TOF scan, Idmed, France). The choice of muscular relaxant was left to the discretion of the anaesthetist. Fluid administration consisted of a baseline infusion of balanced crystalloid infusion (Plasmalyte®, Baxter, Belgium) and compensation for blood loss with either Plasmalyte®, 3% modified gelatin, or 4% albumin (depending on patient conditions and physician preference). Surgical procedure Almost all the liver transplantation were performed by recipient hepatectomy without venous-venous bypass, using the vena cava–sparing technique and piggy-back reconstruction. Liver reperfusion was performed through the portal vein first followed by subsequent arterial reperfusion. Biliary reconstruction was carried out with an end-to-end choledochocholedochostomy without a T-tube. Our immunosuppressive regimen comprised primarily tacrolimus with mycophenolate mofetil and prednisone. Tacrolimus trough levels were maintained at 5–10 ng/mL. Steroids were discontinued approximately 3 months after liver transplant surgery. Measurements and study outcomes MAP was recorded automatically during surgery at 30 second intervals by our anaesthesia information management system (Innovian). We extracted the raw values: all values < 30 and > 150 mmHg were considered to be artifacts and deleted. For each patient, we calculated the mean MAP value during the procedure and the percentage of case time during which the patient was hypotensive, defined as a MAP < 65 mmHg. IOH was then categorised into 3 levels based on the interquartile range (IQR) values of the study cohort for the percentage of case time during which patients were hypotensive, according to the methodology of Thacker et al [ 21 ] : “short duration” of IOH (in the lower 25th percentile), “intermediate duration” (between the 25th and the 75th percentile) and “long duration” (within in the upper 75th percentile). The primary outcome was the development of stage 1–3 AKI, defined using serum creatinine-based KDIGO definitions without taking into account diuresis (“modified” KDIGO classifications) because urine output is rarely documented accurately in the perioperative setting. The three modified KDIGO stages are: 1) Mild injury: creatinine increase of at least 0.3 mg/dl within the first 48-hours or 1.5 to 1.9 times the baseline level during the first postoperative week; 2) Moderate injury: creatinine increase of 2.0 to 3.0 times the baseline; and 3) Severe injury: creatinine increase of greater than 3.0 times the baseline, creatinine level of at least 4 mg/dl, or dependency on renal replacement therapy. Statistical analysis The normality of continuous data was assessed using a Kolmogorov-Smirnov test. Normally distributed variables were compared using a student’s t-test and are expressed as mean ± standard deviation (SD) and those not normally distributed were compared using a Mann-Whitney U-test and are expressed as median [25% − 75%] percentiles. Discrete data were expressed as a number and percentage and compared using a Chi square or a Fisher’s exact test when indicated. We used logistic regression modelling to evaluate the association between IOH and the development of postoperative AKI. Univariate logistic models were used to test for association with AKI using the following independent variables: sex, age, ASA class, weight, body mass index (BMI), Child-Pugh score, baseline serum creatinine and haemoglobin, MELD laboratory score, duration of anaesthesia, duration of surgery, fluid volumes (crystalloid, colloid, packed red blood cells, cell saver), estimated blood loss, diuresis, total fluid output, net fluid balance, use of vasopressors, mean case time with central venous pressure > 8 mmHg, preoperative use of different medications (Table 1 ), patient comorbidities (Table 1 ), donor age, donor BMI, postoperative fluid balance, use of cardiopulmonary bypass, presence of portal ischaemia or arterial ischaemia and any episodes of MAP < 65 mmHg. Variables significantly associated in univariate testing were then included in a multivariate logistic regression to evaluate their association with AKI. Risks of developing AKI based on the model are presented as odds ratios [ORs] and their 95% confidence intervals. Statistical significance was determined at the 0.05 level. All analyses were conducted with Minitab (Paris, France) and R ( www.r-project.org ). Table 1 Baseline characteristics Variables No AKI (N = 88) AKI (N = 117) p-value* Age (years) 57 [48–64] 57 [51–62] 0.85 Male (%) 61 (69) 83 (71) 0.76 Weight (kg) 75 [61–83] 83 [70–94] 0.019 ASA score (II/III/IV/V) 4/55/28/1 1/56/57/3 0.99 Comorbid conditions ¬ Myocardial injury (%) 5 (6) 5 (4) 0.61 ¬ Arterial hypertension (%) 52 (59) 73 (62) 0.88 ¬ Heart failure (%) 1 (1) 1 (1) 0.71 ¬ Hyperlipidaemia (%) 8 (9) 28 (24) 0.055 ¬ Diabetes mellitus (%) 26 (30) 32 (27) 0.16 ¬ Atrial fibrillation (%) 8 (9) 11 (9) 0.75 ¬ COPD (%) 5 (6) 4 (3) 0.61 ¬ Peripheral arteritis (% 4 (5) 5 (4) 0.76 Medication ¬ β blocker (%) 42 (47) 50 (43) 0.77 ¬ ACEI (%) 6 (7) 8 (7) 0.87 ¬ ARB (%) 2 (2) 1 (1) 0.99 ¬ Diuretics (%) 34 (39) 64 (55) 0.039 ¬ Statin (%) 9 (9) 13 (11) 0.75 Child-Pugh score 7 [ 5 – 11 ] 11 [ 7 – 13 ] 0.022 MELD score 12 [ 9 – 20 ] 19 [ 14 – 29 ] 0.014 Fulminant hepatitis (%) 4 (5) 8 (7) 0.81 Haemoglobin (g/dL) 12.1 [9.5–13.6] 10.4 [8.9–12.7] 0.014 Creatinine (mg/dL) 0.90 [0.70–1.19] 1.00 [0.70–1.32] 0.061 HBV (%) 14 (16) 14 (12) 0.86 HCV (%) 17 (20) 23 (20) 0.23 Donor age (y) 56 [46–66] 57 [45–68] 0.38 Donor BMI (kg/m 2 ) 25 [ 23 – 28 ] 26 [ 24 – 28 ] 0.14 * Univariate analysis Data are listed as “value (%)” and or median [25–75 percentiles]. AKI: acute kidney injury; ASA : American Society of Anesthesiology physical status; COPD: Chronic obstructive pulmonary disease ; ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blockers; MELD: model for end-stage liver disease; HBV: Hepatitis B virus; HCV: Hepatitis C virus Results Among the 242 patients who underwent a liver transplantation between January 1st 2014 and December 30th 2019, 205 patients met our inclusion criteria (Fig. 1 ) . One hundred and seventeen patients (57%) experienced some type of postoperative AKI (stages 1–3). AKI stage 1 occurred in 53 patients (25.9%) and stage 2–3 in 64 patients (31.1%). Among the whole study cohort, the median [25th − 75th quartiles] percentage of case time that patients had IOH was 21.4% [8.6–39.5]. Consequently, “short” duration of IOH was defined less than 8.6% of the intraoperative case time with a MAP < 65 mmHg (quartile 1), “intermediate” duration as 8.6–39.5% of case time with a MAP < 65 mmHg (quartiles 2–3) and “long” duration as > 39.5% of case time with a MAP < 65 mmHg (quartile 4). There were 52 (25%), 102 (50%) and 51 (25%) patients respectively each of these subgroups. Only two patients had no IOH using our definition (0% of case time spent with a MAP < 65 mmHg). Perioperative characteristics of the patients are shown in Tables 1 and 2 . Table 2 Perioperative variables Variables No AKI (N = 88) AKI (N = 117) p-value* Mean MAP (mmHg) 78 ± 7 72 ± 6 < 0.001 Duration of IOH** • Quartile 1 (< 8.6%) (%) • Quartiles 2–3 (8.6–39.5%) (%) • Quartile 4 (> 39.5%) (%) 44 (50) 37 (42) 7 (8) 8 (7) 65 (55) 44 (38) < 0.001 Anaesthesia duration (min) 460 [411–536] 500 [453–583] 0.39 Surgical duration (min) 333 [294–385] 376 [324–438] 0.076 Venous bypass (%) 3 (3) 5 (4) 0.53 Portal ischaemia (min) 378 [319–458] 420 [360–495] 0.047 Arterial ischaemia (min) 28 [24–35] 33 [26–43] 0.25 Crystalloids (mL) 2500 [1500–4150] 2100 [1500–3774] 0.25 Colloids (mL) 650 [0-1075] 900 [300–1500] 0.30 Packed red blood cells (mL) 271 [0-1034] 753 [241–1339] 0.013 Cell saver (mL) 211 [0-710] 479 [0-956] 0.064 Total IN (mL) 6157 [4041–9726] 8068 [5285–11517] 0.015 Estimated blood loss (mL) 2000 [1025–3000] 2700 [1500–5000] 0.006 Diuresis (mL) 368 [203–733] 259 [158–425] 0.26 Total OUT (mL) 2338 [1650–3304] 3050 [1793–5285] 0.011 Intraoperative net fluid balance (mL) 3660 [2028–5825] 4684 [2551–7764] 0.087 Fluid balance at POD#1 (mL) 1204 [188–2813] 2899 [1587–4534] 0.002 Combined fluid balance (mL)¤ 4926 [3103–8674] 8369 [4944–11308] 0.003 Calculated blood loss (mL) at POD#2 777 [535–1450] 1222 [698–2080] 0.010 Mean central venous pressure > 8 mmHg $ 50 (58) 75 (64) 0.336 Use of vasopressors 85 (97) 117 (100) 0.044 * univariate analysis ** percentage of surgical time spent with a MAP < 65 mmHg (see text for details) IOH: intraoperative hypotension POD#1: postoperative day 1 POD#2: postoperative day 2 ¤ combined fluid balance is the combination of intraoperative fluid balance and fluid balance on POD#1 $ mean central venous pressure is the average of all values over the surgery. “Total IN” is the sum of crystalloid, colloid, packed red blood cells and cell saver administration and “total OUT” is the sum of estimated blood loss and urine output. Net fluid balance is the difference total IN – total OUT. Data are expressed as mean ± standard deviation, median and [25th -75th ] percentiles or number and percentage (%) In univariate testing ( Tables 1 and 2 ) , patients who developed postoperative AKI had higher BMI (p = 0.041), were more likely to have received preoperative diuretics (p = 0.039), had higher Child-Pugh (p = 0.0022) and MELD (p = 0.014) scores, had lower preoperative haemoglobin levels (p = 0.014), were more likely to have had prolonged IOH (p < 0.001), portal ischaemia (p = 0.047), or packed red blood cell transfusion (p = 0.013), and had higher total fluid input (p = 0.015), estimated blood loss (p = 0.006), and total fluid output (p = 0.011) than patients who did not develop AKI. In multivariable analysis using the perioperative variables shown in Tables 1 and 2 , only BMI and IOH (OR = 1.05 [1.02–1.09], p < 0.001), were significantly associated with an increased risk of AKI. For every one percent increase in case time spent with a MAP of ≤ 65 mmHg, the risk of AKI increased by about 5%. Compared to “ short duration ” IOH, “ intermediate duration” IOH was associated with a 10-fold increased risk of developing AKI (OR of 9.7; 95% CI 4.1–22.7; P < 0.0001). “ Long duration” IOH was associated with an even greater risk of postoperative AKI (OR 34.6; 95% CI 11.5–108.6; P < 0.0001). Figure 2 shows the three different durations of IOH and their associations with the development of postoperative AKI. This suggests that the observed association between IOH and AKI was a dose-response relationship. Discussion The presence of IOH was associated with an increased risk of developing postoperative AKI after liver transplantation and this association was independent of potential perioperative confounders. Moreover, the longer a patient spent with a MAP < 65 mmHg during the liver transplantation procedure, the greater the risk he or she had of developing AKI in the immediate postoperative period. These findings confirm that IOH is of real clinical importance and should not be overlooked during the intraoperative period. Multiple large retrospective studies have shown an association between IOH and postoperative AKI,[ 13 – 20 , 22 ] and others have reported an association between the duration of IOH and cardiac, renal and neurological adverse events.[ 13 , 17 , 23 , 24 ] However, this association remains poorly defined in the context of liver transplantation.[ 20 ] To our knowledge, only one study has assessed the relationship between IOH and the risk of AKI in this patient population.