Incidence, Risk Factors and Clinical Outcomes of Acute Kidney Injury after Heart Transplantation: A Retrospective Single Center Study.

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Yiyao Jiang, Xiangrong Kong, Fenlong Xue, Honglei Chen, Wei Zhou, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-29665/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Oct, 2020 Read the published version in Journal of Cardiothoracic Surgery → Version 2 posted 4 You are reading this latest preprint version Show more versions Abstract Objectives: This study aimed to identify the incidence rate of Acute kidney injury (AKI) in our center and predict in-hospital mortality and long-term survival after heart transplantation (HTx). Methods: This single-center, retrospective study from October 2009 and March 2020 analyzed the pre-, intra-, and postoperative characteristics of 95 patients who underwent HTx. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Risk factors were analyzed by multivariable logistic regression models. The log-rank test was used to compare long-term survival. Results: : Thirty-three (34.7%) patients developed AKI. The mortality in hospital in HTx patients with and without AKI were 21.21% and 6.45%, respectively ( P <0.05). Recipients in AKI who required renal replacement therapy (RRT) had a hospital mortality rate of 43.75% compared to 6.45% in those without AKI or RRT ( P< 0.0001). A long cardiopulmonary bypass (CPB) time (OR:11.393, 95% CI: 2.183 to 59.465, P =0.0039) was positively related to the occurrence of AKI. A high intraoperative urine volume (OR: 0.031, 95% CI: 0.005 to 0.212, P =0.0004) was negatively correlated with AKI. AKI requiring RRT (OR, 11.348; 95% CI, 2.418-53.267, P =0.002) was a risk factor for mortality in hospital. Overall survival in patients without AKI at 1 and 3 years was not different from that in patients with AKI ( P =0.096). Conclusions: AKI is common after HTx. AKI requiring RRT could contribute powerful prognostic information to predict mortality in hospital. A long CPB time and low intraoperative urine volume are associated with the occurrence of AKI. Cardiothoracic Surgery Acute kidney injury Heart transplantation Mortality Outcomes Figures Figure 1 Figure 2 Figure 3 Introduction Heart transplantation (HTx) is a generally successful procedure for patients with end-stage heart failure, improving their survival and quality of life [1]. Acute kidney injury (AKI) is a frequent complication following HTx. With an incidence ranging from 14% to 76%, it is a significant contributor to high morbidity and mortality [2-7]. There are various causes of AKI, such as renal hypoperfusion, prolonged cardiopulmonary bypass (CPB), and nephrotoxicity of immunosuppressive drugs [8]. Therefore, there is a need to identify high-risk factors, reduce the life-threatening outcomes of AKI, and enhance the long-term survival rates in HTx patients. Scoring systems for the quantification of AKI have been applied in clinical studies. These criteria included the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria, the Acute Kidney Injury Network (AKIN) criteria, and the Kidney Disease: Improving Global Outcomes (KDIGO) criteria [9-11]. Based on these criteria, AKI can be defined and staged. It is important to note that despite different performances of different scoring systems, a mild to modest form of AKI does not play a significant role in predicting poor long-term outcomes [12]. However, patients who develop severe AKI frequently receive renal replacement therapy (RRT) as a salvage treatment. The need for RRT has been reported to be one of the most important predictors of a poor prognosis after HTx [13]. Although some clinical outcomes associated with AKI requiring RRT have been described, its impact on long-term survival has not been addressed. The aims of this study were to (1) evaluate the incidence of AKI after HTx in our center by using the KDIGO criteria, (2) identify risk factors for AKI and in-hospital mortality after HTx, and (3) explore long-term survival in AKI patients. Methods Patient population Between October 2009 and March 2020, 113 patients were transplanted. According to exclusion criteria, 10 patients were underwent for combined heart-kidney transplant were not included; 8 patients who were lost to follow-up were also excluded. We included 95 patients in the final analysis. All patients were followed in the outpatient department. Perioperative management A biatrial technique was performed in the HTx procedure. All patients received methylprednisolone intraoperatively (500 mg when the aortic cross clamp was released) followed by 120 mg q8h intravenous for the first 24 h, 120mg q12h for the second 24h, 120 mg once daily for the third 24h and basiliximab (20 mg loading dose in the operating room and 20 mg the fourth day). On the fourth day postoperation, tacrolimus and mycophenolate mofetil was started at an oral dose of 1.5 mg and 500mg twice daily, respectively. Tacrolimus and mycophenolate mofetil were prescribed for the rest of their lives. Further, dosing was based on tacrolimus whole-blood trough concentrations at 6 a.m (12 h post-dose). A whole-blood tacrolimus trough concentration between 7 and 15 ng/ml was considered in the first 3 months and thereafter tapered towards 5-10 ng/ml. Accompanying immunosuppression comprised corticosteroids, prednisolone was started 28mg orally on the fourth day postoperation, followed by 24mg once daily and tapered off to 8mg once daily orally. Outcome measure AKI was classified according to the KDIGO criteria [11]. The KDIGO criteria recognize 3 stages of AKI severity based on serum creatinine (SCr) levels and urine output. The definition of AKI was based on peak creatinine within 7 days postoperation. The administration of loop diuretics is a commonly used method in the postoperative period and in the early management of AKI, at least in patients with volume overload and/or oliguria. Indications for RRT were stage 3 AKI combined with one of the following: hyperkalemia, severe hypervolemia, uncorrectable metabolic acidosis or serious uremia. Continuous variables are presented as mean±standard deviation, while categorical or integer variables are presented as number and percentage. To compare values between two groups, Student’s t test was used for normally distributed numerical variables, and Wilcoxon rank test for nonnormally ones. One-way analysis of covariance (ANOVA) or Kruskal-Wallis test was used for comparisons more than two groups. When there was a statistical significance among groups, SNK method was used to perform comparison between groups. Categorical or integer parameters compared by Fisher’s exact test or Chi-square test. Other continuous variables were expressed as median and interquartile (25 th to 75 th percentile) range and compared by Mann-Whitney U-test or Kruskal-Wallis test. Survival analysis was performed using log-rank test. Cox proportional hazards model were used to identify variables independently associated with mortality. All statistical procedures were performed using SAS 9.4 (SAS Institute Inc. Cary, NC, USA) and GraphPad Prism 5.0 (GraphPad Software Inc., La Jolla, USA). A two-tailed P value < 0.05 was considered statistically significant. Results Table 1 shows the demographics and perioperative characteristics of the HTx recipients stratified into 3 groups by the estimated glomerular filtration rate (eGFR). Patients in the GFR<30 ml/min/1.73 m 2 group were older than those in the eGFR≥60 ml/min/1.73 m 2 group ( P <0.001), and frequency of chronic kidney disease and the creatinine levels were higher in the GFR<30 ml/min/1.73 m 2 group than in the other groups ( P =0.0005 and P< 0.0001, respectively). However, there was no difference in body mass index (BMI) or left ventricular ejection fraction (LVEF) among the groups ( P =0.575 and 0.257, respectively). In addition, the three groups had a similar frequency of dilated cardiomyopathy (DCM), coronary artery disease (CAD), valve disease, and pre-percutaneous coronary intervention (PCI) ( P =0.279, 0.604, 0.756 and 0.441, respectively). Intraoperatively, patients in the GFR 0.05). Although there was decreased urine volume during the operation in the GFR0.05). Of the 95 HTx recipients who were enrolled, 33 patients fulfilled the criteria for AKI, and 62 patients were assigned to the non-AKI group (Table 2). Although there was no difference in most perioperative variables, the CPB time, blood loss and frequency of application of intra-aortic balloon pump with venoarterial extracorporeal membrane oxygenation (IABP/ECMO) during the operation were higher in the AKI group than in the non-AKI group ( P =0.0149, 0.0312 and 0.0102, respectively). Moreover, the urine volume during and after the operation was lower in the AKI group ( P <0.005). The frequency of RRT was higher in the AKI group than in the non-AKI group ( P< 0.0001). Table 3 shows the demographics and perioperative characteristics of 95 HTx recipients stratified into 3 groups by post-HTx RRT. Intraoperatively, the AKI with RRT group had a longer CPB time, more blood loss, lower urine volume and a higher frequency of IABP/ECMO than the other groups ( P =0.0088, 0.0298, 0.0021 and <0.0001, respectively). Postoperatively, there were significant differences in urine volume, mechanical ventilation rate and mortality in hospital. The overall hospital mortality was 11.58%(11/95). The orrcurence of AKI was associated with mortality in hospital ( P =0.0383). Patients requiring RRT had a hospital mortality of 43.75% (7/16) compared with 6.45% (4/62) in those patients without AKI or RRT (Figure 3 and Table 3). The causes of death were as follows: sepsis (n=3), respiratory failure (n=2), cerebral hemorrhage (n=1), pulmonary embolism (n=1), gastrointestinal bleeding (n=1), disseminated intravascular coagulation (n=1), shock (n=1), and 1 patients without diagnosis. Multivariate logistic regression analysis suggested that AKI requiring RRT was a risk factor independently associated with hospital mortality (Table 4). The median duration of follow-up after hospital discharge was 608 days (interquartile range, 303-1180 days) with a maximum of 3405 days. The clinical outcomes are summarized by eGFR stratification in Figure 1. There were no differences in long-term survival among the 3 groups stratified by eGFR ( P =0.897). When stratified by AKI, there was no difference in the overall 3-year survival rates ( P =0.096) (Figure 2). However, the survival rate was 72.16±16.38% in the AKI with RRT group, while the survival rate was 89.43±2.33% in the non-AKI without RRT group ( P <0.001) (Figure 3). A total of 4 deaths were observed during the follow-up period. The causes of death within 1 year were as follows: sepsis (n=2) and tumor metastasis (n=1). One patient requiring RRT passed away due to cerebral infarction at 3 years after HTx. The multivariable model for AKI is summarized in Table 5. When the CPB time is more than 265 min, it was positively related to the occurrence of AKI (OR: 11.393, 95% CI: 2.183 to 59.465, P =0.0039) . A decreased intraoperative urine volume, less than 1700ml, it may positively correlated with AKI (OR: 0.181, 95% CI: 0.042 to 0.774, P =0.0211). Discussion In our retrospective analysis, we found that AKI was a frequent complication of HTx, with an incidence of 34.7%. We also showed that a relatively short CPB time (≤ 265 min) and increased intraoperative urine volume could prevent the occurrence of AKI. Furthermore, AKI requiring RRT was an independent risk factor for in-hospital mortality after HTx. Finally, AKI requiring RRT was not associated with long-term mortality. Severe AKI is an important independent contributor to mortality in the HTx population. Accumulating evidence indicates that AKI requiring RRT could be a strong predictor of adverse clinical outcomes. In Renata’s study, patients with AKI, especially those requiring RRT (46.9%), had higher hospital mortality (16%) than those without AKI [14]. However, after hospital discharge, AKI was not associated with poor long-term outcomes. With a median follow-up after hospital discharge of 6.7 years, overall survival at 1, 5, and 10 years was 95.4%, 85.1%, and 75.4% and 85.2%, 69.8% and 63.5% among patients with AKI stages 2 and 3, respectively [14]. Fortrie’s findings showed that one-year mortality rates in patients without AKI and with AKI stages 1, 2, and 3 were 4.8%, 7.6%, 11.8%, and 14.7%, respectively[7]. In an extensive follow-up of 471 HTx patients over a period up to 26 years, no association was found between the development of AKI and long-term mortality or chronic RRT dependence [15]. In this study, we found that mortality in hospital in patients with AKI was 21.21%, and the incidence rate of AKI requiring RRT was 48.48%. Moreover, overall survival in patients without AKI at 1, and 3 years was higher than that in AKI patients. In contrast to the high overall incidence of AKI, the need for RRT in our study was 16.84%. This is similar to previous studies reporting a need for RRT in 6% to 29% of patients [2, 4, 6]. A recent analysis indicated that AKI requiring RRT had a 1-year mortality rate of 59.2% [16]. In Boyle’s study, AKI requiring RRT was associated with a mortality rate of 50% compared to 1.4% in patients without AKI [17]. We estimated an increased risk for in hospital mortality, with an odd ratio of 11.348 in AKI patients requiring RRT. These results could be explained by the fact that patients with severe AKI are less likely to achieve full recovery of kidney function, even with RRT, than patients with mild AKI. In fact, some AKI patients requiring RRT develop at least one other serious complication (sepsis, graft failure, or acute myocardial infarction), which can lead to early mortality during the postoperative care period. In our study, seven patients in AKI with RRT group passed away in hospital. However, there was a nonsignificant tendency toward an increase in long-term mortality in AKI patients requiring RRT, which is consistent with previous reports[3]. Therefore, the impact of RRT appears to be lost at long-term follow-up. This result indicated that recovery of kidney function prior to hospital discharge was associated with decreased long-term mortality risk. The interactions between the heart and kidney systems have become a matter of great concern [18]. The difference between arterial driving pressure and venous outflow pressure must remain sufficiently large for adequate renal blood flow and glomerular filtration. The low-resistance nature of the renal vasculature and parenchyma