Intraoperative central venous pressures related to early graft function in deceased donor kidney transplant recipients with low immunological risks

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We retrospectively analyzed 202 recipients who underwent deceased donor kidney transplantation from March 2010 to December 2020. Anesthetic monitoring data during the intraoperative period was analyzed at 5-minute intervals, and basic clinical parameters were evaluated. The mean recipient age was 46.6 ± 10.3 years, and the mean donor age was 41.7 ± 12.7 years. Anesthetic time averaged 285.8 ± 70.2 minutes, and operation time averaged 223.1 ± 44.0 minutes. The incidence of SGF was 11.8%, and the incidence of DGF was 3.9%. Mean central venous pressures (CVPs) were higher in recipients with SGF or DGF (11.7 mmHg) compared to those with immediate graft function (9.7 mmHg). Higher CVP was identified as an independent risk factor for SGF or DGF (odds ratio 1.219, p = 0.006). This study suggests that intraoperative monitoring of CVP is crucial for predicting short-term graft function in deceased donor kidney transplantation and should be managed to prevent excessive fluid intake. Health sciences/Nephrology Health sciences/Risk factors Figures Figure 1 Introduction Kidney transplantation (KT) has been known as the treatment of choice for patients with end-stage renal disease. Especially for patients on waiting list who have to receive a deceased donor KT, delayed graft function (DGF) is one of the most common complication, defined as the need for the dialysis within the first week after transplantation 1 . The incidence of DGF varies among studies and is definition dependent, and DGF occurs more frequently in deceased donor KT than living donor KT 2,3 . For kidney transplant recipients, DGF had a 41% increased risk of graft loss and was associated with a 38% relative increase in the risk of acute rejection 1,4–6 . Furthermore, cases where some level of graft dysfunction is observed even without progression to DGF are called slow graft function (SGF). SGF refers to a state in which serum creatinine decreases slowly but does not require dialysis, and has many different definitions for each study 7–9 . Importantly, SGF is also related to acute rejection and poor long-term graft survival 7,10 . Mainly, it has been shown that the occurrence of SGF of DGF is closely related to donor factors, but perioperative hemodynamic management is also known to be related to the occurrence and prevention of SGF or DGF 11,12 . Proper management of fluid levels is crucial in order to minimize perioperative complications, as hypovolemia can contribute to additional kidney damage while excessive fluid therapy may lead to pulmonary edema related to right ventricular dysfunction 13 . Therefore, intraoperative anesthetic management of kidney transplant patients is a critical aspect that significantly influences both patient and graft outcomes. As indicators for appropriate fluid management, central venous pressure (CVP) has traditionally been used as one of the anesthesiological monitoring elements for effective fluid management during transplant surgery 14–16 . The prior way of fluid management during KT was to evaluate the volume status based on CVP and increase CVP by providing a sufficient amount of fluids. However, according to a recently published guideline, there is insufficient evidence to target high CVP with large volume fluid management 17 . On behalf of targeting high CVP, individualized goal-directed fluid therapy, which is not based on CVP, is suggested to be the preferred method for optimizing the fluid management 18 . However, it is also true that there is a possibility of hypoperfusion occurring when individualization is attempted, so there are questions about whether a target should be set when performing fluid management 19 . In this study, we analyzed the CVP value during KT surgery, analyzed the correlation between CVP and SGF or DGF occurrence under conventional fluid management. Results Total 202 recipients with low immunological risks received deceased donor KT. The mean age was 46.6 years and male recipients were 119 (58.9%). According to criteria mentioned before, the incidence of SGF was 22 (10.9%) and the incidence of DGF was 8 (3.8%). 