[ 20 ] In that study, the authors demonstrated that severe IOH, defined as a MAP < 50 mmHg was strongly related to the development of moderate and severe AKI (stage 2–3). Patients undergoing liver transplant surgery frequently experience IOH as a result of various factors, including, among others, the duration of surgery, the severity of bleeding, the severity of the ischaemic reperfusion syndrome and the severity of the end-stage liver disease, characterised by a hyperdynamic state (high cardiac output and low systemic vascular resistance). However, most studies, that have assessed predisposing factors for AKI after liver transplant surgery, focused mainly on preoperative factors, which are often not modifiable . Perioperative risk factors, such as IOH, are, in contrast, potentially modifiable, and may be minimised by close a collaboration between the surgeon and the anaesthetist. Our results suggest that avoiding or at least minimising the duration of IOH may be a valuable target to reduce the development of postoperative AKI. Importantly, our hospital has no any strict MAP targets for liver transplant surgery (except to avoid a MAP < 65 mmHg) and MAP management is left to the discretion of the anaesthetist in charge of the patient. Two large randomised controlled trials have demonstrated that targeting a higher arterial pressure during surgery (well above 65 mmHg) was associated with a lower incidence of postoperative AKI.[ 25 , 26 ] In the first, there was a lower incidence of organ dysfunction in the group of patients managed using a targeted systolic arterial pressure closer to the patient's baseline value compared to the control group in which the same blood pressure target was used for all patients.[ 25 ] In the second study, targeting a MAP level between 80–95 mmHg in chronically hypertensive patients reduced the occurrence of postoperative AKI compared to two other MAP targets (65–79 and 96–110 mmHg).[ 26 ] French national guidelines recommend maintaining of MAP > 70 mmHg in patients with chronic hypertension (which is the case in 60% of our study cohort) in order to prevent AKI.[ 27 ] It naturally follows that targeting a strict MAP goal of 65 mmHg can potentially be flawed as a strict definition of IOH is quite challenging. While some authors use a reduction from baseline value” (e.g. a 20–30% reduction from the patient’s preoperative MAP value), others continue to use the well-known “absolute” threshold value of 65 mmHg to define IOH. We decided in this study to choose the latter as this is the most common practice at our institution. The validity of this threshold can of course be challenged, but Salmasi and colleagues demonstrated that management based on an absolute MAP threshold of 65 mmHg in all patients was equivalent to management targeting relative reductions in MAP from preoperative values in terms of incidence of myocardial and kidney injury.[ 13 ] Additionally, although the results of a large randomised controlled study supported the individualization of arterial pressure targets in order to reduce the incidence of organ dysfunction (including a reduction in AKI),[ 25 , 28 ] it is important to remember that such an approach can be extremely challenging to apply in patients undergoing liver transplant surgery, as higher values may potentially increase bleeding, making surgical conditions more challenging. As always, the risk-benefit ratio should be carefully assessed and future investigation into an optimal definition of IOH is urgently required for liver transplant recipients. This study has several additional limitations that should be taken into consideration when interpreting our findings. Firstly, it was observational, retrospective, single-centre and included a relatively small sample size. Therefore, a causal relationship cannot be established and our results may not be generalisable to other hospitals with different perioperative haemodynamic and anaesthetic management. Secondly, our findings may be biased by unmeasured confounding parameters at both the patient and hospital levels. Thirdly, as urine output was not taken into account for the classification of AKI, this may have led to a slight “underestimation” of the incidence of postoperative AKI in our study cohort. Fourthly, per KDIGO definitions, we defined AKI as the change in creatinine value between the preoperative value and the highest value during the first postoperative week. This might introduce time-varying confounding or mediating factors, which limit interpretation of the study finding. Fifthly, postoperative hypotension was not taken into account as MAP was less frequently measured in the intensive care unit or on the floor than in the operating room. Sixthly, although all patients had a pulmonary catheter, data on mixed venous oxygen saturation (SvO 2 ) and cardiac index were not linked to our electronic medical records and thus, could not be assessed in the present study. However, it is important to note that a recent manuscript demonstrated that decreased SvO 2 was associated with postoperative AKI after liver transplantation.[ 29 ] Seventhly, we had no data on the occurrence of post- reperfusion syndrome and its importance on IOH duration. Finally, it is important to note that we reported the odds ratio for a frequent outcome (AKI), and the odds ratio can overestimate the risk in this situation. Conclusions Our findings indicate that IOH is independently associated with the development of AKI after liver transplant surgery. The longer the MAP stays < 65 mmHg, the higher the risk the patient will develop AKI in the immediate postoperative period, and the greater the likely severity. Avoidance of IOH during liver transplant surgery may thus help reduce the incidence of this severe postoperative complication. Prospective studies are needed to assess whether targeting a higher MAP during this complex surgical procedure can reduce the risk of postoperative AKI. Declarations Ethics approval: Not Applicable Consent for publication: Not Applicable Availability of data and materials: By request to the corresponding author Competing interests: AJ is a consultant for Edwards Lifesciences (Irvine, California, USA), Aguettant Laboratoire (Lyon, France) and Fresenius Kabi (Bad Homburg, Germany) BS has received honoraria for consulting, honoraria for giving lectures, and refunds of travel expenses from Edwards Lifesciences Inc. (Irvine, CA, USA). BS has received honoraria for consulting, institutional restricted research grants, honoraria for giving lectures, and refunds of travel expenses from Pulsion Medical Systems SE (Feldkirchen, Germany). BS has received institutional restricted research grants, honoraria for giving lectures, and refunds of travel expenses from CNSystems Medizintechnik GmbH (Graz, Austria). BS has received institutional restricted research grants from Retia Medical LLC. (Valhalla, NY, USA). BS has received honoraria for giving lectures from Philips Medizin Systeme Böblingen GmbH (Böblingen, Germany). BS has received honoraria for consulting, institutional restricted research grants, and refunds of travel expenses from Tensys Medical Inc. (San Diego, CA, USA). OD is consultant for Medtronic (Trévoux, FRANCE) and received honoraria for giving lectures for Medtronic (Trévoux, FRANCE) and Livanova (Châtillon, France). The other authors have no conflicts of interest related to this article Funding: The authors received no funding for this work Authors' contributions: All authors read and approved the final manuscript. J: Designed the study, collected and analyzed the data and drafted the manuscript. L: Collected and analyzed the data and edited the final manuscript. I: Analyzed the data and edited the manuscript. VO: Analyzed the data and edited the final manuscript. G: Collected and analyzed the data and edited the final manuscript. B: Collected the data and edited the final manuscript. A: Analyzed the data and edited the final manuscript. D: Collected & analyzed the data and edited the final manuscript. FM: Analyzed the data and edited the final manuscript. C: Analyzed the data and edited the final manuscript. A: Analyzed the data and edited the final manuscript. D: Analyzed the data and edited the final manuscript. S: Analyzed the data and edited the final manuscript. V: Analyzed the data and edited the final manuscript R: Statistical analysis of the data and edited the final manuscript. VdL: Statistical analysis of the data and edited the final manuscript. Acknowledgements: All the clinicians who helped in data collection from the current liver transplant database. References Wilkinson A, Pham PT. Kidney dysfunction in the recipients of liver transplants . 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J Cardiothorac Vasc Anesth. 2017;31(2):582–9. Thacker JK, Mountford WK, Ernst FR, Krukas MR, Mythen MM. Perioperative Fluid Utilization Variability and Association With Outcomes: Considerations for Enhanced Recovery Efforts in Sample US Surgical Populations. Annals of surgery. 2016;263(3):502–10. Mathis MR, Naik BI, Freundlich RE, Shanks AM, Heung M, Kim M, Burns ML, Colquhoun DA, Rangrass G, Janda A, et al. Preoperative Risk and the Association between Hypotension and Postoperative Acute Kidney Injury. Anesthesiology. 2020;132(3):461–75. Wesselink EM, Kappen TH, Torn HM, Slooter AJC, van Klei WA. Intraoperative hypotension and the risk of postoperative adverse outcomes: a systematic review. Br J Anaesth. 2018;121(4):706–21. Maheshwari K, Turan A, Mao G, Yang D, Niazi AK, Agarwal D, Sessler DI, Kurz A. The association of hypotension during non-cardiac surgery, before and after skin incision, with postoperative acute kidney injury: a retrospective cohort analysis. Anaesthesia. 2018;73(10):1223–8. Futier E, Lefrant JY, Guinot PG, Godet T, Lorne E, Cuvillon P, Bertran S, Leone M, Pastene B, Piriou V, et al. Effect of Individualized vs Standard Blood Pressure Management Strategies on Postoperative Organ Dysfunction Among High-Risk Patients Undergoing Major Surgery: A Randomized Clinical Trial. JAMA: the journal of the American Medical Association. 2017;318(14):1346–57. Wu X, Jiang Z, Ying J, Han Y, Chen Z. Optimal blood pressure decreases acute kidney injury after gastrointestinal surgery in elderly hypertensive patients: A randomized study: Optimal blood pressure reduces acute kidney injury. J Clin Anesth. 2017;43:77–83. Ichai C, Vinsonneau C, Souweine B, Armando F, Canet E, Clec'h C, Constantin JM, Darmon M, Duranteau J, Gaillot T, et al: Acute kidney injury in the perioperative period and in intensive care units ( excluding renal replacement therapies ). Anaesthesia, critical care & pain medicine 2016, 35 (2):151–165. Godet T, Grobost R, Futier E. Personalization of arterial pressure in the perioperative period. Curr Opin Crit Care. 2018;24(6):554–9. Kim WH, Oh HW, Yang SM, Yu JH, Lee HC, Jung CW, Suh KS, Lee KH. Intraoperative Hemodynamic Parameters and Acute Kidney Injury After Living Donor Liver Transplantation. Transplantation. 