and the very low oxygen tension in the outer medulla also explain the unique sensitivity of the kidneys to hypotension-induced injury [2, 19]. Thus, both hemodynamic instability and antecedent hypotension should be considered in the consultative evaluation of a patient with developing AKI. Several factors have been suggested to contribute to the development of postoperative AKI. In general, the most common cause in the early postoperative period is ischemic-reperfusion injury [20]. Intraoperatively, maintenance of a mean arterial pressure (MAP) >60-65 mmHg, reduction in CPB time, minimization of blood transfusion and avoidance of nephrotoxic agents may prevent AKI [2, 21]. Moreover, increased central venous pressure (CVP) was associated with a reduced GFR and all-cause mortality. Right atrial pressure strongly predicts the development of AKI early after HTx and can be used as an early AKI indicator [22]. Finally, postoperatively, chloride-restricted fluid management was associated with less AKI and RRT [23]. In our opinion, a relatively short CPB time and increased intraoperative urine volume play important roles in preventing the occurrence of AKI after HTx. When AKI occurs, the most important thing is the time of applying RRT. It offers steady fluid removal and their intensity can be easily titrated for prevention or rapid administration of treatment of volume overload. This intervention in the postoperative management can prevent a higher progression of perioperative AKI, and the occurrence of the worst outcomes [24]. Although left ventricular assist device (LVAD ) is widely applied as a bridge to HTx, kidney dysfunction is common after LVAD implantation. In theory, improvements in cardiac output after implantation of LVAD would be expected to improve renal perfusion. Previous studies shown that the improvement in renal function was seen during the first month postimplantation of LVAD and no further improvements occurred thereafter [25, 26]. However, a decrease in renal function after implantation raising uncertainties about the long-term effects of continuous blood flow on renal function [27, 28]. The incidence of postimplantation AKI is 7%-14% in continuous-flow devices [29]. In addition, RRT is needed in a subset of patients who develop post-LVAD AKI[30]. In our study, a patient with non-pulsatile flow LVAD implantation developed AKI stage 2 before HTx but there is no AKI in post-HTx. We consider that the influence of LVAD on kidney do not affect the treatment effect of HTx. The performance and usefulness of different AKI scoring systems with regard to mortality vary greatly [31]. The KDIGO criteria are widely applied in the analysis of AKI in HTx patients. However, the emphasis on SCr and urine volume may exaggerate the severity of AKI. In addition, according to the RIFLE criteria, AKI encompasses the entire spectrum of the syndrome, from minor changes in renal function to the requirement of RRT. Thus, AKI does not simply represent acute renal failure but is a more general description [32]. Since the AKIN criteria are not sensitive enough to capture all episodes of AKI in cardiac surgery patients, they are not widely used for HTx patients [33]. We consider to evaluate this issue in future clinical trials. We acknowledge that several limitations exist in this study. The inherent limitation is that it was a retrospective, single-center study that enrolled a small number of patients. Furthermore, the small sample size made it difficult to detect small effects and prevented the accuracy of multivariate analysis. In addition, patients were relatively old and likely to suffer from comorbid conditions, such as diabetes mellitus and hypertension. These comorbidities may interfere with the analysis of the long-term survival rates in AKI requiring RRT. Finally, the indication for dialysis is standardized; however, to some extent, it depends on the physician treating the individual patient, which may have acted as a confounder in our study. Conclusions Our study suggests that AKI is a frequent complication of HTx, and the results demonstrated that AKI requiring RRT following HTx was associated with an increased risk for for in-hospital mortality. However, AKI patients had a relatively good long-term prognosis, with the recovery of renal function. Therefore, the results of this study highlight that risk factor identification may assist in implementing strategies to prevent or limit the progression of AKI, which, in turn, may improve survival. Abbreviations AKI: Acute kidney injury; HTx: Heart transplantation; KDIGO: Kidney Disease: Improving Global Outcomes; RRT: Renal replacement therapy; CPB: Cardiopulmonary bypass; RIFLEL: Risk/Injury/Failure/Loss/End-stage; AKIN: Acute Kidney Injury Network; SCr: Serum creatinine; ANOVA: One-way analysis of covariance; eGFR: estimated glomerular filtration rate; BMI: Body mass index; LVAD: Left ventricular assist device; LVEF: Left ventricular ejection fraction; DCM: Dilated cardiomyopathy; CAD: Coronary artery disease; PCI: percutaneous coronary intervention; IABP: Intra-aortic balloon pump; ECMO: Extracorporeal membrane oxygenation; OR: Odds ratio; CI: Confidence interval. Declarations Acknowledgments We thank Dr. HJ He and Dr. F Li for her assistance in statistical analysis. Authors’ contributions Yiyao Jiang -Writing, Data collection, Statistics and Draft. Xiangrong Kong -Design, Reviewing. Fenlong Xue -Data collection. Honglei Chen -Data collection. Wei Zhou -Data collection. Junwu Chai- Data collection. Fei Wu -Draft. Shanshan Jiang -Draft. Zhilong Li -Statistics. Kai Wang -Writing. All authors read and approved the final manuscript. Funding This work was supported by grants from the National Natural Science Foundation of China (81800214), Natural Science Foundation of Anhui Province (1808085QH236). Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The study was approved by the Institutional Ethical Review Board of Tianjin First Center Hospital. The need for patient consent was waived due to the retrospective study design. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. References Dellgren G , et al. Three decades of heart transplantation in Scandinavia: long-term follow-up. Eur J Heart Fail . 2013;15(3):308-315. De Santo LS , et al. 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Changes in End-Organ Function in Patients With Prolonged Continuous-Flow Left Ventricular Assist Device Support. Ann Thorac Surg. 2017; 103(3): 717-724. Kirklin JK, et al. Seventh INTERMACS annual report: 15,000 patients and counting. J Heart Lung Transplant. 2015; 34(12): 1495-1504. Slaughter MS, et al. HeartWare ventricular assist system for bridge to transplant: combined results of the bridge to transplant and continued access protocol trial. J Heart Lung Transplant. 2013; 32(7): 675-683. Patel AM, et al. Renal failure in patients with left ventricular assist devices. Clin J Am Soc Nephrol. 2013; 8(3): 484-496. Topkara VK, et al. Preoperative Proteinuria and Reduced Glomerular Filtration Rate Predicts Renal Replacement Therapy in Patients Supported With Continuous-Flow Left Ventricular Assist Devices. Circ Heart Fail. 2016; 9(12): e002897. Schiferer A , et al. Acute Kidney Injury and Outcome After Heart Transplantation: Large Differences in Performance of Scoring Systems. Transplantation . 2016; 100(11): 2439-2446. Tjahjono R , Connellan M , Granger E . Predictors of Acute Kidney Injury in Cardiac Transplantation. Transplant Proc . 2016; 48(1): 167-172. Sutherland L , et al. Acute kidney injury after cardiac surgery: A comparison of different definitions. Nephrology (Carlton) . 2020; 25(3):212-218 </ol Tables Table 1. Demographics and Perioperative Characteristics of the HTx Recipients Stratified by eGFR. Overall (n=95) eGFR (ml/min/1.73 m 2 ) P value <30 (n=25) 30-59 (n=61) ≥60 (n=9) Demographic data Age, years 54.31±11.92 58.88±9.75 55.15±9.20 35.89±17.20 0.0007* Sex, men, n (%) 81(85.26) 19(76.00) 54(88.52) 8(88.89) 0.318 BMI (kg/m 2 ) 24.54±3.83 23.89±3.15 24.70±4.08 25.25±3.92 0.575 History of alcohol 29(30.53) 10(40.00) 17(27.87) 2(22.22) 0.464 History of smoking 63(66.32) 16(64.00) 41(67.21) 6(66.67) 0.960 Hypertension 39(41.05) 15(60.00) 21(34.43) 3(33.33) 0.083 Diabetes mellitus 34(35.79) 12(48.00) 19(31.15) 3(33.33) 0.334 Chronic kidney disease 20(21.05) 12(48.00) 6(9.84) 2(22.22) 0.0005* Pretransplant characteristics DCM 38(40.00) 7(28.00) 26(42.62) 5(55.56) 0.279 CAD 27(28.42) 9(36.00) 16(26.23) 2(22.22) 0.604 Valve disease 15(15.79) 3(12.00) 10(16.39) 2(22.22) 0.756 Pre-PCI 11(11.58) 4(16) 7(11.48) 0(0) 0.441 ICD implantation 3(3.16) 2(8.00) 1(1.64) 0(0) 0.267 LVAD implantation 1(1.05) 0(0) 0(0) 1(11.11) 0.008* Cardiac tumor 1(1.05) 0(0) 1(1.64) 0(0) 0.755 EF pre-HTx (%) 28(23,31) 30(24,33) 26(23,30) 25(20,30) 0.257 Creatinine (mg/dL) 1.14(0.95,1.27) 1.60(1.33,1.91) 1.10(0.95,1.22) 0.76(0.70,0.87) <.0001* Intraoperative characteristics CPB duration (min) 225(183,262) 225(180,270) 220(193,255) 210(180,225) 0.822 Blood transfusion (ml) 1440(1100,2100) 1400(1100,2000) 1440(1100,2200) 1640(1000,2050) 0.849 Infusion (ml) 1810(1320,2440) 2000(1505,2580) 1800(1320,2350) 1700(1190,1925) 0.483 Blood loss (ml) 1000(1000,2200) 1500(1000,2500) 1000(1000,2000) 1500(1000,2000) 0.804 Urine volume (ml) 1800(1200,2500) 1300(770,1650) 2000(1300,2500) 2150(2000,2900) 0.001* IABP/ECMO 6(6.32) 4(16.00) 2(3.28) 0(0) 0.065 Postoperative characteristics AKI stage NO-AKI 62(65.26) 16(64.00) 40(65.57) 6(66.67) 0.428 Stage 1 11(11.58) 1(4.00) 9(14.75) 1(11.11) Stage 2 9(9.47) 3(12.00) 4(6.56) 2(22.22) Stage 3 13(13.68) 5(20.00) 8(13.11) 0(0) Urine volume 1 st Day after operation 2200(1980,2805) 2100(1965,2485) 2200(1980,2735) 2525(2115,3320) 0.194 2 nd Day after operation 2125(1765,2505) 1935(1400,2498) 2135(1845,2500) 2425(2005,2970) 0.081 3 rd Day after operation 2110(1860,2050) 2050(1400,2498) 2145(1930,2450) 2305(2050,2440) 0.300 Mechanical ventilation (min) 1080(840,2220) 1920(960,3720) 1040(783,2100) 960(720,1410) 0.134 RRT 16(16.84) 7(28.00) 9(14.75) 0(0) 0.123 Time from operation to discharge (days) 26(22,33) 29(23,37) 26(22,32) 24(20,26) 0.370 Death 15(15.79) 4(16.00) 10(16.39) 1(11.11) 0.921 Mortality in hospital 11(11.58) 4(16.00) 6(9.84) 1(11.11) 0.719 Death within 1 year 3(3.16) 0(0) 3(4.92) 0(0) 0.422 Follow-up days 608(303,1180) 555(341,951) 692(276,1180) 1451(497,2132) 0.199 * P< 0.05; eGFR was calculated using the Chronic Kidney Disease Epidemiology collaboration equation. HTx, Heart transplantation; eGFR, estimated glomerular filtration rate; BMI, body mass index; DCM, dilated cardiomyopathy; CAD, coronary arterial disease; Pre-PCI, previous percutaneous coronary intervention; ICD, implantable cardioverter defibrillator; LVAD, left ventricular assist device; CPB, cardiopulmonary bypass; RRT, renal replacement therapy. Numbers in brackets are interquartile ranges (IQRs). ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables. Table 2. Demographics and Perioperative Characteristics of HTx Recipients Stratified by AKI. AKI (n=33) Non-AKI (n=62) P value Demographic data Age, years 55.12±12.02 53.87±11.94 0.534 < 60 19(57.58) 36(58.06) 0.964 ≥60 14(42.42) 26(41.94) Sex, men, n (%) 31(93.94) 50(80.65) 0.083 BMI (kg/m 2 ) 25.29±4.32 24.14±3.51 0.164 History of alcohol 8(24.24) 21(33.87) 0.335 History of smoking 23(69.70) 40(64.52) 0.613 Hypertension 17(51.52) 22(35.48) 0.133 Diabetes mellitus 14(42.42) 20(32.26) 0.328 Chronic kidney disease 10(30.3) 10(16.13) 0.109 Pretransplant characteristics DCM 8(24.24) 30(48.39) 0.023 CAD 13(39.39) 14(22.58) 0.085 Valve disease 5(15.15) 10(16.13) 0.902 Pre-PCI 7(21.21) 4(6.45) 0.033* ICD implantation 0(0) 3(4.84) 0.202 LVAD implantation 1(3.03) 0(0) 0.347 Cardiac tumor 0(0) 1(1.61) 0.653 EF pre-HTx (%) 28(25,31) 27(22,30) 0.359 Creatinine (mg/dL) 1.14(1,1.27) 1.14(0.95,1.27) 0.617 GFR (ml/min/1.73m 2 ) 38.58(29.74,45.60) 38.05(29.68,46.23) 0.988 <30 9(27.27) 16(25.81) 0.0986 30-59 21(63.64) 40(64.52) ≥60 3(9.09) 6(9.68) Intraoperative characteristics CPB duration (min) 240(210,270) 209(180,240) 0.0149* Blood transfusion (ml) 1470(1300,2000) 1440(1000,2100) 0.630 Infusion (ml) 2050(1350,2980) 1800(1300,2220) 0.108 Blood loss (ml) 1600(1000,3000) 1000(1000,2000) 0.0312* Urine volume (ml) 1500(850,2000) 2000(1300,2700) 0.0006* IABP/ECMO 5(15.15) 1(1.61) 0.0102* Postoperative characteristics Urine volume 1 st Day after operation 2100(1720,2965) 2200(2030,2795) 0.223 2 nd Day after operation 1850(1260,2335) 2197.5(1875,2510) 0.017* 3 rd Day after operation 2015(1260,2155) 2180(2005,2615) 0.0003* RRT 16(48.48) 0(0) <.0001* Mechanical ventilation (min) 1380(840-3780) 1020(780,2080) 0.109 Time from operation to discharge (days) 29(24,51) 25(22,30) 0.022* Death 8(24.24) 7(11.29) 0.101 Mortality in hospital 7(21.21) 4(6.45) 0.038* Death within 1 year 0(0) 3(4.84) 0.549 Follow-up days 510(258,1423) 658.5(382,1162) 0.514 * P< 0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables. Table 3. Demographics and Perioperative Characteristics of HTx Recipients Stratified by RRT Non-AKI without RRT (n=62) AKI without RRT (n=17) AKI with RRT (n=16) P value Demographic data Age, years 53.87±11.94 52.24±14.63 58.19±7.77 0.597 < 60 36(58.06) 10(58.82) 9(56.25) 0.988 ≥60 26(41.94) 7(41.18) 7(43.75) Sex, men, n (%) 5(80.65) 17(100) 14(87.50) 0.135 BMI (kg/m 2 ) 24.14±3.51 25.11±4.52 25.47±4.23 0.368 History of alcohol 21(33.87) 2(11.76) 6(37.50) 0.176 History of smoking 40(64.52) 13(76.47) 10(62.50) 0.616 Hypertension 22(35.48) 9(52.94) 8(50.00) 0.318 Diabetes mellitus 20(32.26) 6(35.29) 8(50.00) 0.422 Chronic kidney disease 10(16.13) 3(16.13) 7(43.75) 0.052 Pretransplant characteristics DCM 30(48.39) 5(29.41) 3(18.75) 0.062 CAD 14(22.58) 5(29.41) 8(50.00) 0.097 Valve disease 10(16.13) 2(11.76) 3(18.75) 0.854 Pre-PCI 4(6.45) 5(29.41) 2(12.50) 0.033* ICD implantation 3(4.84) 0(0) 0(0) 0.442 LVAD implantation 0(0) 1(5.88) 0(0) 0.098 Cardiac tumor 1(1.61) 0(0) 0(0) 0.764 EF pre-HTx (%) 27(22,30) 28(25,30) 28.5(24.5,33.5) 0.571 Creatinine (mg/dL) 1.14(0.95,1.27) 1.14(1.00,1.19) 1.25(1.04,1.51) 0.244 GFR (ml/min/1.73 m 2 ) 38.05(29.68,46.23) 39.18(35.39,47.80) 37.36(24.10,40.43) 0.183 <30 16(25.81) 2(11.76) 7(43.75) 0.189 30-59 40(64.52) 12(70.59) 9(56.25) ≥60 6(9.68) 3(17.65) 0(0) Intraoperative characteristics CPB duration (min) 209(180,240) 210(210,240) 269(232.5,297.5) 0.0088* Blood transfusion (ml) 1440(1000,2100) 1440(1000,1812) 1500(1300,2625) 0.499 Infusion (ml) 1800(1300,2220) 1980(1400,2950) 2055(1285,3025) 0.275 Blood loss (ml) 1000(1000,2000) 1000(1000,2500) 2200(1300,3350) 0.0298* Urine volume (ml) 2000(1300,2700) 1500(1000,2000) 