172 recipients recovered their graft function immediately (85.1%). The basic characteristics between IGF and SGF + DGF group were expressed in Table 1 . The mean age of patients were not different and more male patients were in SGF + DGF group (70.0%). The mean body mass index (BMI) was significantly higher in SGF + DGF group than IGF group (21.9 ± 2.9 vs 23.9 ± 3.5, p = 0.001). The mean duration of anesthesia time were 283.3 ± 46.9 minutes in IGF group and 300.3 ± 145.0 minutes in SGF + DGF group and the mean operation time were 223.2 ± 46.5 minutes in IFG group and 222.6 ± 56.1 minutes in SGF + DGF group. Mean total ischemic time of two groups were 286.4 ± 92.9 minutes in IGF group and 317.9 ± 90.8 minutes in SGF + DGF group. In terms of ischemic time, warm ischemic time of SGF + DGF group was significantly longer than IGF group (54.1 ± 23.5 vs 43.4 ± 13.1 minutes, p = 0.021). More total fluid was administered in the SGF + DGF group than IFG group (4133.8 ± 1136.5 vs 3645.5 ± 954.5, p = 0.013). In addition, total bleeding and transfusion amounts were greater in SGF + DGF group. The mean donor creatinine levels were 0.83 mg/dL in IGF group and 1.1 mg/dL in SGF + DGF group ( p < 0.001). Also, there was no difference in 1- and 3-year graft survival rates depending on whether SGF or DGF occurred or not (98.8% vs 100.0% at 1-year and 97.1% vs 96.7% at 3-year, respectively). Table 1 Basic characteristics between two groups IGF group (n = 172) SGF + DGF group (n = 30) P value Recipients variables Age (yr) 46.4 ± 10.5 47.7 ± 8.8 0.515 Male sex 98 (56.9%) 21 (70.0%) 0.228 Body mass index (kg/m 2 ) 21.9 ± 2.9 23.9 ± 3.5 0.001 Dialysis modality 1.000 Hemodialysis 152 (87.9%) 26 (86.7%) Peritoneal dialysis 21 (12.1%) 4 (13.3%) Dialysis duration (month) 101.04 ± 262.3 45.7 ± 51.6 0.277 PRA positivity at transplantation Class I 30 (17.4%) 8 (26.7%) 0.368 Class II 30 (17.4%) 9 (30.0%) 0.367 HLA mismatches 3.5 ± 2.0 3.3 ± 1.7 0.552 Operation time (minutes) 223.2 ± 46.5 222.6 ± 56.1 0.951 Anesthesia time (minutes) 283.3 ± 46.9 300.3 ± 145.0 0.528 Total ischemic time (minutes) 286.4 ± 92.9 317.9 ± 90.8 0.087 Warm ischemic time (minutes) 43.4 ± 13.1 54.1 ± 23.5 0.021 Cold ischemic time (minutes) 242.9 ± 90.9 263.8 ± 91.1 0.248 Total fluid intake during operation (mL) 3645.5 ± 954.5 4133.8 ± 1136.5 0.013 Total fluid intake per body weight (mL/kg) 62.2 ± 17.5 61.9 ± 17.1 0.955 Total bleeding (mL) 379.5 ± 340.8 654.3 ± 990.1 0.014 Transfusion during operation (mL) 423.0 ± 285.7 697.2 ± 853.9 0.369 Graft weight (gram) 207.7 ± 40.1 202.7 ± 62.7 0.677 Donor variables Age (yr) 41.7 ± 13.2 41.3 ± 10.8 0.886 Male sex 113 (65.3%) 19 (63.3%) 0.833 Donor creatinine level (mg/dL) 0.83 ± 0.31 1.1 ± 0.27 0.001 The continuous variable were expressed by mean ± Standard deviation and number of cases with percentages were for the categorical variables. PRA = panel reactive antibody. Intraoperative CVP changes Among intraoperative variables, CVP, systolic blood pressure (SBP), mean arterial pressure (MAP) were measured and analyzed for evaluating risk factors. The change in mean CVP during operation in the IGF group and SGF + DGF group is shown graphically in Fig. 1 . Mean CVPs at baseline were 9.7 mmHg in recipients with IGF group and 11.7 mmHg in recipients with SGF or DGF group. The mean CVP values of SGF + DGF group were significantly high up to 30 minutes before reperfusion, including the baseline value. After reperfusion, there was no significant difference between two groups, but SGF or DGF group still had a higher mean CVP value. Overall, an overall increase in CVP was seen in both groups throughout operation. When the cut off value of baseline CVP was set according to normal range of CVP in all patients and divided into groups above 12mmHg and below, SGF or DGF occurrence occurred significantly more when baseline CVP was above 12mmHg ( p = 0.025). Risk factors for occurrence of SGF