2019;103(9):1877–86. Cite Share Download PDF Status: Published Journal Publication published 11 Jan, 2021 Read the published version in BMC Anesthesiology → Version 1 posted Review # 3 received at journal 05 Dec, 2020 Editorial decision: Minor revision 05 Dec, 2020 Review # 1 received at journal 08 Nov, 2020 Review # 2 received at journal 08 Nov, 2020 Reviewer # 3 agreed at journal 05 Nov, 2020 Reviewer # 2 agreed at journal 05 Nov, 2020 Reviewers invited by journal 02 Nov, 2020 Reviewer # 1 agreed at journal 02 Nov, 2020 Editor assigned by journal 01 Nov, 2020 Submission checks completed at journal 01 Nov, 2020 Editor invited by journal 01 Nov, 2020 First submitted to journal 12 Oct, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-102671\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research article\",\"associatedPublications\":[],\"authors\":[{\"id\":4403653,\"identity\":\"84c79a90-77a0-412b-b197-072f03d66bf0\",\"order_by\":0,\"name\":\"Alexandre 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Medicine\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Brenton\",\"middleName\":\"\",\"lastName\":\"Alexander\",\"suffix\":\"\"},{\"id\":4403660,\"identity\":\"89a72db4-85d0-4dae-a1c2-e353384141ea\",\"order_by\":7,\"name\":\"Olivier Desebbe\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Sauvegarde Clinic: Clinique de la Sauvegarde\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Olivier\",\"middleName\":\"\",\"lastName\":\"Desebbe\",\"suffix\":\"\"},{\"id\":4403661,\"identity\":\"c7fdea5c-4891-4947-a08e-e82e10be5430\",\"order_by\":8,\"name\":\"Francois-martin Carrier\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of Montreal: Universite de Montreal\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Francois-martin\",\"middleName\":\"\",\"lastName\":\"Carrier\",\"suffix\":\"\"},{\"id\":4403662,\"identity\":\"d7dea4e1-a8c4-4f7a-873b-9f989c19749e\",\"order_by\":9,\"name\":\"Daniel Cherqui\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Université Paris-Saclay: Universite Paris-Saclay\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Daniel\",\"middleName\":\"\",\"lastName\":\"Cherqui\",\"suffix\":\"\"},{\"id\":4403663,\"identity\":\"4545b11a-2f6f-4251-bf6c-6b6f18389511\",\"order_by\":10,\"name\":\"Rene Adam\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Université Paris-Saclay: Universite Paris-Saclay\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rene\",\"middleName\":\"\",\"lastName\":\"Adam\",\"suffix\":\"\"},{\"id\":4403664,\"identity\":\"8e0cd100-0890-4df4-9db4-09be6f0b1082\",\"order_by\":11,\"name\":\"Jacques Duranteau\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Universite Paris-Saclay\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jacques\",\"middleName\":\"\",\"lastName\":\"Duranteau\",\"suffix\":\"\"},{\"id\":4403665,\"identity\":\"5b346a1b-f17f-402a-914f-309c91b9d5c8\",\"order_by\":12,\"name\":\"Bernd Saugel\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Central Medical Library Hamburg: Universitatsklinikum Hamburg-Eppendorf\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Bernd\",\"middleName\":\"\",\"lastName\":\"Saugel\",\"suffix\":\"\"},{\"id\":4403666,\"identity\":\"c399468a-8f0c-4e2b-8a8a-e64d9459a39d\",\"order_by\":13,\"name\":\"Jean-Louis Vincent\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Erasme Hospital: Hopital Erasme\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jean-Louis\",\"middleName\":\"\",\"lastName\":\"Vincent\",\"suffix\":\"\"},{\"id\":4403667,\"identity\":\"b96bd65d-2537-414d-9c03-b42eaea76211\",\"order_by\":14,\"name\":\"Joseph Rinehart\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"University of California Irvine\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Joseph\",\"middleName\":\"\",\"lastName\":\"Rinehart\",\"suffix\":\"\"},{\"id\":4403668,\"identity\":\"2ad42d35-4093-462a-a0f5-6d180b593a23\",\"order_by\":15,\"name\":\"Philippe Van der Linden\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Brugmann University Hospital - Site Victor Horta: UVC Brugmann - Site Victor Horta\",\"correspondingAuthor\":false,\"submittingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Philippe\",\"middleName\":\"Van der\",\"lastName\":\"Linden\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2020-11-03 23:40:08\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-102671/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-102671/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12871-020-01228-y\",\"type\":\"published\",\"date\":\"2021-01-11T15:00:29+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":3467251,\"identity\":\"e4c6d507-f0ab-4afa-82e1-c85faa04d93a\",\"added_by\":\"auto\",\"created_at\":\"2020-11-09 17:02:34\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":540058,\"visible\":true,\"origin\":\"\",\"legend\":\"Among the 242 patients who underwent a liver transplantation between January 1st 2014 and December 30th 2019, 205 patients met our inclusion criteria\",\"description\":\"\",\"filename\":\"Diapositive1.JPG\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-102671/v1/2ca1025d91e5197bd2be66d4.JPG\"},{\"id\":3467240,\"identity\":\"a4328a0b-f114-4943-b63f-d14e57bf09de\",\"added_by\":\"auto\",\"created_at\":\"2020-11-09 17:02:28\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":540058,\"visible\":true,\"origin\":\"\",\"legend\":\"Among the 242 patients who underwent a liver transplantation between January 1st 2014 and December 30th 2019, 205 patients met our inclusion criteria\",\"description\":\"\",\"filename\":\"Diapositive1.JPG\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-102671/v1/34766810871a688fc4d9f02e.JPG\"},{\"id\":3467252,\"identity\":\"bccc2876-55f9-48d9-8e3c-6211a69a0e54\",\"added_by\":\"auto\",\"created_at\":\"2020-11-09 17:02:34\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":675453,\"visible\":true,\"origin\":\"\",\"legend\":\"three different durations of IOH and their associations with the development of postoperative AKI. This suggests that the observed association between IOH and AKI was a dose-response relationship\",\"description\":\"\",\"filename\":\"Diapositive2.JPG\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-102671/v1/b0f06a0bf64d5368baeea77d.JPG\"},{\"id\":3467241,\"identity\":\"33e10c6b-79be-4f1f-8b4e-259379c96a65\",\"added_by\":\"auto\",\"created_at\":\"2020-11-09 17:02:28\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":675453,\"visible\":true,\"origin\":\"\",\"legend\":\"three different durations of IOH and their associations with the development of postoperative AKI. This suggests that the observed association between IOH and AKI was a dose-response relationship\",\"description\":\"\",\"filename\":\"Diapositive2.JPG\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-102671/v1/93500a61efcb8fac161db90a.JPG\"},{\"id\":13611765,\"identity\":\"c6315732-3c11-491e-8d77-12fe77198d88\",\"added_by\":\"auto\",\"created_at\":\"2021-09-17 06:30:05\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":782429,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-102671/v1/7d74026a-a328-44fc-b139-2da2820b1d83.pdf\"}],\"financialInterests\":\"\",\"formattedTitle\":\"Intraoperative Hypotension during Liver Transplant Surgery is Associated with Postoperative Acute Kidney: A Retrospective Cohort Study\",\"fulltext\":[{\"header\":\"Background\",\"content\":\" \\u003cp\\u003eAcute kidney injury (AKI) is a common postoperative complication following liver transplantation and is associated with increased morbidity, mortality and development of chronic kidney disease.[\\u003cspan additionalcitationids=\\\"CR2 CR3 CR4\\\" citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e] One of the most common diagnostic criteria used to classify AKI is the \\u0026ldquo;Kidney Disease: Improving Global Outcomes\\u0026rdquo; (KDIGO) system, which is based on changes in serum creatinine and urine output.[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e] However, as urine output is rarely documented accurately in the perioperative setting, increases in serum creatinine are frequently used independently to define postoperative AKI (\\u0026ldquo;modified\\u0026rdquo; KDIGO classification).\\u003c/p\\u003e \\u003cp\\u003eMultiple studies have identified patient and donor risk factors for AKI following liver transplant surgery including among others, female sex, obesity, diabetes, high model for end-stage liver disease (MELD) score, large amounts of blood loss, use of hydroxyethyl starch solution, perioperative blood glucose variability, cold and warm ischaemia times, donor age and graft sizes.[\\u003cspan additionalcitationids=\\\"CR8 CR9 CR10 CR11\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e] Haemodynamic variable such as intraoperative hypotension (IOH), most often defined as a mean arterial pressure (MAP)\\u0026thinsp;\\u0026le;\\u0026thinsp;65\\u0026nbsp;mmHg, has been shown to be one of the most important factors associated with postoperative AKI.[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e] Numerous large retrospective studies have shown that IOH is associated with postoperative AKI after various types of non-cardiac surgery, [\\u003cspan additionalcitationids=\\\"CR15 CR16 CR17 CR18\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e] but data on such an association in liver transplantation remain scarce.[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]\\u003c/p\\u003e \\u003cp\\u003eWe therefore conducted a historical cohort analysis to evaluate the association between IOH and the development of postoperative AKI in patients undergoing liver transplant surgery.\\u003c/p\\u003e \"},{\"header\":\"Methods\",\"content\":\" \\u003cp\\u003eThis single centre historical cohort study was approved by our Institutional Review Board on December 14, 2018 under the reference P2018/555 with a waiver of informed consent because of the observational and retrospective nature of the study.\\u003c/p\\u003e \\u003cp\\u003eWe identified all liver transplant patients from 2014 (when the anaesthetic data for our patients started to be computerised) to 2019 with our dedicated operating room softwares (TrackPro\\u0026reg; and UltraGenda\\u0026reg;, Belgium). We then retrospectively analysed the patients\\u0026rsquo; electronic medical records, which include a continuous intraoperative recording of vital signs (Innovian\\u0026reg; Perioperative Care, Dr\\u0026auml;ger, L\\u0026uuml;beck, Germany). All patients who underwent a liver transplant between January 1, 2014 and December 30, 2019 were included except those. With a preoperative serum creatinine value\\u0026thinsp;\\u0026gt;\\u0026thinsp;1.5\\u0026nbsp;mg/dL, and any patient who underwent a combined transplantation procedure (liver-kidney, liver-heart or liver-lung).\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eAnaesthetic protocol\\u003c/h2\\u003e \\u003cp\\u003eIntraoperative anaesthesia was standardised according to institutional guidelines. Patients arrived in the operating room and were placed under an infrared heating lamp. Several non-invasive monitors were then applied: a 5-lead electrocardiogram (ECG), non-invasive blood pressure, rectal temperature probe, and a frontal electroencephalogram using bispectral index (BIS) monitoring (Aspect Medical System Inc, Natick, MA, USA). A bladder catheter was inserted. Vascular access consisted of one or two large bore peripheral venous catheters, right femoral artery and vein catheters, and right jugular vein catheter. The left femoral and internal jugular veins were not cannulated in case veno-venous bypass was required. A Swan-Ganz catheter (Edwards Lifesciences, Irvine, CA, USA) was inserted and use of haemodynamic agents was guided using continuous cardiac index, mixed venous oxygen saturation, central venous pressure, and arterial pressure. Rapid infusers, perfusion heaters, and a cell saver were ready for use prior to induction. In case of active haemorrhage, anaesthetists typically guided blood product administration using ROTEM monitoring. General anaesthesia was induced with propofol or etomidate. Antinociception was achieved with a remifentanil infusion and anaesthesia was maintained with sevoflurane or desflurane depending on physician preference. Rapid sequence intubation was performed if patients had not fasted appropriately or if they had abdominal ascites. Neuromuscular blockade was achieved in all patients and controlled with a train-of-four monitor (TOF scan, Idmed, France). The choice of muscular relaxant was left to the discretion of the anaesthetist. Fluid administration consisted of a baseline infusion of balanced crystalloid infusion (Plasmalyte\\u0026reg;, Baxter, Belgium) and compensation for blood loss with either Plasmalyte\\u0026reg;, 3% modified gelatin, or 4% albumin (depending on patient conditions and physician preference).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSurgical procedure\\u003c/h2\\u003e \\u003cp\\u003eAlmost all the liver transplantation were performed by recipient hepatectomy without venous-venous bypass, using the vena cava\\u0026ndash;sparing technique and piggy-back reconstruction. Liver reperfusion was performed through the portal vein first followed by subsequent arterial reperfusion. Biliary reconstruction was carried out with an end-to-end choledochocholedochostomy without a T-tube.