1100(710,2000) 0.0021* IABP/ECMO 1(1.61) 0(0) 5(31.25) <.0001* Postoperative characteristics Urine volume 1 st Day after operation 2200(2030,2795) 2470(2100,3010) 1597.5(521,2214) 0.0016* 2 nd Day after operation 2197.5(1875) 2130(1800,2465) 1253.5(145,2087.5) 0.0020* 3 rd Day after operation 2180(2005,2615) 2090(2000,2265) 1365(75,2112.5) 0.0002* Mechanical ventilation (min) 1020(780,2080) 960(783,1380) 3090(1550,6141) 0.0033* Time from operation to discharge (days) 25(22,30) 28(24,34) 38(24.5,64) 0.029* Death 7(11.29) 0(0) 8(50.00) 0.0001* Mortality in hospital 4(6.45) 0(0) 7(43.75) <.0001* Death within 1 year 3(4.84) 0(0) 0(0) 0.438 Follow-up days 658.5(382,1162) 954(489,2336) 261(24.5,736.5) 0.0028* * P< 0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables Table 4 Univariate and multivariate analysis of characteristics associated with in-hospital mortality Univariate OR 95% CI P value Lower-limit Upper-limit Age, years ≥60 4.333 1.071 17.534 0.0398* CPB duration 1.005 0.999 1.010 0.0940 Blood loss 1.000 0.999 1.000 0.683 Urine volume 1.000 0.999 1.000 0.247 IABP/ECMO 10.125 1.746 58.700 0.0098* AKI 3.904 1.051 14.507 0.042* AKI requiring RRT 11.278 2.740 46.424 0.0008* Multivariate OR 95% CI P value Lower-limit Upper-limit AKI requiring RRT (ref=no-AKI and no-RRT) 11.348 2.418 53.267 0.002* IABP/ECMO 2.302 0.299 17.743 0.424 * P <0.05; OR, odds ratio; CI, confidence interval; CPB, cardiopulmonary bypass; IABP, intra-aortic balloon pump; ECMO, extracorporeal membrane oxygenation; AKI, acute kidney injury; RRT, renal replacement therapy. Table 5 Multivariate model for AKI. N(%) OR 95% CI P value Lower-limit Upper-limit CPB duration <195(ref) 26 (27.37) 1 NA NA NA 195-225 31 (32.63) 1.853 0.477 7.206 0.373 226-265 15 (15.79) 3.674 0.724 18.638 0.116 ≥265 23 (24.21) 11.393 2.183 59.465 0.0039* Urine during operation <1200(ref) 22 (23.16) 1 NA NA NA 1200-1700 25 (26.32) 0.181 0.042 0.774 0.0211* 1701-2300 23 (24.21) 0.514 0.143 1.853 0.309 ≥2300 25 (26.32) 0.031 0.005 0.212 0.0004* * P< 0.05; OR, odds ratio; CI, confidence interval; CPB, cardiopulmonary bypass; NA: not applicable; HR, hazard ratio ; AKI, acute kidney injury; RRT, renal replacement therapy. Cite Share Download PDF Status: Published Journal Publication published 07 Oct, 2020 Read the published version in Journal of Cardiothoracic Surgery → Version 2 posted Editorial decision: Accept 27 Sep, 2020 Editor assigned by journal 23 Sep, 2020 Submission checks completed at journal 22 Sep, 2020 Editor invited by journal 22 Sep, 2020 You are reading this latest preprint version Show more versions 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-29665","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":2734768,"identity":"0aade42c-6a7c-495b-a7d8-d4dc040fd556","order_by":0,"name":"Yiyao Jiang","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yiyao","middleName":"","lastName":"Jiang","suffix":""},{"id":2734769,"identity":"93708384-c18b-4e78-a874-d99ae15ef299","order_by":1,"name":"Xiangrong Kong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYBACCTBpAOMaSPDwMzA2kKKlwkZGsoEoLXBwJs3G4AABh0m29x5+zVNglycfffjYw69th3mMzx9ue/CDwU5OF4dl0jzn0ixnGCQXG55LSzeWBWoxu5HYbtjDkGxshsM6OYkcM4MPBsyJG3t4zKQlwVoY2yR4GA4kbsOnJcGgHqHFuP9gm+QfPFqkJXKMH3wwOJw4n4fHTPLDmTQeA4bENml8tkj2nDFjnGFwPHEDD1uaNDCQeSRuALXIGOD2i8TxHuPPPH+qE+f3MB+T/GEgYc/ff/yZ5JsKOzlcWoCADRw3oOhg5oELGuBSDQbMH0CkfAMDA+MPvApHwSgYBaNgpAIAXDFZhOSRkHUAAAAASUVORK5CYII=","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Xiangrong","middleName":"","lastName":"Kong","suffix":""},{"id":2734770,"identity":"c3e67b99-da75-4234-8a1b-0a6ba1bae27a","order_by":2,"name":"Fenlong Xue","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fenlong","middleName":"","lastName":"Xue","suffix":""},{"id":2734771,"identity":"803954ed-bbd3-481d-989d-3c312cb4891c","order_by":3,"name":"Honglei Chen","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Honglei","middleName":"","lastName":"Chen","suffix":""},{"id":2734772,"identity":"4befbf20-6a14-463a-a7e0-e6a30f47bdc9","order_by":4,"name":"Wei Zhou","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhou","suffix":""},{"id":2734773,"identity":"fe84b98b-8228-4b82-80df-7859fcec2450","order_by":5,"name":"Junwu Chai","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Junwu","middleName":"","lastName":"Chai","suffix":""},{"id":2734774,"identity":"6ebc3a0c-6249-4a77-8854-209160750406","order_by":6,"name":"Fei Wu","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Wu","suffix":""},{"id":2734775,"identity":"a96279d5-3bcd-4485-8ed6-25bd2410763f","order_by":7,"name":"Shanshan Jiang","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shanshan","middleName":"","lastName":"Jiang","suffix":""},{"id":2734776,"identity":"a4f766fb-3531-46ab-9d34-6febc38cdea4","order_by":8,"name":"Zhilong Li","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhilong","middleName":"","lastName":"Li","suffix":""},{"id":2734777,"identity":"429b9940-12a2-49f2-91bb-e49abaa2f968","order_by":9,"name":"Kai Wang","email":"","orcid":"","institution":"Tianjin First Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2020-05-19 04:55:46","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-29665/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-29665/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13019-020-01351-4","type":"published","date":"2020-10-07T12:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":2627535,"identity":"87dd5fed-d24c-4eb6-b0e2-417cd3412baa","added_by":"511b2bc0-d74a-4970-b541-fe819c3d0d40","created_at":"2020-09-25 21:03:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51074,"visible":true,"origin":"","legend":"Kaplan-Meier curves for overall survival. Analysis stratified by eGFR. eGFR, estimated glomerular filtration rate in ml/min/1.73 m2.","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-29665/v2/figure_1.png"},{"id":2627537,"identity":"39aeffd3-417e-430e-9758-a12304e5a4fb","added_by":"511b2bc0-d74a-4970-b541-fe819c3d0d40","created_at":"2020-09-25 21:03:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43852,"visible":true,"origin":"","legend":"Kaplan-Meier curves for overall survival. Analysis stratified by AKI. AKI, acute kidney injury.","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-29665/v2/figure_2.png"},{"id":2627534,"identity":"95b7b4d7-9d10-4d55-a425-2804c235a7cf","added_by":"511b2bc0-d74a-4970-b541-fe819c3d0d40","created_at":"2020-09-25 21:03:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":45212,"visible":true,"origin":"","legend":"Kaplan-Meier curves for overall survival. Analysis stratified by RRT. RRT, renal replacement therapy.","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-29665/v2/figure_3.png"},{"id":13596467,"identity":"dc8afa66-7bfe-4b68-aee2-7d4c3501bfe0","added_by":"auto","created_at":"2021-09-17 05:28:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":541059,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-29665/v2/191e9a13-b581-4d0b-8aba-67d81b8baf0b.pdf"}],"financialInterests":"","formattedTitle":"Incidence, Risk Factors and Clinical Outcomes of Acute Kidney Injury after Heart Transplantation: A Retrospective Single Center Study.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHeart transplantation (HTx) is a generally successful procedure for patients with end-stage heart failure, improving their survival and quality of life [1]. Acute kidney injury (AKI) is a frequent complication following HTx. With an incidence ranging from 14% to 76%, it is a significant contributor to high morbidity and mortality [2-7]. There are various causes of AKI, such as renal hypoperfusion, prolonged cardiopulmonary bypass (CPB), and nephrotoxicity of immunosuppressive drugs [8]. Therefore, there is a need to identify high-risk factors, reduce the life-threatening outcomes of AKI, and enhance the long-term survival rates in HTx patients.\u003c/p\u003e\n\u003cp\u003eScoring systems for the quantification of AKI have been applied in clinical studies. These criteria included the Risk/Injury/Failure/Loss/End-stage (RIFLE) criteria, the Acute Kidney Injury Network (AKIN) criteria, and the Kidney Disease: Improving Global Outcomes (KDIGO) criteria [9-11]. Based on these criteria, AKI can be defined and staged. It is important to note that despite different performances of different scoring systems, a mild to modest form of AKI does not play a significant role in predicting poor long-term outcomes [12]. However, patients who develop severe AKI frequently receive renal replacement therapy (RRT) as a salvage treatment. \u0026nbsp;The need for RRT has been reported to be one of the most important predictors of a poor prognosis after HTx [13]. Although some clinical outcomes associated with AKI requiring RRT have been described, its impact on long-term survival has not been addressed.\u003c/p\u003e\n\u003cp\u003eThe aims of this study were to (1) evaluate the incidence of AKI after HTx in our center by using the KDIGO criteria, (2) identify risk factors for AKI and in-hospital mortality after HTx, and (3) explore long-term survival in AKI patients.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003ePatient population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBetween October 2009 and March 2020, 113 patients were transplanted. According to exclusion criteria, 10 patients were underwent for combined heart-kidney transplant were not included; 8 patients who were lost to follow-up were also excluded. We included 95 patients in the final analysis. All patients were followed in the outpatient department.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerioperative management\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA biatrial technique was performed in the HTx procedure. All patients received methylprednisolone intraoperatively (500 mg when the aortic cross clamp was released) followed by 120 mg q8h intravenous for the first 24 h, 120mg q12h for the second 24h, 120 mg once daily for the third 24h and basiliximab (20 mg loading dose in the operating room and 20 mg the fourth day). On the fourth day postoperation, tacrolimus and mycophenolate mofetil was started at an oral dose of 1.5 mg and 500mg twice daily, respectively. Tacrolimus and mycophenolate mofetil were prescribed for the rest of their lives. Further, dosing was based on tacrolimus whole-blood trough concentrations at 6 a.m (12 h post-dose). A whole-blood tacrolimus trough concentration between 7 and 15 ng/ml was considered in the first 3 months and thereafter tapered towards 5-10 ng/ml. Accompanying immunosuppression comprised corticosteroids, prednisolone was started 28mg orally on the fourth day postoperation, followed by 24mg once daily and tapered off to 8mg once daily orally.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome measure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAKI was classified according to the KDIGO criteria [11]. The KDIGO criteria recognize 3 stages of AKI severity based on serum creatinine (SCr) levels and urine output. The definition of AKI was based on peak creatinine within 7 days postoperation. The administration of loop diuretics is a commonly used method in the postoperative period and in the early management of AKI, at least in patients with volume overload and/or oliguria. Indications for RRT were stage 3 AKI combined with one of the following: hyperkalemia, severe hypervolemia, uncorrectable metabolic acidosis or serious uremia.\u003c/p\u003e\n\u003cp\u003eContinuous variables are presented as mean\u0026plusmn;standard deviation, while categorical or integer variables are presented as number and percentage. To compare values between two groups, Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test was used for normally distributed numerical variables, and Wilcoxon rank test for nonnormally ones. One-way analysis of covariance (ANOVA) or Kruskal-Wallis test was used for comparisons more than two groups. When there was a statistical significance among groups, SNK method was used to perform comparison between groups. Categorical or integer parameters compared by Fisher\u0026rsquo;s exact test or Chi-square test. Other continuous variables were expressed as median and interquartile (25\u003csup\u003eth\u003c/sup\u003e to 75\u003csup\u003eth\u003c/sup\u003e percentile) range and compared by Mann-Whitney U-test or Kruskal-Wallis test. Survival analysis was performed using log-rank test. Cox proportional hazards model were used to identify variables independently associated with mortality. All statistical procedures were performed using SAS 9.4 (SAS Institute Inc. Cary, NC, USA) and GraphPad Prism 5.0 (GraphPad Software Inc., La Jolla, USA). A two-tailed \u003cem\u003eP\u003c/em\u003e value \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTable 1 shows the demographics and perioperative characteristics of the HTx recipients stratified into 3 groups by the estimated glomerular filtration rate (eGFR). Patients in the GFR\u0026lt;30 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e group were older than those in the eGFR\u0026ge;60 ml/min/1.73 m\u003csup\u003e2 \u003c/sup\u003egroup (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), and frequency of chronic kidney disease and the creatinine levels were higher in the GFR\u0026lt;30 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e group than in the other groups (\u003cem\u003eP\u003c/em\u003e=0.0005 and \u003cem\u003eP\u0026lt;\u003c/em\u003e0.0001, respectively). However, there was no difference in body mass index (BMI) or left ventricular ejection fraction (LVEF) among the groups (\u003cem\u003eP\u003c/em\u003e=0.575 and 0.257, respectively). In addition, the three groups had a similar frequency of dilated cardiomyopathy (DCM), coronary artery disease (CAD), valve disease, and pre-percutaneous coronary intervention (PCI) (\u003cem\u003eP\u003c/em\u003e=0.279, 0.604, 0.756 and 0.441, respectively). Intraoperatively, patients in the GFR\u0026lt;30 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e group had a longer duration of CPB and more infusion than the patients in the other groups, but there was no statistical significance (\u003cem\u003eP\u0026gt;\u003c/em\u003e0.05). Although there was decreased urine volume during the operation in the GFR\u0026lt;30 ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e group (\u003cem\u003eP\u003c/em\u003e=0.001), there was no difference in time from operation to discharge, mortality in hospital, death within 1 year, or the incidence of AKI between the groups (\u003cem\u003eP\u003c/em\u003e\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003eOf the 95 HTx recipients who were enrolled, 33 patients fulfilled the criteria for AKI, and 62 patients were assigned to the non-AKI group (Table 2). Although there was no difference in most perioperative variables, the CPB time, blood loss and frequency of application of intra-aortic balloon pump with venoarterial extracorporeal membrane oxygenation (IABP/ECMO) during the operation were higher in the AKI group than in the non-AKI group (\u003cem\u003eP\u003c/em\u003e=0.0149, 0.0312 and 0.0102, respectively). Moreover, the urine volume during and after the operation was lower in the AKI group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.005). The frequency of RRT was higher in the AKI group than in the non-AKI group (\u003cem\u003eP\u0026lt;\u003c/em\u003e0.0001).