or DGF In a logistic regression test conducted including all relevant factors to identify risk factors, baseline CVP, recipient’s BMI, donor serum creatinine, warm ischemic time and total fluid intake were associated with SGF or DGF development (Table 2 ). Among these variables, only baseline CVP and fluid intake related to anesthesiological factors during operation were selected and a logistic regression test was performed, and it was found that baseline CVP was a significantly involved risk factor in the development of SGF or DGF. (Odds ratio 1.186, p = 0.006). Table 2 Logistic regression analysis of anesthesiologic risk factors developing SGF or DGF Variables Unadjusted OR P value Adjusted OR P value Age (per 1 year) 1.013 0.513 Baseline CVP (mmHg) 1.172 0.008 1.186 0.006 Recipient’s BMI (per 1 kg/m 2 ) 1.223 0.001 Donor Cr (per 1 mg/dL) 12.229 0.001 Warm ischemic time (per min) 1.038 0.002 Total fluid intake (per liter) 1.522 0.018 1.393 0.094 CVP = central venous pressure, SBP = systolic blood pressure, Cr = creatinine, The relationship between baseline CVP and right ventricular systolic pressure (RVSP) To determine the relationship between CVP and pulmonary HTN, we retrospectively examined the echocardiogram results from preoperative period. Among them, the RVSP value, which is related to pulmonary hypertension, was analyzed. The RVSP value was significantly higher in the patient group with a CVP of 12 mmHg or more ( p = 0.049). As a result of dividing the RVSP into 35, 40, and 45 mmHg standards, the overall probability of RVSP being high was higher in the group with higher CVP, but the result was not significant (Table 3 ). Table 3 Association between baseline central venous pressure and right ventricular systolic pressure CVP 12mmHg (n = 35*) P value Mean Right ventricular systolic pressure 31.1 ± 7.6 34.1 ± 8.9 0.049 RVSP below or above 35mmHg 90 / 31 21 / 14 0.137 RVSP below or above 40mmHg 106 / 15 26 / 9 0.065 RVSP below or above 45mmHg 117 / 4 32 / 3 0.188 CVP, central venous pressure; RVSP, right ventricular systolic pressure *: Of the total 202 patients, 56 patients without RVSP data were excluded. Discussion In this retrospective study, we investigated CVP values during KT surgery, and analyzed the correlation between CVP and SGF or DGF occurrence under conventional fluid management. The relationship between CVP and early renal graft function has been reported for a long time 20 . Hypovolemia along with prolonged ischemic time and previous acute tubular necrosis can lead to further graft injury during operation. To optimize volume status of kidney transplant recipients, CVP was used as indicator for fluid management. Many studies suggested that maintaining proper CVP during operation especially at reperfusion period should be achieved by administrating fluid excessively 21 . However, according to recent studies, fluid management targeting CVP is not effective in preventing SGF or DGF and conventional treatment that supplies large fluid is not necessary is gaining persuasiveness 17 . Similar to these suggestions, the results of this study showed that when conventional fluid management was performed, SGF or DGF occurred more frequently in kidney transplant recipients with higher CVP. Therefore, this study can support the recommendation that larger volume fluid management targeting higher CVP is no longer beneficial. In the perioperative setting, the primary objective is to prevent tissue hypoxia, which is a significant factor leading to organ dysfunction. Conventional indicators such as CVP may appear normal even in cases of tissue hypoxia, making them unreliable for predicting a potential mismatch between oxygen supply and demand. This is especially true if these indicators are not evaluated alongside perfusion markers like cardiac output, lactates, and central venous saturation 22–24 . Therefore, it is true natural that tissue perfusion cannot be measured by targeting CVP alone. However, the reason why CVP or other variables have been used so far is because it is relatively easy to measure the responsiveness to fluid administration