\\u003c/p\\u003e \\u003cp\\u003eOur immunosuppressive regimen comprised primarily tacrolimus with mycophenolate mofetil and prednisone. Tacrolimus trough levels were maintained at 5\\u0026ndash;10\\u0026nbsp;ng/mL. Steroids were discontinued approximately 3 months after liver transplant surgery.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMeasurements and study outcomes\\u003c/h2\\u003e \\u003cp\\u003eMAP was recorded automatically during surgery at 30 second intervals by our anaesthesia information management system (Innovian). We extracted the raw values: all values\\u0026thinsp;\\u0026lt;\\u0026thinsp;30 and \\u0026gt;\\u0026thinsp;150\\u0026nbsp;mmHg were considered to be artifacts and deleted. For each patient, we calculated the mean MAP value during the procedure and the percentage of case time during which the patient was hypotensive, defined as a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg. IOH was then categorised into 3 levels based on the interquartile range (IQR) values of the study cohort for the percentage of case time during which patients were hypotensive, according to the methodology of Thacker et al [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] : \\u0026ldquo;short duration\\u0026rdquo; of IOH (in the lower 25th percentile), \\u0026ldquo;intermediate duration\\u0026rdquo; (between the 25th and the 75th percentile) and \\u0026ldquo;long duration\\u0026rdquo; (within in the upper 75th percentile).\\u003c/p\\u003e \\u003cp\\u003eThe primary outcome was the development of stage 1\\u0026ndash;3 AKI, defined using serum creatinine-based KDIGO definitions without taking into account diuresis (\\u0026ldquo;modified\\u0026rdquo; KDIGO classifications) because urine output is rarely documented accurately in the perioperative setting. The three modified KDIGO stages are: 1) Mild injury: creatinine increase of at least 0.3\\u0026nbsp;mg/dl within the first 48-hours or 1.5 to 1.9 times the baseline level during the first postoperative week; 2) Moderate injury: creatinine increase of 2.0 to 3.0 times the baseline; and 3) Severe injury: creatinine increase of greater than 3.0 times the baseline, creatinine level of at least 4\\u0026nbsp;mg/dl, or dependency on renal replacement therapy.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eStatistical analysis\\u003c/h2\\u003e \\u003cp\\u003eThe normality of continuous data was assessed using a Kolmogorov-Smirnov test. Normally distributed variables were compared using a student\\u0026rsquo;s t-test and are expressed as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation (SD) and those not normally distributed were compared using a Mann-Whitney U-test and are expressed as median [25% \\u0026minus;\\u0026thinsp;75%] percentiles. Discrete data were expressed as a number and percentage and compared using a Chi square or a Fisher\\u0026rsquo;s exact test when indicated.\\u003c/p\\u003e \\u003cp\\u003eWe used logistic regression modelling to evaluate the association between IOH and the development of postoperative AKI. Univariate logistic models were used to test for association with AKI using the following independent variables: sex, age, ASA class, weight, body mass index (BMI), Child-Pugh score, baseline serum creatinine and haemoglobin, MELD laboratory score, duration of anaesthesia, duration of surgery, fluid volumes (crystalloid, colloid, packed red blood cells, cell saver), estimated blood loss, diuresis, total fluid output, net fluid balance, use of vasopressors, mean case time with central venous pressure\\u0026thinsp;\\u0026gt;\\u0026thinsp;8\\u0026nbsp;mmHg, preoperative use of different medications (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), patient comorbidities (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), donor age, donor BMI, postoperative fluid balance, use of cardiopulmonary bypass, presence of portal ischaemia or arterial ischaemia and any episodes of MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg. Variables significantly associated in univariate testing were then included in a multivariate logistic regression to evaluate their association with AKI. Risks of developing AKI based on the model are presented as odds ratios [ORs] and their 95% confidence intervals. Statistical significance was determined at the 0.05 level. All analyses were conducted with Minitab (Paris, France) and R (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e\\u003ca href=\\\"http://www.r-project.org\\\" target=\\\"_blank\\\"\\u003ewww.r-project.org\\u003c/a\\u003e\\u003c/span\\u003e\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eBaseline characteristics\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariables\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNo AKI\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;88)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAKI\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;117)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ep-value*\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAge (years)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e57 [48\\u0026ndash;64]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e57 [51\\u0026ndash;62]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.85\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMale (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e61 (69)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83 (71)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.76\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eWeight (kg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e75 [61\\u0026ndash;83]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e83 [70\\u0026ndash;94]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.019\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eASA score (II/III/IV/V)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4/55/28/1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1/56/57/3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.99\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eComorbid conditions\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Myocardial injury (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5 (6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Arterial hypertension (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e52 (59)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e73 (62)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Heart failure (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1 (1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Hyperlipidaemia (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8 (9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e28 (24)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.055\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Diabetes mellitus (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e26 (30)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e32 (27)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Atrial fibrillation (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e8 (9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11 (9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; COPD (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5 (6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4 (3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Peripheral arteritis (%\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.76\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003eMedication\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; β blocker (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e42 (47)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e50 (43)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; ACEI (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6 (7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.87\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; ARB (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2 (2)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1 (1)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.99\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Diuretics (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e34 (39)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e64 (55)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.039\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003e\\u0026not; Statin (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9 (9)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e13 (11)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.75\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChild-Pugh score\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e7 [\\u003cspan additionalcitationids=\\\"CR6 CR7 CR8 CR9 CR10\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e11 [\\u003cspan additionalcitationids=\\\"CR8 CR9 CR10 CR11 CR12\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.022\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMELD score\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e12 [\\u003cspan additionalcitationids=\\\"CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19\\\" citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e19 [\\u003cspan additionalcitationids=\\\"CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28\\\" citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.014\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFulminant hepatitis (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4 (5)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (7)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.81\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHaemoglobin (g/dL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e12.1 [9.5\\u0026ndash;13.6]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e10.4 [8.9\\u0026ndash;12.7]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.014\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCreatinine (mg/dL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0.90 [0.70\\u0026ndash;1.19]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.00 [0.70\\u0026ndash;1.32]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.061\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHBV (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e14 (16)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e14 (12)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.86\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHCV (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e17 (20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e23 (20)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDonor age (y)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e56 [46\\u0026ndash;66]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e57 [45\\u0026ndash;68]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDonor BMI (kg/m\\u003csup\\u003e2\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e25 [\\u003cspan additionalcitationids=\\\"CR24 CR25 CR26 CR27\\\" citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26 [\\u003cspan additionalcitationids=\\\"CR25 CR26 CR27\\\" citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.14\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e* Univariate analysis\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eData are listed as \\u0026ldquo;value (%)\\u0026rdquo; and or median [25\\u0026ndash;75 percentiles]. AKI: acute kidney injury; ASA : American Society of Anesthesiology physical status; COPD: Chronic obstructive pulmonary disease ; ACEI: angiotensin-converting enzyme inhibitor; ARB: angiotensin II receptor blockers; MELD: model for end-stage liver disease; HBV: Hepatitis B virus; HCV: Hepatitis C virus\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \"},{\"header\":\"Results\",\"content\":\" \\u003cp\\u003eAmong the 242 patients who underwent a liver transplantation between January 1st 2014 and December 30th 2019, 205 patients met our inclusion criteria (Fig.