\u003c/p\u003e\n\u003cp\u003eTable 3 shows the demographics and perioperative characteristics of 95 HTx recipients stratified into 3 groups by post-HTx RRT. Intraoperatively, the AKI with RRT group had a longer CPB time, more blood loss, lower urine volume and a higher frequency of IABP/ECMO than the other groups (\u003cem\u003eP\u003c/em\u003e=0.0088, 0.0298, 0.0021 and \u0026lt;0.0001, respectively). Postoperatively, there were significant differences in urine volume, mechanical ventilation rate and mortality in hospital.\u003c/p\u003e\n\u003cp\u003eThe overall hospital mortality was 11.58%(11/95). The orrcurence of AKI was associated with mortality in hospital (\u003cem\u003eP\u003c/em\u003e=0.0383). Patients requiring RRT had a hospital mortality of 43.75% (7/16) compared with 6.45% (4/62) in those patients without AKI or RRT (Figure 3 and Table 3). The causes of death were as follows: sepsis (n=3), respiratory failure (n=2), cerebral hemorrhage (n=1), pulmonary embolism (n=1), gastrointestinal bleeding (n=1), disseminated intravascular coagulation (n=1), shock (n=1), and 1 patients without diagnosis. Multivariate logistic regression analysis suggested that AKI requiring RRT was a risk factor independently associated with hospital mortality (Table 4).\u003c/p\u003e\n\u003cp\u003eThe median duration of follow-up after hospital discharge was 608 days (interquartile range, 303-1180 days) with a maximum of 3405 days. The clinical outcomes are summarized by eGFR stratification in Figure 1. There were no differences in long-term survival among the 3 groups stratified by eGFR (\u003cem\u003eP\u003c/em\u003e=0.897). When stratified by AKI, there was no difference in the overall 3-year survival rates (\u003cem\u003eP\u003c/em\u003e=0.096) (Figure 2). However, the survival rate was 72.16\u0026plusmn;16.38% in the AKI with RRT group, while the survival rate was 89.43\u0026plusmn;2.33% in the non-AKI without RRT group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) (Figure 3). A total of 4 deaths were observed during the follow-up period. The causes of death within 1 year were as follows: sepsis (n=2) and tumor metastasis (n=1). One patient requiring RRT passed away due to cerebral infarction at 3 years after HTx.\u003c/p\u003e\n\u003cp\u003eThe multivariable model for AKI is summarized in Table 5. When the CPB time is more than 265 min, it was positively related to the occurrence of AKI (OR: 11.393, 95% CI: 2.183 to 59.465,\u003cem\u003e P\u003c/em\u003e=0.0039) . A decreased intraoperative urine volume, less than 1700ml, it may positively correlated with AKI (OR: 0.181, 95% CI: 0.042 to 0.774, \u003cem\u003eP\u003c/em\u003e=0.0211).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our retrospective analysis, we found that AKI was a frequent complication of HTx, with an incidence of 34.7%. We also showed that a relatively short CPB time (\u0026le; 265 min) and increased intraoperative urine volume could prevent the occurrence of AKI. Furthermore, AKI requiring RRT was an independent risk factor for in-hospital mortality after HTx. Finally, AKI requiring RRT was not associated with long-term mortality.\u003c/p\u003e\n\u003cp\u003eSevere AKI is an important independent contributor to mortality in the HTx population. Accumulating evidence indicates that AKI requiring RRT could be a strong predictor of adverse clinical outcomes. In Renata\u0026rsquo;s study, patients with AKI, especially those requiring RRT (46.9%), had higher hospital mortality (16%) than those without AKI [14]. However, after hospital discharge, AKI was not associated with poor long-term outcomes. With a median follow-up after hospital discharge of 6.7 years, overall survival at 1, 5, and 10 years was 95.4%, 85.1%, and 75.4% and 85.2%, 69.8% and 63.5% among patients with AKI stages 2 and 3, respectively [14]. Fortrie\u0026rsquo;s findings showed that one-year mortality rates in patients without AKI and with AKI stages 1, 2, and 3 were 4.8%, 7.6%, 11.8%, and 14.7%, respectively[7]. In an extensive follow-up of 471 HTx patients over a period up to 26 years, no association was found between the development of AKI and long-term mortality or chronic RRT dependence [15]. In this study, we found that mortality in hospital in patients with AKI was 21.21%, and the incidence rate of AKI requiring RRT was 48.48%. Moreover, overall survival in patients without AKI at 1, and 3 years was higher than that in AKI patients.\u003c/p\u003e\n\u003cp\u003eIn contrast to the high overall incidence of AKI, the need for RRT in our study was 16.84%. This is similar to previous studies reporting a need for RRT in 6% to 29% of patients [2, 4, 6]. A recent analysis indicated that AKI requiring RRT had a 1-year mortality rate of 59.2% [16]. In Boyle\u0026rsquo;s study, AKI requiring RRT was associated with a mortality rate of 50% compared to 1.4% in patients without AKI [17]. We estimated an increased risk for in hospital mortality, with an odd ratio of 11.348 in AKI patients requiring RRT. These results could be explained by the fact that patients with severe AKI are less likely to achieve full recovery of kidney function, even with RRT, than patients with mild AKI. In fact, some AKI patients requiring RRT develop at least one other serious complication (sepsis, graft failure, or acute myocardial infarction), which can lead to early mortality during the postoperative care period. In our study, seven patients in AKI with RRT group passed away in hospital. However, there was a nonsignificant tendency toward an increase in long-term mortality in AKI patients requiring RRT, which is consistent with previous reports[3]. Therefore, the impact of RRT appears to be lost at long-term follow-up. This result indicated that recovery of kidney function prior to hospital discharge was associated with decreased long-term mortality risk.\u003c/p\u003e\n\u003cp\u003eThe interactions between the heart and kidney systems have become a matter of great concern [18]. The difference between arterial driving pressure and venous outflow pressure must remain sufficiently large for adequate renal blood flow and glomerular filtration. The low-resistance nature of the renal vasculature and parenchyma and the very low oxygen tension in the outer medulla also explain the unique sensitivity of the kidneys to hypotension-induced injury [2, 19]. Thus, both hemodynamic instability and antecedent hypotension should be considered in the consultative evaluation of a patient with developing AKI.\u003c/p\u003e\n\u003cp\u003eSeveral factors have been suggested to contribute to the development of postoperative AKI. In general, the most common cause in the early postoperative period is ischemic-reperfusion injury [20]. Intraoperatively, maintenance of a mean arterial pressure (MAP) \u0026gt;60-65 mmHg, reduction in CPB time, minimization of blood transfusion and avoidance of nephrotoxic agents may prevent AKI [2, 21]. Moreover, increased central venous pressure (CVP) was associated with a reduced GFR and all-cause mortality. Right atrial pressure strongly predicts the development of AKI early after HTx and can be used as an early AKI indicator [22]. Finally, postoperatively, chloride-restricted fluid management was associated with less AKI and RRT [23]. In our opinion, a relatively short CPB time and increased intraoperative urine volume play important roles in preventing the occurrence of AKI after HTx.\u003c/p\u003e\n\u003cp\u003eWhen AKI occurs, the most important thing is the time of applying RRT. It offers steady fluid removal and their intensity can be easily titrated for prevention or rapid administration of treatment of volume overload. This intervention in the postoperative management can prevent a higher progression of perioperative AKI, and the occurrence of the worst outcomes [24].\u003c/p\u003e\n\u003cp\u003eAlthough left ventricular assist device (LVAD ) is widely applied as a bridge to HTx, kidney dysfunction is common after LVAD implantation. In theory, improvements in cardiac output after implantation of LVAD would be expected to improve renal perfusion. Previous studies shown that the improvement in renal function was seen during the first month postimplantation of LVAD and no further improvements occurred thereafter [25, 26]. However, a decrease in renal function after implantation raising uncertainties about the long-term effects of continuous blood flow on renal function [27, 28]. The incidence of postimplantation AKI is 7%-14% in continuous-flow devices [29]. In addition, RRT is needed in a subset of patients who develop post-LVAD AKI[30]. In our study, a patient with non-pulsatile flow LVAD implantation developed AKI stage 2 before HTx but there is no AKI in post-HTx. We consider that the influence of LVAD on kidney do not affect the treatment effect of HTx.\u003c/p\u003e\n\u003cp\u003eThe performance and usefulness of different AKI scoring systems with regard to mortality vary greatly [31]. The KDIGO criteria are widely applied in the analysis of AKI in HTx patients. However, the emphasis on SCr and urine volume may exaggerate the severity of AKI. In addition, according to the RIFLE criteria, AKI encompasses the entire spectrum of the syndrome, from minor changes in renal function to the requirement of RRT. Thus, AKI does not simply represent acute renal failure but is a more general description [32]. Since the AKIN criteria are not sensitive enough to capture all episodes of AKI in cardiac surgery patients, they are not widely used for HTx patients [33]. We consider to evaluate this issue in future clinical trials.\u003c/p\u003e\n\u003cp\u003eWe acknowledge that several limitations exist in this study. The inherent limitation is that it was a retrospective, single-center study that enrolled a small number of patients. Furthermore, the small sample size made it difficult to detect small effects and prevented the accuracy of multivariate analysis. In addition, patients were relatively old and likely to suffer from comorbid conditions, such as diabetes mellitus and hypertension. These comorbidities may interfere with the analysis of the long-term survival rates in AKI requiring RRT. Finally, the indication for dialysis is standardized; however, to some extent, it depends on the physician treating the individual patient, which may have acted as a confounder in our study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study suggests that AKI is a frequent complication of HTx, and the results demonstrated that AKI requiring RRT following HTx was associated with an increased risk for for in-hospital mortality. However, AKI patients had a relatively good long-term prognosis, with the recovery of renal function. Therefore, the results of this study highlight that risk factor identification may assist in implementing strategies to prevent or limit the progression of AKI, which, in turn, may improve survival.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAKI: Acute kidney injury; HTx: Heart transplantation; KDIGO: Kidney Disease: Improving Global Outcomes; RRT: Renal replacement therapy; CPB: Cardiopulmonary bypass; RIFLEL: Risk/Injury/Failure/Loss/End-stage; AKIN: Acute Kidney Injury Network; SCr: Serum creatinine; ANOVA: One-way analysis of covariance; eGFR: estimated glomerular filtration rate; BMI: Body mass index; LVAD: Left ventricular assist device; LVEF: Left ventricular ejection fraction; DCM: Dilated cardiomyopathy; CAD: Coronary artery disease; PCI: percutaneous coronary intervention; IABP: Intra-aortic balloon pump; ECMO: Extracorporeal membrane oxygenation; OR: Odds ratio; CI: Confidence interval.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Dr. HJ He and Dr. F Li for her assistance in statistical analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYiyao Jiang -Writing, Data collection, Statistics and Draft. Xiangrong Kong -Design, Reviewing. Fenlong Xue -Data collection. Honglei Chen -Data collection. Wei Zhou -Data collection. Junwu Chai- Data collection. Fei Wu -Draft. Shanshan Jiang -Draft. Zhilong Li -Statistics. Kai Wang -Writing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Natural Science Foundation of China (81800214), Natural Science Foundation of Anhui Province (1808085QH236).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Institutional Ethical Review Board of Tianjin First Center Hospital. The need for patient consent was waived due to the retrospective study design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Dellgren%20G%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=23109651\"\u003eDellgren G\u003c/a\u003e, et al. 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The Cardiorenal Syndrome in Heart Failure. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/31735318\"\u003eHeart Fail Clin\u003c/a\u003e. 2020; 16(1): 81-97.\u003c/li\u003e\n\u003cli\u003eBadin J, et al. Relation between mean arterial pressure and renal function in the early phase of shock: a prospective, explorative cohort study. Crit Care. 2011; 15(3):\u003c/li\u003e\n\u003cli\u003eMalek M, Nematbakhsh M. Renal ischemia/reperfusion injury; from pathophysiology to treatment. Journal of Renal Injury Prevention. 2015; 4(2): 20-27.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Leone%20M%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=25888071\"\u003eLeone M\u003c/a\u003e,\u0026nbsp;et al. Optimizing mean arterial pressure in septic shock: a critical reappraisal of the literature. Crit Care. 2015; 19:\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Guven%20G%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=29671040\"\u003eGuven G\u003c/a\u003e,\u0026nbsp;et al.Preoperative right heart hemodynamics predict postoperative acute kidney injury after heart transplantation. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Preoperative+right+heart+hemodynamics++predict+postoperative+acute+kidney+injury++after+heart+transplantation\"\u003eIntensive Care Med\u003c/a\u003e. 2018; 44(5): 588-597.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Yunos%20NM%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=23073953\"\u003eYunos NM\u003c/a\u003e,\u0026nbsp;et al. Association between a chloride-liberal vs chloride-restrictive intravenous fluid administration strategy and kidney injury in critically ill adults. JAMA. 2012; 308(15): 1566\u0026ndash;1572.\u003c/li\u003e\n\u003cli\u003eKwon JT, Jung TE, Lee DH. Predictive risk factors of acute kidney injury after on-pump coronary artery bypass grafting.\u0026nbsp;Ann Transl Med. 2019; 7(3): 44.\u003c/li\u003e\n\u003cli\u003eBrisco MA, et al. Prevalence and prognostic importance of changes in renal function after mechanical circulatory support.\u0026nbsp;Circ Heart Fail. 2014; 7(1): 68-75.\u003c/li\u003e\n\u003cli\u003eYoshioka D, et al. Changes in End-Organ Function in Patients With Prolonged Continuous-Flow Left Ventricular Assist Device Support.\u0026nbsp;Ann Thorac Surg. 2017; 103(3): 717-724.\u003c/li\u003e\n\u003cli\u003eKirklin JK, et al. Seventh INTERMACS annual report: 15,000 patients and counting.\u0026nbsp;J Heart Lung Transplant. 2015; 34(12): 1495-1504.\u003c/li\u003e\n\u003cli\u003eSlaughter MS, et al. HeartWare ventricular assist system for bridge to transplant: combined results of the bridge to transplant and continued access protocol trial.\u0026nbsp;J Heart Lung Transplant. 2013; 32(7): 675-683.\u003c/li\u003e\n\u003cli\u003ePatel AM, et al. Renal failure in patients with left ventricular assist devices.\u0026nbsp;Clin J Am Soc Nephrol. 2013; 8(3): 484-496.\u003c/li\u003e\n\u003cli\u003eTopkara VK, et al. Preoperative Proteinuria and Reduced Glomerular Filtration Rate Predicts Renal Replacement Therapy in Patients Supported With Continuous-Flow Left Ventricular Assist Devices.\u0026nbsp;Circ Heart Fail. 2016; 9(12): e002897.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Schiferer%20A%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=26683512\"\u003eSchiferer A\u003c/a\u003e,\u0026nbsp;et al. Acute Kidney Injury and Outcome After Heart Transplantation: Large Differences in Performance of Scoring Systems. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Acute+Kidney+Injury+and+Outcome+After+Heart+Transplantation:+Large+Differences+in+Performance+of+Scoring+Systems\"\u003eTransplantation\u003c/a\u003e. 2016; 100(11): 2439-2446.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Tjahjono%20R%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=26915863\"\u003eTjahjono R\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Connellan%20M%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=26915863\"\u003eConnellan M\u003c/a\u003e,\u0026nbsp;\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Granger%20E%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=26915863\"\u003eGranger E\u003c/a\u003e. Predictors of Acute Kidney Injury in Cardiac Transplantation. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/26915863\"\u003eTransplant Proc\u003c/a\u003e. 2016; 48(1): 167-172.\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=Sutherland%20L%5BAuthor%5D\u0026amp;cauthor=true\u0026amp;cauthor_uid=31587419\"\u003eSutherland L\u003c/a\u003e,\u0026nbsp;et al. Acute kidney injury after cardiac surgery: A comparison of different definitions. \u003ca href=\"https://www.ncbi.nlm.nih.gov/pubmed/31587419\"\u003eNephrology (Carlton)\u003c/a\u003e. 2020; 25(3):212-218\u003c/li\u003e\n\u003c/ol"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographics and Perioperative Characteristics of the HTx Recipients Stratified by eGFR.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"629\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"111\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(n=95)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"3\" width=\"339\"\u003e\n\u003cp\u003e\u003cstrong\u003eeGFR (ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"65\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;30 (n=25)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e\u003cstrong\u003e30-59 (n=61)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026ge;60 (n=9)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eAge, years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e54.31\u0026plusmn;11.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e58.88\u0026plusmn;9.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e55.15\u0026plusmn;9.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e35.89\u0026plusmn;17.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.0007*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eSex, men, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e81(85.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e19(76.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e54(88.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e8(88.89)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.318\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e24.54\u0026plusmn;3.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e23.89\u0026plusmn;3.15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e24.70\u0026plusmn;4.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e25.25\u0026plusmn;3.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.575\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eHistory of alcohol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e29(30.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e10(40.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e17(27.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2(22.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.464\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eHistory of smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e63(66.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e16(64.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e41(67.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e6(66.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.960\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e39(41.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e15(60.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e21(34.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e3(33.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.083\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eDiabetes mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e34(35.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e12(48.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e19(31.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e3(33.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.334\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eChronic kidney disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e20(21.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e12(48.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e6(9.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2(22.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.0005*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003e\u003cstrong\u003ePretransplant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eDCM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e38(40.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e7(28.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e26(42.62)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e5(55.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.279\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eCAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e27(28.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e9(36.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e16(26.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2(22.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.604\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eValve disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e15(15.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3(12.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e10(16.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2(22.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.756\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003ePre-PCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e11(11.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4(16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e7(11.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.441\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eICD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3(3.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2(8.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1(1.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.267\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eLVAD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1(1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1(11.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.008*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eCardiac tumor\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1(1.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1(1.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.755\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eEF pre-HTx (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e28(23,31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e30(24,33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e26(23,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e25(20,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.257\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1.14(0.95,1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1.60(1.33,1.91)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1.10(0.95,1.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0.76(0.70,0.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003e\u003cstrong\u003eIntraoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eCPB duration (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e225(183,262)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e225(180,270)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e220(193,255)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e210(180,225)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.822\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eBlood transfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1440(1100,2100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1400(1100,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1440(1100,2200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1640(1000,2050)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.849\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eInfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1810(1320,2440)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2000(1505,2580)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1800(1320,2350)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1700(1190,1925)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.483\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eBlood loss (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1000(1000,2200)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1500(1000,2500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1000(1000,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1500(1000,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.804\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eUrine volume (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1800(1200,2500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1300(770,1650)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2000(1300,2500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2150(2000,2900)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eIABP/ECMO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e6(6.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4(16.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2(3.28)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.065\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003e\u003cstrong\u003ePostoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003eAKI stage\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eNO-AKI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e62(65.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e16(64.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e40(65.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e6(66.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.428\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eStage 1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e11(11.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1(4.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e9(14.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1(11.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"65\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eStage 2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e9(9.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3(12.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4(6.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2(22.22)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eStage 3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e13(13.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e5(20.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e8(13.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\" width=\"629\"\u003e\n\u003cp\u003eUrine volume\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003e1\u003csup\u003est \u003c/sup\u003eDay after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2200(1980,2805)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2100(1965,2485)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2200(1980,2735)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2525(2115,3320)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.194\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2125(1765,2505)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1935(1400,2498)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2135(1845,2500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2425(2005,2970)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.081\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2110(1860,2050)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2050(1400,2498)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e2145(1930,2450)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e2305(2050,2440)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.300\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eMechanical ventilation (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1080(840,2220)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1920(960,3720)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e1040(783,2100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e960(720,1410)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.134\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eRRT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e16(16.