during operation. Previously, investigations into the relationship between CVP and DGF have predominantly centered on single-point CVP measurements. These measurements were typically taken at specific junctures, such as baseline, reperfusion, or post-anesthesia, to establish this connection. In our study, however, CVP was monitored continuously throughout the surgical procedure, allowing us to track CVP fluctuations in both the SGF + DGF group and the IGF group. This methodology distinguishes our study from others in the field. As a result of measuring and comparing CVP at various time points, including baseline CVP, it was found that when conventional fluid management was implemented, CVP continued to rise, peaked around the time of reperfusion, and was maintained. This is interpreted because most conventional fluid management is performed by targeting blood pressure or CVP at reperfusion period. Considering these changes in CVP, it can be seen that the value of CVP itself is more important than the CVP value at a specific point in time. Since there is no difference in the amount of fluid intake between the SGF + DGF and IGF groups, the value of baseline CVP can be considered to increase proportionally according to fluid intake. Therefore, if CVP is within the normal range based on baseline CVP, it could be concluded that increasing fluid intake to increase CVP does not help early graft function recovery. High CVP values have a negative effect on graft function due to complications that may occur when fluid overload occurs when CVP is high 25 . Additionally, since most KT candidate patients have a high risk of developing cardiac complications, fluid overload may make them more vulnerable to heart-related complications. Therefore, in the pre-anesthesia evaluation performed before kidney transplant surgery, it would be important to examine indicators that can predict problems caused by volume overload more accurately than the CVP value, such as RVSP. RVSP represents pulmonary hypertension, which is related to right ventricular function 26,27 . According to guidelines, more than 35 mmHg of RVSP indicates pulmonary hypertension [ 26 ]. As RVSP value increases, the severity of pulmonary hypertension is also increased. In this study, we investigated the RVSP values obtained from preoperative echocardiography results and compared them with the patients' CVP results. As a result, it was found that the average RVSP value was significantly higher in patients with CVP of 12 mmHg or higher. Therefore, if the baseline CVP value is high enough to be outside the normal range, it is expected that the RVSP value will also be high, and it is important to perform passive fluid intake during the operation to prevent cardio-pulmonary complications that may occur. Several limitations of our study were existed. First, this study was conducted at a single center in Korea and was conducted in an area with a relatively low incidence of SGF or DGF. Therefore, in this study where the incidence of DGF is important, it can be said that the low incidence of DGF is a disadvantage in studying DGF risk factors. Second, although all echocardiograms measuring RVSP were performed before surgery, the date of surgery and the date of examination were different for each patient, which may slightly reduce the reliability of the research results. Finally, our study population was relatively small, compared with similar studies on evaluating CVP and graft function. In this retrospective study, higher CVP was significant intraoperative risk factors for SGF or DGF during deceased donor kidney transplantation. Other factors, such as high body mass index, prolonged ischemic time, and higher donor creatinine level were also revealed as risk factors. Considering anesthesiological factors that can be monitored during operation, CVP are important factors affecting short-term function after kidney transplantation and should be monitored to prevent excessive fluid intake. Methods Study population We retrospectively analyzed the recipients who underwent deceased donor kidney transplantation