\\u0026nbsp;1\\u003cb\\u003e)\\u003c/b\\u003e.\\u003c/p\\u003e \\u003cp\\u003eOne hundred and seventeen patients (57%) experienced some type of postoperative AKI (stages 1\\u0026ndash;3). AKI stage 1 occurred in 53 patients (25.9%) and stage 2\\u0026ndash;3 in 64 patients (31.1%). Among the whole study cohort, the median [25th \\u0026minus;\\u0026thinsp;75th quartiles] percentage of case time that patients had IOH was 21.4% [8.6\\u0026ndash;39.5]. Consequently, \\u0026ldquo;short\\u0026rdquo; duration of IOH was defined less than 8.6% of the intraoperative case time with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg (quartile 1), \\u0026ldquo;intermediate\\u0026rdquo; duration as 8.6\\u0026ndash;39.5% of case time with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg (quartiles 2\\u0026ndash;3) and \\u0026ldquo;long\\u0026rdquo; duration as \\u0026gt;\\u0026thinsp;39.5% of case time with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg (quartile 4). There were 52 (25%), 102 (50%) and 51 (25%) patients respectively each of these subgroups. Only two patients had no IOH using our definition (0% of case time spent with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg). Perioperative characteristics of the patients are shown in Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003ePerioperative variables\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"4\\\"\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVariables\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eNo AKI\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;88)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eAKI\\u003c/p\\u003e \\u003cp\\u003e(N\\u0026thinsp;=\\u0026thinsp;117)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ep-value*\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean MAP (mmHg)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e78\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;7\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e72\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDuration of IOH**\\u003c/p\\u003e \\u003cp\\u003e\\u0026bull; Quartile 1 (\\u0026lt;\\u0026thinsp;8.6%) (%)\\u003c/p\\u003e \\u003cp\\u003e\\u0026bull; Quartiles 2\\u0026ndash;3 (8.6\\u0026ndash;39.5%) (%)\\u003c/p\\u003e \\u003cp\\u003e\\u0026bull; Quartile 4 (\\u0026gt;\\u0026thinsp;39.5%) (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e44 (50)\\u003c/p\\u003e \\u003cp\\u003e37 (42)\\u003c/p\\u003e \\u003cp\\u003e7 (8)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8 (7)\\u003c/p\\u003e \\u003cp\\u003e65 (55)\\u003c/p\\u003e \\u003cp\\u003e44 (38)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAnaesthesia duration (min)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e460 [411\\u0026ndash;536]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e500 [453\\u0026ndash;583]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.39\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSurgical duration (min)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e333 [294\\u0026ndash;385]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e376 [324\\u0026ndash;438]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.076\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eVenous bypass (%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3 (3)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e5 (4)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePortal ischaemia (min)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e378 [319\\u0026ndash;458]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e420 [360\\u0026ndash;495]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.047\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eArterial ischaemia (min)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e28 [24\\u0026ndash;35]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e33 [26\\u0026ndash;43]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.25\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCrystalloids (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2500 [1500\\u0026ndash;4150]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2100 [1500\\u0026ndash;3774]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.25\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eColloids (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e650 [0-1075]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e900 [300\\u0026ndash;1500]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.30\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePacked red blood cells (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e271 [0-1034]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e753 [241\\u0026ndash;1339]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.013\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCell saver (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e211 [0-710]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e479 [0-956]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.064\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal IN (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e6157 [4041\\u0026ndash;9726]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8068 [5285\\u0026ndash;11517]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.015\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eEstimated blood loss (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2000 [1025\\u0026ndash;3000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2700 [1500\\u0026ndash;5000]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.006\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDiuresis (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e368 [203\\u0026ndash;733]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e259 [158\\u0026ndash;425]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.26\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eTotal OUT (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2338 [1650\\u0026ndash;3304]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3050 [1793\\u0026ndash;5285]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.011\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIntraoperative net fluid balance (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e3660 [2028\\u0026ndash;5825]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4684 [2551\\u0026ndash;7764]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.087\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFluid balance at POD#1 (mL)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1204 [188\\u0026ndash;2813]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2899 [1587\\u0026ndash;4534]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.002\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCombined fluid balance (mL)\\u0026curren;\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e4926 [3103\\u0026ndash;8674]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8369 [4944\\u0026ndash;11308]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.003\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCalculated blood loss (mL) at POD#2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e777 [535\\u0026ndash;1450]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1222 [698\\u0026ndash;2080]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.010\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eMean central venous pressure\\u0026thinsp;\\u0026gt;\\u0026thinsp;8 mmHg\\u003cspan\\u003e$\\u003c/span\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e50 (58)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e75 (64)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.336\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eUse of vasopressors\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e85 (97)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e117 (100)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u003cb\\u003e0.044\\u003c/b\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e* univariate analysis\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e** percentage of surgical time spent with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg (see text for details)\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eIOH: intraoperative hypotension\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003ePOD#1: postoperative day 1\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003ePOD#2: postoperative day 2\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u0026curren; combined fluid balance is the combination of intraoperative fluid balance and fluid balance on POD#1\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e$ mean central venous pressure is the average of all values over the surgery.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003e\\u0026ldquo;Total IN\\u0026rdquo; is the sum of crystalloid, colloid, packed red blood cells and cell saver administration and \\u0026ldquo;total OUT\\u0026rdquo; is the sum of estimated blood loss and urine output. Net fluid balance is the difference total IN \\u0026ndash; total OUT.\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"4\\\"\\u003eData are expressed as mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;standard deviation, median and [25th -75th ] percentiles or number and percentage (%)\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn univariate testing \\u003cb\\u003e(\\u003c/b\\u003eTables\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e\\u003cb\\u003e)\\u003c/b\\u003e, patients who developed postoperative AKI had higher BMI (p\\u0026thinsp;=\\u0026thinsp;0.041), were more likely to have received preoperative diuretics (p\\u0026thinsp;=\\u0026thinsp;0.039), had higher Child-Pugh (p\\u0026thinsp;=\\u0026thinsp;0.0022) and MELD (p\\u0026thinsp;=\\u0026thinsp;0.014) scores, had lower preoperative haemoglobin levels (p\\u0026thinsp;=\\u0026thinsp;0.014), were more likely to have had prolonged IOH (p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), portal ischaemia (p\\u0026thinsp;=\\u0026thinsp;0.047), or packed red blood cell transfusion (p\\u0026thinsp;=\\u0026thinsp;0.013), and had higher total fluid input (p\\u0026thinsp;=\\u0026thinsp;0.015), estimated blood loss (p\\u0026thinsp;=\\u0026thinsp;0.006), and total fluid output (p\\u0026thinsp;=\\u0026thinsp;0.011) than patients who did not develop AKI.\\u003c/p\\u003e \\u003cp\\u003eIn multivariable analysis using the perioperative variables shown in Tables\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, only BMI and IOH (OR\\u0026thinsp;=\\u0026thinsp;1.05 [1.02\\u0026ndash;1.09], p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), were significantly associated with an increased risk of AKI. For every one percent increase in case time spent with a MAP of \\u0026le;\\u0026thinsp;65\\u0026nbsp;mmHg, the risk of AKI increased by about 5%.\\u003c/p\\u003e \\u003cp\\u003eCompared to \\u0026ldquo;\\u003cem\\u003eshort duration\\u003c/em\\u003e\\u0026rdquo; IOH, \\u0026ldquo;\\u003cem\\u003eintermediate duration\\u0026rdquo;\\u003c/em\\u003e IOH was associated with a 10-fold increased risk of developing AKI (OR of 9.7; 95% CI 4.1\\u0026ndash;22.7; P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.0001). \\u0026ldquo;\\u003cem\\u003eLong duration\\u0026rdquo;\\u003c/em\\u003e IOH was associated with an even greater risk of postoperative AKI (OR 34.6; 95% CI 11.5\\u0026ndash;108.6; P\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.0001). Figure\\u0026nbsp;2 shows the three different durations of IOH and their associations with the development of postoperative AKI. This suggests that the observed association between IOH and AKI was a dose-response relationship.