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e7(28.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e9(14.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.123\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eTime from operation to discharge (days)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e26(22,33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e29(23,37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e26(22,32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e24(20,26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.370\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eDeath\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e15(15.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4(16.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e10(16.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1(11.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.921\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eMortality in hospital\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e11(11.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e4(16.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e6(9.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1(11.11)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.719\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eDeath within 1 year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3(3.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e3(4.92)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.422\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"111\"\u003e\n\u003cp\u003eFollow-up days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e608(303,1180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e555(341,951)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"113\"\u003e\n\u003cp\u003e692(276,1180)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"112\"\u003e\n\u003cp\u003e1451(497,2132)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e0.199\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u003cem\u003e P\u0026lt;\u003c/em\u003e0.05; eGFR was calculated using the Chronic Kidney Disease Epidemiology collaboration equation. HTx, Heart transplantation; eGFR, estimated glomerular filtration rate; BMI, body mass index; DCM, dilated cardiomyopathy; CAD, coronary arterial disease; Pre-PCI, previous percutaneous coronary intervention; ICD, implantable cardioverter defibrillator; LVAD, left ventricular assist device; CPB, cardiopulmonary bypass; RRT, renal replacement therapy. Numbers in brackets are interquartile ranges (IQRs). ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Demographics and Perioperative Characteristics of HTx Recipients Stratified by AKI.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"568\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e\u003cstrong\u003eAKI (n=33)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003eNon-AKI (n=62)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" width=\"568\"\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eAge, years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e55.12\u0026plusmn;12.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e53.87\u0026plusmn;11.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.534\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u0026lt; 60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e19(57.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e36(58.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"142\"\u003e\n\u003cp\u003e0.964\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e14(42.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e26(41.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eSex, men, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e31(93.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e50(80.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.083\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e25.29\u0026plusmn;4.32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e24.14\u0026plusmn;3.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.164\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHistory of alcohol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e8(24.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e21(33.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.335\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHistory of smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e23(69.70)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e40(64.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.613\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e17(51.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e22(35.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.133\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eDiabetes mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e14(42.42)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e20(32.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.328\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eChronic kidney disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e10(30.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e10(16.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.109\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" width=\"568\"\u003e\n\u003cp\u003e\u003cstrong\u003ePretransplant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eDCM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e8(24.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e30(48.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.023\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eCAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e13(39.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e14(22.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.085\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eValve disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e5(15.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e10(16.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.902\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003ePre-PCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e7(21.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e4(6.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.033*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eICD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e3(4.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.202\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eLVAD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1(3.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.347\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eCardiac tumor\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1(1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.653\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eEF pre-HTx (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e28(25,31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e27(22,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.359\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1.14(1,1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1.14(0.95,1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.617\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eGFR (ml/min/1.73m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e38.58(29.74,45.60)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e38.05(29.68,46.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.988\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u0026lt;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e9(27.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e16(25.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"142\"\u003e\n\u003cp\u003e0.0986\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e30-59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e21(63.64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e40(64.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e3(9.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e6(9.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" width=\"568\"\u003e\n\u003cp\u003e\u003cstrong\u003eIntraoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eCPB duration (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e240(210,270)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e209(180,240)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.0149*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eBlood transfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1470(1300,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1440(1000,2100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.630\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eInfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e2050(1350,2980)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1800(1300,2220)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.108\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eBlood loss (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1600(1000,3000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1000(1000,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.0312*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eUrine volume (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1500(850,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e2000(1300,2700)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.0006*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eIABP/ECMO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e5(15.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1(1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.0102*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" width=\"568\"\u003e\n\u003cp\u003e\u003cstrong\u003ePostoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\" width=\"568\"\u003e\n\u003cp\u003eUrine volume\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e1\u003csup\u003est \u003c/sup\u003eDay after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e2100(1720,2965)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e2200(2030,2795)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.223\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1850(1260,2335)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e2197.5(1875,2510)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.017*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e2015(1260,2155)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e2180(2005,2615)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.0003*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eRRT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e16(48.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eMechanical ventilation (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e1380(840-3780)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1020(780,2080)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.109\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eTime from operation to discharge (days)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e29(24,51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e25(22,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.022*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eDeath\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e8(24.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e7(11.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eMortality in hospital\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e7(21.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e4(6.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.038*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eDeath within 1 year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e3(4.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.549\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"151\"\u003e\n\u003cp\u003eFollow-up days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"133\"\u003e\n\u003cp\u003e510(258,1423)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e658.5(382,1162)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e0.514\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u003cem\u003e P\u0026lt;\u003c/em\u003e0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3. Demographics and Perioperative Characteristics of HTx Recipients Stratified by RRT\u003c/p\u003e\n\u003ctable border=\"1\" width=\"710\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e\u003cstrong\u003eNon-AKI without RRT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(n=62)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e\u003cstrong\u003eAKI without RRT (n=17)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e\u003cstrong\u003eAKI with RRT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(n=16)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"710\"\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic data\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eAge, years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e53.87\u0026plusmn;11.94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e52.24\u0026plusmn;14.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e58.19\u0026plusmn;7.77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.597\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026lt; 60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e36(58.06)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e10(58.82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e9(56.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"110\"\u003e\n\u003cp\u003e0.988\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e26(41.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e7(41.18)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e7(43.