from March 2010 to December 2020. Before evaluation, we excluded recipients with extended criteria donor, donor creatinine level above 1.5 mg/dL and acute rejection within 2 weeks after transplantation to consider the impact of the donor's condition on the early graft function. After exclusion, total 202 recipients were consisted of the eligible population for evaluation. Immunosuppressive regimen consisted of basiliximab as induction therapy, tacrolimus, mycophenolate mofetil and corticosteroids. Basiliximab was administered just prior to transplantation and 4 days after transplantation. Tacrolimus was initiated at 2 days before KT with an initial dose of 0.05–0.1 mg/kg. Steroids were administrated intravenously at 500 mg on the day of transplantation, 250 mg on the next day after transplantation, and were gradually tapered to a maintenance dose of more than 5 mg a day until 6-months post-transplant. Anesthetic protocol and fluid management In the operating room, all patients were monitored with electrocardiogram (ECG), non-invasive blood pressure, pulse oximetry, and bispectral index (BIS). General anesthesia was achieved by administering 2 mg/kg propofol and 2–3 mcg/kg fentanyl intravenously, followed by the administration of 0.6 mg/kg rocuronium. After the loss of consciousness, sevoflurane was started with 3–5 vol% until endotracheal intubation. After intubation, the anesthetic gas was changed to desflurane, and desflurane was adjusted to maintain BIS between 40–60 at 5–7 vol%. A tidal volume of 8 mL/kg of the patients’ ideal body weight was set, with a respiratory rate of 12–14 bpm to maintain normocapnia conditions. Furthermore, a radial artery catheter was placed, and a central venous catheter was positioned to allow hemodynamic and CVP monitoring. All anesthesiologic variables including heart rate, arterial blood pressure, O 2 saturation, CVP and respiratory rate were monitored and recorded every 5 minutes in the electronic medical record chart. The fluid management strategy involved administering 10–20 mL/kg/h of a combination of 0.9% normal saline, 0.45% half saline, and 5% human albumin throughout the entire surgical procedure. When severe hypotensive episodes (systolic blood pressure < 100 mmHg or mean arterial pressure < 65 mmHg) occurred, ephedrine and phenylephrine were considered the preferred vasopressor for management of hypotension during operation. All patients received 20 mg of furosemide 5 minutes before vascular declamping and 500 mg of methylprednisone at reperfusion intravenously. Study outcomes and data collection The primary outcome of this study was incidence of DGF and SGF. The definition of DGF was the need for dialysis within 7 days after transplantation, and the definition of SGF was serum creatinine level greater than 3.0 mg/dL on post-operative day 5 7 . To investigate the incidence of SGF, serum creatinine levels and urine volume were collected until discharge. Patients whose renal function recovered immediately after transplantation were classified into immediate graft function (IGF) group, and patients who developed SGF or DGF were classified into one group and the values between the two groups were compared. In addition, we evaluated 1 and 3 year graft, patient survival rates in this study. Intraoperative hemodynamic factors were recorded in the electronic medical record every 5 minutes, but the time from the start of surgery to reperfusion was different for each patient. Therefore, we unified these data based on the reperfusion time and collected records from 1 hour and 30 minutes before reperfusion to 1 hour after reperfusion. Additionally, results of echocardiogram performed within 1 year before transplant surgery were collected in all patients for identifying patients who may be more susceptible to elevated CVP. Statistical analysis For categorical variables, data were expressed as a number of patients and a percentage of derived groups, analyzed by Pearson’s χ 2 test and Fisher’s exact test. Continuous variables were expressed as a mean ± standard deviation and analyzed by using the student’s t -test