\\u003c/p\\u003e \"},{\"header\":\"Discussion\",\"content\":\" \\u003cp\\u003eThe presence of IOH was associated with an increased risk of developing postoperative AKI after liver transplantation and this association was independent of potential perioperative confounders. Moreover, the longer a patient spent with a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg during the liver transplantation procedure, the greater the risk he or she had of developing AKI in the immediate postoperative period. These findings confirm that IOH is of real clinical importance and should not be overlooked during the intraoperative period.\\u003c/p\\u003e \\u003cp\\u003eMultiple large retrospective studies have shown an association between IOH and postoperative AKI,[\\u003cspan additionalcitationids=\\\"CR14 CR15 CR16 CR17 CR18 CR19\\\" citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e] and others have reported an association between the duration of IOH and cardiac, renal and neurological adverse events.[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e] However, this association remains poorly defined in the context of liver transplantation.[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] To our knowledge, only one study has assessed the relationship between IOH and the risk of AKI in this patient population.[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] In that study, the authors demonstrated that severe IOH, defined as a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;50\\u0026nbsp;mmHg was strongly related to the development of moderate and severe AKI (stage 2\\u0026ndash;3). Patients undergoing liver transplant surgery frequently experience IOH as a result of various factors, including, among others, the duration of surgery, the severity of bleeding, the severity of the ischaemic reperfusion syndrome and the severity of the end-stage liver disease, characterised by a hyperdynamic state (high cardiac output and low systemic vascular resistance). However, most studies, that have assessed predisposing factors for AKI after liver transplant surgery, focused mainly on preoperative factors, which are often \\u003cem\\u003enot modifiable\\u003c/em\\u003e. Perioperative risk factors, such as IOH, are, in contrast, potentially modifiable, and may be minimised by close a collaboration between the surgeon and the anaesthetist. Our results suggest that avoiding or at least minimising the duration of IOH may be a valuable target to reduce the development of postoperative AKI.\\u003c/p\\u003e \\u003cp\\u003eImportantly, our hospital has no any strict MAP targets for liver transplant surgery (except to avoid a MAP\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg) and MAP management is left to the discretion of the anaesthetist in charge of the patient. Two large randomised controlled trials have demonstrated that targeting a higher arterial pressure during surgery (well above 65\\u0026nbsp;mmHg) was associated with a lower incidence of postoperative AKI.[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e] In the first, there was a lower incidence of organ dysfunction in the group of patients managed using a targeted systolic arterial pressure closer to the patient's baseline value compared to the control group in which the same blood pressure target was used for all patients.[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e] In the second study, targeting a MAP level between 80\\u0026ndash;95\\u0026nbsp;mmHg in chronically hypertensive patients reduced the occurrence of postoperative AKI compared to two other MAP targets (65\\u0026ndash;79 and 96\\u0026ndash;110\\u0026nbsp;mmHg).[\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e] French national guidelines recommend maintaining of MAP\\u0026thinsp;\\u0026gt;\\u0026thinsp;70\\u0026nbsp;mmHg in patients with chronic hypertension (which is the case in 60% of our study cohort) in order to prevent AKI.[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e] It naturally follows that targeting a strict MAP goal of 65\\u0026nbsp;mmHg can potentially be flawed as a strict definition of IOH is quite challenging. While some authors use a reduction from baseline value\\u0026rdquo; (e.g. a 20\\u0026ndash;30% reduction from the patient\\u0026rsquo;s preoperative MAP value), others continue to use the well-known \\u0026ldquo;absolute\\u0026rdquo; threshold value of 65\\u0026nbsp;mmHg to define IOH. We decided in this study to choose the latter as this is the most common practice at our institution. The validity of this threshold can of course be challenged, but Salmasi and colleagues demonstrated that management based on an absolute MAP threshold of 65\\u0026nbsp;mmHg in all patients was equivalent to management targeting relative reductions in MAP from preoperative values in terms of incidence of myocardial and kidney injury.[\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e] Additionally, although the results of a large randomised controlled study supported the individualization of arterial pressure targets in order to reduce the incidence of organ dysfunction (including a reduction in AKI),[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e] it is important to remember that such an approach can be extremely challenging to apply in patients undergoing liver transplant surgery, as higher values may potentially increase bleeding, making surgical conditions more challenging. As always, the risk-benefit ratio should be carefully assessed and future investigation into an optimal definition of IOH is urgently required for liver transplant recipients.\\u003c/p\\u003e \\u003cp\\u003eThis study has several additional limitations that should be taken into consideration when interpreting our findings. Firstly, it was observational, retrospective, single-centre and included a relatively small sample size. Therefore, a causal relationship cannot be established and our results may not be generalisable to other hospitals with different perioperative haemodynamic and anaesthetic management. Secondly, our findings may be biased by unmeasured confounding parameters at both the patient and hospital levels. Thirdly, as urine output was not taken into account for the classification of AKI, this may have led to a slight \\u0026ldquo;underestimation\\u0026rdquo; of the incidence of postoperative AKI in our study cohort. Fourthly, per KDIGO definitions, we defined AKI as the change in creatinine value between the preoperative value and the highest value during the first postoperative week. This might introduce time-varying confounding or mediating factors, which limit interpretation of the study finding. Fifthly, postoperative hypotension was not taken into account as MAP was less frequently measured in the intensive care unit or on the floor than in the operating room. Sixthly, although all patients had a pulmonary catheter, data on mixed venous oxygen saturation (SvO\\u003csub\\u003e2\\u003c/sub\\u003e) and cardiac index were not linked to our electronic medical records and thus, could not be assessed in the present study. However, it is important to note that a recent manuscript demonstrated that decreased SvO\\u003csub\\u003e2\\u003c/sub\\u003e was associated with postoperative AKI after liver transplantation.[\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e] Seventhly, we had no data on the occurrence of post- reperfusion syndrome and its importance on IOH duration. Finally, it is important to note that we reported the odds ratio for a frequent outcome (AKI), and the odds ratio can overestimate the risk in this situation.\\u003c/p\\u003e \"},{\"header\":\"Conclusions\",\"content\":\" \\u003cp\\u003eOur findings indicate that IOH is independently associated with the development of AKI after liver transplant surgery. The longer the MAP stays\\u0026thinsp;\\u0026lt;\\u0026thinsp;65\\u0026nbsp;mmHg, the higher the risk the patient will develop AKI in the immediate postoperative period, and the greater the likely severity. Avoidance of IOH during liver transplant surgery may thus help reduce the incidence of this severe postoperative complication. Prospective studies are needed to assess whether targeting a higher MAP during this complex surgical procedure can reduce the risk of postoperative AKI.\\u003c/p\\u003e \"},{\"header\":\"Declarations\",\"content\":\"\\u003cul\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eEthics approval: \\u003c/strong\\u003eNot Applicable\\u003c/li\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eConsent for publication: \\u003c/strong\\u003eNot Applicable\\u003c/li\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eAvailability of data and materials: \\u003c/strong\\u003eBy request to the corresponding author\\u003c/li\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eCompeting interests:\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003cli\\u003eAJ is a consultant for Edwards Lifesciences (Irvine, California, USA), Aguettant Laboratoire (Lyon, France) and Fresenius Kabi (Bad Homburg, Germany)\\u003c/li\\u003e\\n\\u003cli\\u003eBS has received honoraria for consulting, honoraria for giving lectures, and refunds of travel expenses from Edwards Lifesciences Inc. (Irvine, CA, USA). BS has received honoraria for consulting, institutional restricted research grants, honoraria for giving lectures, and refunds of travel expenses from Pulsion Medical Systems SE (Feldkirchen, Germany). BS has received institutional restricted research grants, honoraria for giving lectures, and refunds of travel expenses from CNSystems Medizintechnik GmbH (Graz, Austria). BS has received institutional restricted research grants from Retia Medical LLC. (Valhalla, NY, USA). BS has received honoraria for giving lectures from Philips Medizin Systeme B\\u0026ouml;blingen GmbH (B\\u0026ouml;blingen, Germany). BS has received honoraria for consulting, institutional restricted research grants, and refunds of travel expenses from Tensys Medical Inc. (San Diego, CA, USA).\\u003c/li\\u003e\\n\\u003cli\\u003eOD is consultant for Medtronic (Tr\\u0026eacute;voux, FRANCE) and received honoraria for giving lectures for Medtronic (Tr\\u0026eacute;voux, FRANCE) and Livanova (Ch\\u0026acirc;tillon, France).\\u003c/li\\u003e\\n\\u003cli\\u003eThe other authors have no conflicts of interest related to this article\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cul\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eFunding: \\u003c/strong\\u003eThe authors received no funding for this work\\u003c/li\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eAuthors' contributions: \\u003c/strong\\u003eAll authors read and approved the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eJ: Designed the study, collected and analyzed the data and drafted the manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eL: Collected and analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eI: Analyzed the data and edited the manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eVO: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eG: Collected and analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eB: Collected the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eA: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eD: Collected \\u0026amp; analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eFM: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eC: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eA: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eD: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eS: Analyzed the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eV: Analyzed the data and edited the final manuscript\\u003c/li\\u003e\\n\\u003cli\\u003eR: Statistical analysis of the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003eVdL: Statistical analysis of the data and edited the final manuscript.