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eSex, men, n (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e5(80.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e17(100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e14(87.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.135\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e24.14\u0026plusmn;3.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e25.11\u0026plusmn;4.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e25.47\u0026plusmn;4.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.368\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eHistory of alcohol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e21(33.87)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2(11.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e6(37.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.176\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eHistory of smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e40(64.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e13(76.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e10(62.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.616\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e22(35.48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e9(52.94)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e8(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.318\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eDiabetes mellitus\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e20(32.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e6(35.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e8(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.422\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eChronic kidney disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e10(16.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e3(16.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e7(43.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.052\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"710\"\u003e\n\u003cp\u003e\u003cstrong\u003ePretransplant characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eDCM\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e30(48.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e5(29.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e3(18.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.062\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e14(22.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e5(29.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e8(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.097\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eValve disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e10(16.13)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2(11.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e3(18.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003ePre-PCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e4(6.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e5(29.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e2(12.50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.033*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eICD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e3(4.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.442\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eLVAD implantation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1(5.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.098\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCardiac tumor\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1(1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.764\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eEF pre-HTx (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e27(22,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e28(25,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e28.5(24.5,33.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.571\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1.14(0.95,1.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1.14(1.00,1.19)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1.25(1.04,1.51)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.244\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eGFR (ml/min/1.73 m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e38.05(29.68,46.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e39.18(35.39,47.80)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e37.36(24.10,40.43)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.183\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026lt;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e16(25.81)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2(11.76)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e7(43.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"3\" width=\"110\"\u003e\n\u003cp\u003e0.189\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e30-59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e40(64.52)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e12(70.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e9(56.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e\u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e6(9.68)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e3(17.65)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"710\"\u003e\n\u003cp\u003e\u003cstrong\u003eIntraoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCPB duration (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e209(180,240)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e210(210,240)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e269(232.5,297.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0088*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eBlood transfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1440(1000,2100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1440(1000,1812)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1500(1300,2625)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.499\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eInfusion (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1800(1300,2220)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1980(1400,2950)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e2055(1285,3025)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.275\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eBlood loss (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1000(1000,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1000(1000,2500)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e2200(1300,3350)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0298*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eUrine volume (ml)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e2000(1300,2700)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e1500(1000,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1100(710,2000)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0021*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eIABP/ECMO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1(1.61)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e5(31.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"710\"\u003e\n\u003cp\u003e\u003cstrong\u003ePostoperative characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\" width=\"710\"\u003e\n\u003cp\u003eUrine volume\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e1\u003csup\u003est \u003c/sup\u003eDay after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e2200(2030,2795)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2470(2100,3010)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1597.5(521,2214)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0016*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e2197.5(1875)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2130(1800,2465)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1253.5(145,2087.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0020*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e Day after operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e2180(2005,2615)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e2090(2000,2265)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e1365(75,2112.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0002*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMechanical ventilation (min)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e1020(780,2080)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e960(783,1380)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e3090(1550,6141)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0033*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eTime from operation to discharge (days)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e25(22,30)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e28(24,34)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e38(24.5,64)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.029*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eDeath\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e7(11.29)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e8(50.00)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMortality in hospital\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e4(6.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e7(43.75)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u0026lt;.0001*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eDeath within 1 year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e3(4.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e0(0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.438\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eFollow-up days\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"156\"\u003e\n\u003cp\u003e658.5(382,1162)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"136\"\u003e\n\u003cp\u003e954(489,2336)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"149\"\u003e\n\u003cp\u003e261(24.5,736.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.0028*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u003cem\u003e P\u0026lt;\u003c/em\u003e0.05; ANOVA was applied to the BMI variable because of its normal distribution. The Kruskal-Wallis test was used to compare other variables\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Univariate and multivariate analysis of characteristics associated with in-hospital mortality\u003c/p\u003e\n\u003ctable border=\"1\" width=\"555\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"184\"\u003e\n\u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"82\"\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"3\" width=\"205\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"84\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"103\"\u003e\n\u003cp\u003eLower-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003eUpper-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eAge, years \u0026ge;60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e4.333\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e1.071\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e17.534\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.0398*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eCPB duration\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e1.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e0.999\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e1.010\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.0940\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eBlood loss\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e0.999\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.683\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eUrine volume\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e0.999\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e1.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.247\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eIABP/ECMO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e10.125\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e1.746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e58.700\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.0098*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eAKI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e3.904\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e1.051\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e14.507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.042*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eAKI requiring RRT\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e11.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e2.740\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e46.424\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.0008*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"184\"\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"82\"\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"3\" width=\"205\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 70px;\" rowspan=\"2\" width=\"84\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"103\"\u003e\n\u003cp\u003eLower-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003eUpper-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 59px;\"\u003e\n\u003ctd style=\"height: 59px;\" width=\"184\"\u003e\n\u003cp\u003eAKI requiring RRT\u003c/p\u003e\n\u003cp\u003e(ref=no-AKI and no-RRT)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"82\"\u003e\n\u003cp\u003e11.348\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"102\"\u003e\n\u003cp\u003e2.418\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e53.267\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"84\"\u003e\n\u003cp\u003e0.002*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"184\"\u003e\n\u003cp\u003eIABP/ECMO\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"82\"\u003e\n\u003cp\u003e2.302\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"102\"\u003e\n\u003cp\u003e0.299\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"102\"\u003e\n\u003cp\u003e17.743\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"84\"\u003e\n\u003cp\u003e0.424\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e* P\u003c/em\u003e\u0026lt;0.05; OR, odds ratio; CI, confidence interval; CPB, cardiopulmonary bypass; IABP, intra-aortic balloon pump; ECMO, extracorporeal membrane oxygenation; AKI, acute kidney injury; RRT, renal replacement therapy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 5 Multivariate model for AKI.