and Mann-whitney test. Logistic regression analysis was used to confirm independent risk factors for the development of SGF or DGF. The P -value less than 0.05 was considered significant. Data analysis was conducted using SPSS version 20.0 (SPSS Inc., Chicago, IL, USA). Ethics This study was approved by the Ajou University Hospital Institutional Review Board (AJOUIRB-MDB-2020-387). Patients authorized the use of their health records for research and had waived informed consent because this study was a retrospective study. For the deceased donor kidney transplants, informed consent was obtained either from the donor previously or from a relative or kin at the time of transplantation. This retrospective study was conducted in accordance with the principles of the Declaration of Helsinki. Also, this study was conducted in accordance with the Declaration of Istanbul on organ trafficking and transplant tourism. This study did not involve organs or tissues procured from prisoners. Declarations Author Contribution Jun Bae Bang and Hyo Eun Ahn contributed to the conceptualization, methodology, formal analysis, and investigation of the study. Hyo Eun Ahn was responsible for writing the original draft of the manuscript. Jun Bae Bang reviewed and edited the manuscript, supervised the project, and acquired the necessary funding and resources. Both authors read and approved the final manuscript Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Yarlagadda, S. G. et al. Marked variation in the definition and diagnosis of delayed graft function: a systematic review. Nephrol Dial Transplant 23, 2995–3003, doi: 10.1093/ndt/gfn158 (2008). Schröppel, B. & Legendre, C. Delayed kidney graft function: from mechanism to translation. Kidney Int 86, 251–258, doi: 10.1038/ki.2014.18 (2014). Irish, W. D. et al. Nomogram for predicting the likelihood of delayed graft function in adult cadaveric renal transplant recipients. J Am Soc Nephrol 14, 2967–2974, doi: 10.1097/01.asn.0000093254.31868.85 (2003). Pérez Fontán, M. et al. Outcome of grafts with long-lasting delayed function after renal transplantation. Transplantation 62, 42–47, doi: 10.1097/00007890-199607150-00009 (1996). Ojo, A. O., Wolfe, R. A., Held, P. J., Port, F. K. & Schmouder, R. L. Delayed graft function: risk factors and implications for renal allograft survival. Transplantation 63, 968–974, doi: 10.1097/00007890-199704150-00011 (1997). Butala, N. M., Reese, P. P., Doshi, M. D. & Parikh, C. R. Is delayed graft function causally associated with long-term outcomes after kidney transplantation? Instrumental variable analysis. Transplantation 95, 1008–1014, doi: 10.1097/TP.0b013e3182855544 (2013). Humar, A. et al. Effect of initial slow graft function on renal allograft rejection and survival. Clin Transplant 11, 623–627 (1997). Zeraati, A. A., Naghibi, M., Kianoush, S. & Ashraf, H. Impact of slow and delayed graft function on kidney graft survival between various subgroups among renal transplant patients. Transplant Proc 41, 2777–2780, doi: 10.1016/j.transproceed.2009.07.038 (2009). Lee, S. Y. et al. Clinical significance of slow recovery of graft function in living donor kidney transplantation. Transplantation 90, 38–43, doi: 10.1097/TP.0b013e3181e065a2 (2010). Humar, A. et al. Risk factors for slow graft function after kidney transplants: a multivariate analysis. Clin Transplant 16, 425–429, doi: 10.1034/j.1399-0012.2002.02055.x (2002). Campos, L. et al. Do intraoperative hemodynamic factors of the recipient influence renal graft function? Transplant Proc 44, 1800–1803, doi: 10.1016/j.transproceed.2012.05.042 (2012). Snoeijs, M. G. et al. Recipient hemodynamics during non-heart-beating donor kidney transplantation are major predictors of primary nonfunction. Am J Transplant 7, 1158–1166, doi: 10.1111/j.1600-6143.2007.01744.x (2007). Chappell, D., Jacob, M., Hofmann-Kiefer, K., Conzen, P. & Rehm, M. A rational approach to perioperative fluid management. Anesthesiology 109, 723–740, doi: 10.1097/ALN.0b013e3181863117 (2008). Aulakh, N. K. et al. Influence of hemodynamics and intra-operative hydration on