\\u003c/li\\u003e\\n\\u003cli\\u003e\\u003cstrong\\u003eAcknowledgements: \\u003c/strong\\u003eAll the clinicians who helped in data collection from the current liver transplant database.\\u003c/li\\u003e\\n\\u003c/ul\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eWilkinson A, Pham PT. \\u003cb\\u003eKidney dysfunction in the recipients of liver transplants\\u003c/b\\u003e. \\u003cem\\u003eLiver transplantation: official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society\\u003c/em\\u003e 2005(11 Suppl 2):S47-51.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCholongitas E, Senzolo M, Patch D, Shaw S, O'Beirne J, Burroughs AK. Cirrhotics admitted to intensive care unit: the impact of acute renal failure on mortality. Eur J Gastroenterol Hepatol. 2009;21(7):744\\u0026ndash;50.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVelidedeoglu E, Bloom RD, Crawford MD, Desai NM, Campos L, Abt PL, Markmann JW, Mange KC, Olthoff KM, Shaked A, et al. Early kidney dysfunction post liver transplantation predicts late chronic kidney disease. Transplantation. 2004;77(4):553\\u0026ndash;6.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHilmi IA, Damian D, Al-Khafaji A, Planinsic R, Boucek C, Sakai T, Chang CC, Kellum JA. Acute kidney injury following orthotopic liver transplantation: incidence, risk factors, and effects on patient and graft outcomes. Br J Anaesth. 2015;114(6):919\\u0026ndash;26.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBarri YM, Sanchez EQ, Jennings LW, Melton LB, Hays S, Levy MF, Klintmalm GB. Acute kidney injury following liver transplantation: definition and outcome. Liver transplantation: official publication of the American Association for the Study of Liver Diseases the International Liver Transplantation Society. 2009;15(5):475\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKellum JA, Lameire N. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care (London England). 2013;17(1):204.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIwata H, Mizuno S, Ishikawa E, Tanemura A, Murata Y, Kuriyama N, Azumi Y, Kishiwada M, Usui M, Sakurai H, et al: \\u003cb\\u003eNegative prognostic impact of renal replacement therapy in adult living\\u003c/b\\u003e-\\u003cb\\u003edonor liver transplant recipients\\u003c/b\\u003e: \\u003cb\\u003epreoperative recipient condition and donor factors\\u003c/b\\u003e. \\u003cem\\u003eTransplantation proceedings\\u003c/em\\u003e 2014, \\u003cb\\u003e46\\u003c/b\\u003e(3):716\\u0026ndash;720.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHand WR, Whiteley JR, Epperson TI, Tam L, Crego H, Wolf B, Chavin KD, Taber DJ. Hydroxyethyl starch and acute kidney injury in orthotopic liver transplantation: a single-center retrospective review. Anesthesia analgesia. 2015;120(3):619\\u0026ndash;26.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYoo S, Lee HJ, Lee H, Ryu HG. Association Between Perioperative Hyperglycemia or Glucose Variability and Postoperative Acute Kidney Injury After Liver Transplantation: A Retrospective Observational Study. Anesthesia analgesia. 2017;124(1):35\\u0026ndash;41.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCheng Y, Wei GQ, Cai QC, Jiang Y, Wu AP. Prognostic Value of Model for End-Stage Liver Disease Incorporating with Serum Sodium Score for Development of Acute Kidney Injury after Liver Transplantation. Chin Med J. 2018;131(11):1314\\u0026ndash;20.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCabezuelo JB, Ram\\u0026iacute;rez P, R\\u0026iacute;os A, Acosta F, Torres D, Sansano T, Pons JA, Bru M, Montoya M, Bueno FS, et al. Risk factors of acute renal failure after liver transplantation. Kidney international. 2006;69(6):1073\\u0026ndash;80.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eThongprayoon C, Kaewput W, Thamcharoen N, Bathini T, Watthanasuntorn K, Lertjitbanjong P, Sharma K, Salim SA, Ungprasert P, Wijarnpreecha K, et al: \\u003cb\\u003eIncidence and Impact of Acute Kidney Injury after Liver Transplantation: A Meta-Analysis\\u003c/b\\u003e. \\u003cem\\u003eJournal of clinical medicine\\u003c/em\\u003e 2019, 8(3).\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSalmasi V, Maheshwari K, Yang D, Mascha EJ, Singh A, Sessler DI, Kurz A. Relationship between Intraoperative Hypotension, Defined by Either Reduction from Baseline or Absolute Thresholds, and Acute Kidney and Myocardial Injury after Noncardiac Surgery: A Retrospective Cohort Analysis. Anesthesiology. 2017;126(1):47\\u0026ndash;65.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHallqvist L, Granath F, Huldt E, Bell M. Intraoperative hypotension is associated with acute kidney injury in noncardiac surgery: An observational study. Eur J Anaesthesiol. 2018;35(4):273\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSun LY, Wijeysundera DN, Tait GA, Beattie WS. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015;123(3):515\\u0026ndash;23.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJang WY, Jung JK, Lee DK, Han SB. Intraoperative hypotension is a risk factor for postoperative acute kidney injury after femoral neck fracture surgery: a retrospective study. BMC Musculoskelet Disord. 2019;20(1):131.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWalsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, Cywinski J, Thabane L, Sessler DI. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology. 2013;119(3):507\\u0026ndash;15.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTang Y, Zhu C, Liu J, Wang A, Duan K, Li B, Yuan H, Zhang H, Yao M, Ouyang W. Association of Intraoperative Hypotension with Acute Kidney Injury after Noncardiac Surgery in Patients Younger than 60 Years Old. Kidney blood pressure research. 2019;44(2):211\\u0026ndash;21.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAn R, Pang QY, Liu HL: \\u003cb\\u003eAssociation of intra\\u003c/b\\u003e-\\u003cb\\u003eoperative hypotension with acute kidney injury\\u003c/b\\u003e, \\u003cb\\u003emyocardial injury and mortality in non\\u003c/b\\u003e-\\u003cb\\u003ecardiac surgery\\u003c/b\\u003e: \\u003cb\\u003eA meta\\u003c/b\\u003e-\\u003cb\\u003eanalysis\\u003c/b\\u003e. \\u003cem\\u003eInternational journal of clinical practice\\u003c/em\\u003e 2019, \\u003cb\\u003e73\\u003c/b\\u003e(10):e13394.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMizota T, Hamada M, Matsukawa S, Seo H, Tanaka T, Segawa H. Relationship Between Intraoperative Hypotension and Acute Kidney Injury After Living Donor Liver Transplantation: A Retrospective Analysis. J Cardiothorac Vasc Anesth. 2017;31(2):582\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eThacker JK, Mountford WK, Ernst FR, Krukas MR, Mythen MM. Perioperative Fluid Utilization Variability and Association With Outcomes: Considerations for Enhanced Recovery Efforts in Sample US Surgical Populations. Annals of surgery. 2016;263(3):502\\u0026ndash;10.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMathis MR, Naik BI, Freundlich RE, Shanks AM, Heung M, Kim M, Burns ML, Colquhoun DA, Rangrass G, Janda A, et al. Preoperative Risk and the Association between Hypotension and Postoperative Acute Kidney Injury. Anesthesiology. 2020;132(3):461\\u0026ndash;75.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWesselink EM, Kappen TH, Torn HM, Slooter AJC, van Klei WA. Intraoperative hypotension and the risk of postoperative adverse outcomes: a systematic review. Br J Anaesth. 2018;121(4):706\\u0026ndash;21.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMaheshwari K, Turan A, Mao G, Yang D, Niazi AK, Agarwal D, Sessler DI, Kurz A. The association of hypotension during non-cardiac surgery, before and after skin incision, with postoperative acute kidney injury: a retrospective cohort analysis. Anaesthesia. 2018;73(10):1223\\u0026ndash;8.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFutier E, Lefrant JY, Guinot PG, Godet T, Lorne E, Cuvillon P, Bertran S, Leone M, Pastene B, Piriou V, et al. Effect of Individualized vs Standard Blood Pressure Management Strategies on Postoperative Organ Dysfunction Among High-Risk Patients Undergoing Major Surgery: A Randomized Clinical Trial. JAMA: the journal of the American Medical Association. 2017;318(14):1346\\u0026ndash;57.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWu X, Jiang Z, Ying J, Han Y, Chen Z. Optimal blood pressure decreases acute kidney injury after gastrointestinal surgery in elderly hypertensive patients: A randomized study: Optimal blood pressure reduces acute kidney injury. J Clin Anesth. 2017;43:77\\u0026ndash;83.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eIchai C, Vinsonneau C, Souweine B, Armando F, Canet E, Clec'h C, Constantin JM, Darmon M, Duranteau J, Gaillot T, et al: \\u003cb\\u003eAcute kidney injury in the perioperative period and in intensive care units\\u003c/b\\u003e (\\u003cb\\u003eexcluding renal replacement therapies\\u003c/b\\u003e). \\u003cem\\u003eAnaesthesia, critical care \\u0026amp; pain medicine\\u003c/em\\u003e 2016, \\u003cb\\u003e35\\u003c/b\\u003e(2):151\\u0026ndash;165.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGodet T, Grobost R, Futier E. Personalization of arterial pressure in the perioperative period. Curr Opin Crit Care. 2018;24(6):554\\u0026ndash;9.\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim WH, Oh HW, Yang SM, Yu JH, Lee HC, Jung CW, Suh KS, Lee KH. Intraoperative Hemodynamic Parameters and Acute Kidney Injury After Living Donor Liver Transplantation. Transplantation. 2019;103(9):1877\\u0026ndash;86.\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-anesthesiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"bane\",\"sideBox\":\"Learn more about [BMC Anesthesiology](http://bmcanesthesiol.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/bane\",\"title\":\"BMC Anesthesiology\",\"twitterHandle\":\"BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Acute kidney disease, renal failure, Chronic kidney disease, Hemodynamic, Postoperative complications\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-102671/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-102671/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eBACKGROUND\\u003c/em\\u003e: \\u003c/strong\\u003eAcute kidney injury (AKI) occurs frequently after liver transplant surgery and is associated with significant morbidity and mortality. While the impact of intraoperative hypotension (IOH) on postoperative AKI has been well demonstrated in patients undergoing a wide variety of non-cardiac surgeries, it remains poorly studied in liver transplant surgery. We tested the hypothesis that IOH is associated with AKI following liver transplant surgery. \\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eMETHODS\\u003c/em\\u003e:\\u003c/strong\\u003e This historical cohort study included all consecutive patients who underwent liver transplant surgery between 2014 and 2019 except those with a preoperative creatinine \\u0026gt; 1.5 mg/dl and/or who had combined transplantation surgery. IOH was defined as any mean arterial pressure (MAP) \\u0026lt; 65 mmHg and was classified according to the percentage of case time during which the MAP was \\u0026lt; 65 mmHg into three groups, based on the interquartile range of the study cohort: \\u003cem\\u003e“short”\\u003c/em\\u003e (Quartile 1, \\u0026lt; 8.6% of case time), “\\u003cem\\u003eintermediate” \\u003c/em\\u003e(Quartiles 2-3, 8.6-39.5%) and “\\u003cem\\u003elong”\\u003c/em\\u003e (Quartile 4, \\u0026gt; 39.5%) duration. AKI stages were classified according to a “modified” “Kidney Disease: Improving Global Outcomes” (KDIGO) criteria. Logistic regression modelling was conducted to assess the association between IOH and postoperative AKI. The model was run both as a univariate and with multiple perioperative covariates to test for robustness to confounders. \\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eRESULTS\\u003c/em\\u003e:\\u003c/strong\\u003e Of the 205 patients who met our inclusion criteria, 117 (57.1%) developed AKI. Fifty-two (25%), 102 (50%) and 51 (25%) patients had short, intermediate and long duration of IOH respectively. In multivariate analysis, IOH was independently associated with an increased risk of AKI (adjusted odds ratio [OR] 1.05; 95%CI 1.02-1.09; P \\u0026lt; 0.001). Compared to “\\u003cem\\u003eshort duration\\u003c/em\\u003e” of IOH, “\\u003cem\\u003eintermediate duration”\\u003c/em\\u003e was associated with a 10-fold increased risk of developing AKI (OR 9.7; 95%CI 4.1-22.7; P \\u0026lt; 0.001). “\\u003cem\\u003eLong duration”\\u003c/em\\u003e was associated with an even greater risk of AKI compared to “\\u003cem\\u003eshort duration\\u003c/em\\u003e” (OR 34.6; 95%CI 11.5-108.6; P \\u0026lt; 0.001).