\u003c/p\u003e\n\u003ctable border=\"1\" width=\"636\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" width=\"142\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"105\"\u003e\n\u003cp\u003e\u003cstrong\u003eN(%)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"76\"\u003e\n\u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"219\"\u003e\n\u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd rowspan=\"2\" width=\"95\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e value\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eLower-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eUpper-limit\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003eCPB duration\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u0026lt;195(ref)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e26 (27.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e195-225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e31 (32.63)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.853\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e7.206\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.373\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e226-265\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e15 (15.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e3.674\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.724\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e18.638\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.116\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u0026ge;265\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e23 (24.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e11.393\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e2.183\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e59.465\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.0039*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" width=\"246\"\u003e\n\u003cp\u003eUrine during operation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u0026lt;1200(ref)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e22 (23.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1200-1700\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e25 (26.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.181\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e0.774\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.0211*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e1701-2300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e23 (24.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.514\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.143\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e1.853\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.309\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"142\"\u003e\n\u003cp\u003e\u0026ge;2300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"105\"\u003e\n\u003cp\u003e25 (26.32)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e0.031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"110\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"109\"\u003e\n\u003cp\u003e0.212\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e0.0004*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u003cem\u003e P\u0026lt;\u003c/em\u003e0.05; OR, odds ratio; CI, confidence interval; CPB, cardiopulmonary bypass; NA: not applicable; HR, hazard ratio ; AKI, acute kidney injury; RRT, renal replacement therapy.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\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":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Acute kidney injury, Heart transplantation, Mortality, Outcomes","lastPublishedDoi":"10.21203/rs.3.rs-29665/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-29665/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjectives: \u003c/strong\u003eThis study aimed to identify the incidence rate of Acute kidney injury (AKI) in our center and predict in-hospital mortality and long-term survival after heart transplantation (HTx). \u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eThis single-center, retrospective study from October 2009 and March 2020 analyzed the pre-, intra-, and postoperative characteristics of 95 patients who underwent HTx. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Risk factors were analyzed by multivariable logistic regression models. The log-rank test was used to compare long-term survival. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e : Thirty-three (34.7%) patients developed AKI. The mortality in hospital in HTx patients with and without AKI were 21.21% and 6.45%, respectively (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Recipients in AKI who required renal replacement therapy (RRT) had a hospital mortality rate of 43.75% compared to 6.45% in those without AKI or RRT (\u003cem\u003eP\u0026lt;\u003c/em\u003e0.0001). A long cardiopulmonary bypass (CPB) time (OR:11.393, 95% CI: 2.183 to 59.465, \u003cem\u003eP\u003c/em\u003e=0.0039) was positively related to the occurrence of AKI. A high intraoperative urine volume (OR: 0.031, 95% CI: 0.005 to 0.212, \u003cem\u003eP\u003c/em\u003e=0.0004) was negatively correlated with AKI. AKI requiring RRT (OR, 11.348; 95% CI, 2.418-53.267, \u003cem\u003eP\u003c/em\u003e=0.002) was a risk factor for mortality in hospital. Overall survival in patients without AKI at 1 and 3 years was not different from that in patients with AKI (\u003cem\u003eP\u003c/em\u003e=0.096).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eAKI is common after HTx. AKI requiring RRT could contribute powerful prognostic information to predict mortality in hospital. A long CPB time and low intraoperative urine volume are associated with the occurrence of AKI.\u003c/p\u003e","manuscriptTitle":"Incidence, Risk Factors and Clinical Outcomes of Acute Kidney Injury after Heart Transplantation: A Retrospective Single Center Study.","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2020-09-25 20:08:31","doi":"10.21203/rs.3.rs-29665/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2020-09-27T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-09-23T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-09-22T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-09-22T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2020-05-22 21:16:04","doi":"10.21203/rs.3.rs-29665/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2020-08-23T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-06-21T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-06-21T12:00:00+00:00","index":1,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-06-21T12:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-06-21T12:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-06-21T12:00:00+00:00","index":1,"fulltext":"Recommendation: Accept\nForm responses:\n---\n\nComments to Author:\n---\nI think well designed paaper.\nThe volume is small group. but the message is well delivered.\nThe CRRT is more useful to treat aki and reduced morbidity and mortality.\nI think the most important thing is the time of applying CRRT. So I recommened early apply is more helpful aki patients.\n\nMy comment is copy of my paper.\nA prompt intervention in the postoperative management, especially avoiding additional renal insults and optimizing volume status, can prevent a higher progression of perioperative AKI, and the occurrence of the worst outcomes, including in-hospital mortality. Thus, intensive renal preservation during the perioperative period appears to provide sufficient renal protection. Continuous renal replacement therapy (CRRT) offers steady fluid removal and their intensity can be easily titrated for prevention or rapid administration of treatment of volume overload.\n\nEarly diagnosis of AKI is important; firstly, it will help identify patients for nephrology\nreferral and secondly, it will allow for timely interventions, which could improve outcomes. Several studies have actually shown that early nephrology referral for patients who develop AKI result in improved outcomes\n\nThank you for work hard.\n* Level of interest: **An article of limited interest**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare that I have no competing interests'**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. 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/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\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"},{"type":"editorInvitedReview","content":"","date":"2020-06-21T12:00:00+00:00","index":2,"fulltext":"Recommendation: Reject\nForm responses:\n---\n\nComments to Author:\n---\nSUMMARY:\nAuthors present a single-center retrospective study of 72 patients undergoing HTx between October 2009 and December 2019. The objective of the study was to to evaluate evaluate the incidence of AKI after HTx using the KDIGO criteria, identify risk factors for AKI and mortality after HTx, and explore long-term survival in AKI patients requiring RRT. Authors found an incidence of AKI of 36.1%; there was no difference in the overall 5-year survival rates between patients without or with postoperative AKI. Instead, survival rate was significantly lower in patients requiring postoperative RRT. The multivariable analysis identified long CPB time as an independent risk factor for occurrence of AKI; an increased intraoperative urine volume was negatively correlated with AKI. Postoperative RRT was identified as a strong predictive factor of postoperative death. Authors concluded that AKI is common after HTx and adversely impacts early mortality; AKI requiring RRT could contribute powerful prognostic information to predict short-term survival.\n\nCONSIDERATIONS:\n- The number of the patients included in the study is relatively small.\n- Authors have not reported values of mean and median follow-up. However, looking at Kaplan-Meier curves, it is clear that authors have focused their attention to short- and mid-term follow-up (not long-term follow-up as reported); moreover, patients at risk at 5 years are very few.\n- Authors have not reported any information about in-hospital mortality and influence of AKI or RRT on this outcome.\n- One of the main finding of the study is that RRT is associated with a worse late survival, emerging as a strong predictor of death. However, looking at Kaplan-Meier curve (Figure 3), it seems that RRT has an important effect on peri-operative mortality, with a low-rate of late deaths. In this setting, it is mandatory to explore the effect of AKI and RRT on this outcome, reporting the number of late deaths and their association with study variables.\n- Another important variable not evaluated in the study is the presence of LVAD; it is well-known that the absence of pulsatile flow in LVAD-patients could influence the renal perfusion after HTx. Please comment on it.\n- Long CPB was identified as the independent risk factor for postoperative AKI. What does \"long CPB\" mean? Have you tried to identify a cut-off value?\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* Level of interest: **An article of limited interest**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare that I have no competing interests**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. 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/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\n"},{"type":"editorInvitedReview","content":"","date":"2020-06-21T12:00:00+00:00","index":3,"fulltext":"Recommendation: Major Revision\nForm responses:\n---\n\nComments to Author:\n---\nThe authors have created a well constructed study on a topic that is very important to heart transplant surgeons and cardiologist. I have several issues that should be addressed before the paper should be published. First, this topic is not new and has been well explored and discussed. Why do the authors feel that this topic should be readdressed in a single center? Second, the sample size is small with only 87 patients included? Have the authors considered adding more years to the study to get more patients or make this a multi-center study? The number of patients in this study limits the impact and power of the study. Finally, there is a high incidence of AKI in your study population and I think that is not consistent which most centers.\nOnce again the study is well constructed but the topic is very well reviewed.* Level of interest: **An article of importance in its field**\n* Quality of written English: **Acceptable**\n* Declaration of competing interests: **I declare that I have no competing interest.**\n* I agree to the open peer review policy of the journal. I understand that my name will be included on my report to the authors and, if the manuscript is accepted for publication, my named report including any attachments I upload will be posted on the website along with the authors' responses. 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/). I understand that any comments which I do not wish to be included in my named report can be included as confidential comments to the editors, which will not be published.: **\nI agree to the open peer review policy of the journal**\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"},{"type":"editorAssigned","content":"","date":"2020-05-19T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-05-18T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-05-18T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-05-18T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ca504609-5a7b-430c-8abf-9bd144cc58a1","owner":[],"postedDate":"September 25th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":106045,"name":"Cardiothoracic Surgery"}],"tags":[],"updatedAt":"2020-10-11T15:02:34+00:00","versionOfRecord":{"articleIdentity":"rs-29665","link":"https://doi.org/10.1186/s13019-020-01351-4","journal":{"identity":"journal-of-cardiothoracic-surgery","isVorOnly":false,"title":"Journal of Cardiothoracic Surgery"},"publishedOn":"2020-10-07 12:00:00","publishedOnDateReadable":"October 7th, 2020"},"versionCreatedAt":"2020-09-25 20:08:31","video":"","vorDoi":"10.1186/s13019-020-01351-4","vorDoiUrl":"https://doi.org/10.1186/s13019-020-01351-4","workflowStages":[]},"version":"v2","identity":"rs-29665","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-29665","identity":"rs-29665","version":["v2"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}