\\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eCONCLUSION\\u003c/em\\u003e:\\u003c/strong\\u003e Intraoperative hypotension is independently associated with the development of AKI after liver transplant surgery. The longer the MAP stays \\u0026lt; 65 mmHg, the higher the risk the patient will develop AKI in the immediate postoperative period, and the greater the likely severity. \\u003c/p\\u003e\\u003cp\\u003e\\u003cstrong\\u003eTrial Registration: \\u003c/strong\\u003eNot Applicable\\u003c/p\\u003e\",\"manuscriptTitle\":\"Intraoperative Hypotension during Liver Transplant Surgery is Associated with Postoperative Acute Kidney: A Retrospective Cohort Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2020-11-09 17:02:26\",\"doi\":\"10.21203/rs.3.rs-102671/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2020-12-06T00:00:00+00:00\",\"index\":3,\"fulltext\":\"Recommendation: Major revisions required\\nForm responses:\\n---\\n\\nComments to Author:\\n---\\nWe have read with interest the study by Dr Joosten et Coll, which presents many valuable insights, but it remains some concerns:\\nMajor concerns:\\nWhy eliminate patients with moderate AKI (\\u003e 1.5 mg/dl) before the transplant when they are probably most at risk for severe AKI after the transplant. You need to discuss this point. A study of this subgroup would be interesting.\\nAs the authors point out, the Swan-Ganz data are not reported and therefore we can only rely on MAP for haemodynamic data, which is very limited.\\nFurthermore, the manuscript does not mention the total dose of catecholamine as well as the maximum dose, although the filling volume and fluid balance are specified.\\nThe usual protocol for the use of catecholamines and vascular filling based on hemodynamic data is not described.\\nIt is very surprising to note that in the multivariate analysis, neither the MELD, nor the duration of surgery, nor the duration of ischaemia are statistically significant. The same applies to age. All these variables emerge significantly in multivariate analysis in other studies on the risk of AKI after liver transplantation and are used in particular as a benchmark to establish the validity of the analysis model.\\nWhether BMI is significant and not age or pre-operative MELD is debatable - because it is unusual.\\nCan the non-inclusion of patients with pre-existing AKI explain this?\\nHence the importance of doing another analysis taking them into account for comparison.\\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\\n* Declaration of competing interests: **I declare that I have no competing interests**\\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\\n* Is the use of statistics and treatment of uncertainties appropriate?: **No**\\n* Is the presentation of the work clear?: **Yes**\\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\\n\"},{\"type\":\"decision\",\"content\":\"Minor revision\",\"date\":\"2020-12-06T00:00:00+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2020-11-09T00:00:00+00:00\",\"index\":1,\"fulltext\":\"Recommendation: Accept after minor essential revisions\\nForm responses:\\n---\\n\\nComments to Author:\\n---\\nThank you for giving me the opportunity to review the following manuscript: Intraoperative Hypotension during Liver Transplant Surgery is Associated with Postoperative Acute Kidney: A Retrospective Cohort Study\\n\\nMajor comments:\\n\\nPlease correct the title: the word injury is missing after kidney\\n\\nWhich institutional review board approved the study? There are 12 institutions affiliated with this paper.. Was it Paul Brousse Hospital, the corresponding author's institution?\\n\\nThe ethics approval in the disclosures is applicable. Please review the BMC instructions.\\n\\nOften a MBP under 55 is associated with poor outcome (e.g., AKI). I was surprised to see such a high incidence even at relatively \\\"light\\\" hypotension. Could the authors compare their threshold of 65mmHg to articles that use the 55mmHg threshold in the appropriate paragraph in their discussion?\\n\\nPlease fully discuss Figure 2, which is an extremely compelling figure at it demonstrates the association between time and intensity of AKI. Please also compare the literature.\\n\\nAgain, in the discussion, state the hospital as this is unclear which hospital is \\\"our hospital\\\"\\n\\nHypotension is a modifiable factor: please discuss how you can improve perioperative medicine by maintaining higher BP\\n\\nIn your cohort there is a very high incidence of hypotension. As your team is experienced in automated GDHT, what do you think of the potential of closed-loops systems to solve this problem?\\n\\nYour MAP in the AKI group is 72, don't you think targeting MAP at a higher level (e.g., 85mmHg) would decrease the incidence of hypotension. Should you change your protocol? Please discuss.\\n\\nMinor comments:\\n\\nPlease be concordant: is this a historical or a retrospective study?\\n\\nPlease check the authors' names, is Francois-martin Carrier the correct name? Lower case martin?\\n\\nIn introduction, perhaps also add that anuria is not always a marker of acute renal failure (after all a healthy person that has restricted fluid intake can have perfectly healthy kidneys but a urine output under 0.5cc/kg/h).\\n\\n\\\"Importantly, our hospital has no any strict MAP targets for liver transplant surgery\\n(except to avoid a MAP \\u003c 65mmHg) and MAP management is left to the discretion of the\\nanaesthetist in charge of the patient.\\\"\\n-\\u003e Again, which hospital?\\n\\n\\nPlease have a native speaker read over the English. There are small mistakes\\nFor example, but not limited to:\\n\\\"Haemodynamic variable such as intraoperative hypotension (IOH), most often defined as a mean arterial pressure (MAP) ≤ 65 mmHg, has been shown to be one of the most important factors associated with postoperative AKI.[13])\\\"\\n--\\u003e The subject is hypotension, not haemodynamic variable\\n\\n\\nPlease add adequate references for all sentence stating facts (including, but not limited to):\\n\\\"Patients undergoing liver transplant surgery frequently experience IOH as a result\\nof various factors, including, among others, the duration of surgery, the severity of bleeding,\\nthe severity of the ischaemic reperfusion syndrome and the severity of the end-stage liver\\ndisease, characterised by a hyperdynamic state (high cardiac output and low systemic vascular resistance).\\\"\\n\\n\\\"However, most studies, that have assessed predisposing factors for AKI after liver\\ntransplant surgery, focused mainly on preoperative factors, which are often not modifiable.\\\"\\n--\\u003e In addition to referencing this sentence, please correct it as the punctuation marks are poorly placed.\\n\\n\\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **No**\\n* Declaration of competing interests: **I declare that I have no competing interests**\\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. Any comments that I do not wish to be included in the published report have been included as confidential comments to the editor, which will not be published.: **I agree to the terms of the CC-BY 4.0 license; please do not publish my name with my report. (default)**\\n* Is the study design appropriate to answer the research question (including the use of appropriate controls), and are the conclusions supported by the evidence presented?: **Yes**\\n* Are the methods sufficiently described to allow the study to be repeated?: **Yes**\\n* Is the use of statistics and treatment of uncertainties appropriate?: **Yes**\\n* Is the presentation of the work clear?: **Yes**\\n* Are the images in this manuscript (including electrophoretic gels and blots) free from apparent manipulation?: **Yes**\\n\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2020-11-09T00:00:00+00:00\",\"index\":2,\"fulltext\":\"Recommendation: Accept after discretionary revisions\\nForm responses:\\n---\\n\\nComments to Author:\\n---\\nCongratulations for a great piece of work looking at the relationship between intra operative hypotension and acute kidney injury. It is well written and tackles a hot topic: the association between intra operative hypotension and post operative complications.\\n\\nA few minor details:\\nIn the title, the word injury is misssing after kidney (acute kidney injury)\\nCould you please provide more details regarding the ethics committee who approved the study?\\n\\nSome questions:\\n\\nWhich measurements did you use for mean arteriel pressure: non invasive or hemodynamic monitoring?\\n\\nIntra operative hypotension could also be comprised of stroke volume variation or reduction in systemic vascular resistance (both highly likely events during liver transplant and for which the retrospective data can be collected). Can you explain in more detail why you chose not to use these indices?\\n\\n\\nWhat measures where used to counteract hypotension? Perhaps the authors could suggest future protocols that could be used?\\n\\nIn the conclusion the authors could suggest future studies such as an RCT with two different levels of MAP, or perhaps with other haemodynamic variables?\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n* Publons Reviewer Recognition. Springer Nature can send verification of this review directly to Publons (a subsidiary of Clarivate Analytics). If you would like to take advantage of this service, please click on the “Yes” option below. Your name, email address, title of the reviewed manuscript, name of the journal, and date of your review submission (the “Review Data”) will then be transmitted to Publons upon publication of the manuscript. If you have already registered at Publons, they will notify you of the receipt of this review and update your profile as per your settings and their policy. If you are not registered with Publons, you will receive an email from them asking you to register in order for them to be able to recognize your review on your new profile page. Publons may use the Review Data to generate derivative metadata for the benefit of Publons and you as a reviewer, carefully considering the sensitivity of such information. For example, Publons may verify your record as a reviewer by updating your profile published on its webservice if you have registered for such service or help editors to identify candidate reviewers. Please find the details of processing in Publons’ privacy policy https://publons.com/about/terms: **Yes**\\n* Declaration of competing interests: **I declare that I have no competing interests.**\\n* Reviewer Publication Consent. I agree for my report to be made available under an Open Access Creative Commons CC-BY License (http://creativecommons.org/licenses/by/4.0) if this manuscript is accepted for publication. 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