biochemical outcome of renal transplant recipients. J Anaesthesiol Clin Pharmacol 31, 174–179, doi: 10.4103/0970-9185.155144 (2015). Bacchi, G. et al. The influence of intraoperative central venous pressure on delayed graft function in renal transplantation: a single-center experience. Transplant Proc 42, 3387–3391, doi:10.1016/j.transproceed.2010.08.042 (2010). Othman, M. M., Ismael, A. Z. & Hammouda, G. E. The impact of timing of maximal crystalloid hydration on early graft function during kidney transplantation. Anesth Analg 110, 1440–1446, doi: 10.1213/ANE.0b013e3181d82ca8 (2010). Wagener, G. et al. Fluid Management During Kidney Transplantation: A Consensus Statement of the Committee on Transplant Anesthesia of the American Society of Anesthesiologists. Transplantation 105, 1677–1684, doi: 10.1097/tp.0000000000003581 (2021). Cavaleri, M. et al. Perioperative Goal-Directed Therapy during Kidney Transplantation: An Impact Evaluation on the Major Postoperative Complications. J Clin Med 8, doi: 10.3390/jcm8010080 (2019). Harbell, M. W., Kraus, M. B., Bucker-Petty, S. A. & Harbell, J. W. Intraoperative fluid management and kidney transplantation outcomes: A retrospective cohort study. Clin Transplant 35, e14489, doi: 10.1111/ctr.14489 (2021). Thomsen, H. S., Lokkegaard, H. & Munck, O. Influence of normal central venous pressure on onset of function in renal allografts. Scand J Urol Nephrol 21, 143–145, doi: 10.3109/00365598709180310 (1987). Calixto Fernandes, M. H., Schricker, T., Magder, S. & Hatzakorzian, R. Perioperative fluid management in kidney transplantation: a black box. Crit Care 22, 14, doi: 10.1186/s13054-017-1928-2 (2018). Magder, S. Current tools for assessing heart function and perfusion adequacy. Curr Opin Crit Care 20, 294–300, doi: 10.1097/mcc.0000000000000100 (2014). Marik, P. E. & Cavallazzi, R. Does the central venous pressure predict fluid responsiveness? An updated meta-analysis and a plea for some common sense. Crit Care Med 41, 1774–1781, doi: 10.1097/CCM.0b013e31828a25fd (2013). Magder, S. How to use central venous pressure measurements. Curr Opin Crit Care 11, 264–270, doi: 10.1097/01.ccx.0000163197.70010.33 (2005). Srivastava, D. et al. Effect of intraoperative transesophageal Doppler-guided fluid therapy versus central venous pressure-guided fluid therapy on renal allograft outcome in patients undergoing living donor renal transplant surgery: a comparative study. J Anesth 29, 842–849, doi: 10.1007/s00540-015-2046-4 (2015). Rudski, L. G. et al. Guidelines for the echocardiographic assessment of the right heart in adults: a report from the American Society of Echocardiography endorsed by the European Association of Echocardiography, a registered branch of the European Society of Cardiology, and the Canadian Society of Echocardiography. J Am Soc Echocardiogr 23, 685–713; quiz 786 – 688, doi: 10.1016/j.echo.2010.05.010 (2010). Subias, P. E. Comments on the 2015 ESC/ERS Guidelines for the Diagnosis and Treatment of Pulmonary Hypertension. Rev Esp Cardiol (Engl Ed) 69, 102–108, doi: 10.1016/j.rec.2015.11.030 (2016). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Sep, 2024 Reviews received at journal 14 Sep, 2024 Reviewers agreed at journal 11 Sep, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviews received at journal 19 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers invited by journal 05 Jul, 2024 Editor assigned by journal 05 Jul, 2024 Editor invited by journal 26 Jun, 2024 Submission checks completed at journal 26 Jun, 2024 First submitted to journal 22 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4459030","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":327321135,"identity":"93597cbe-7f18-49e3-b380-a5a5e42dc1de","order_by":0,"name":"Hyoeun Ahn","email":"","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hyoeun","middleName":"","lastName":"Ahn","suffix":""},{"id":327321138,"identity":"e472dbdf-47b2-4b91-83f1-f83a6d7954e1","order_by":1,"name":"Jun Bae Bang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACA4YzDAYf/9gAmYyNB4jWUjizIQ2kpYFYLTwMn3kbDoM5xGkxZzx7cAPvjvN2a9sPA22psYkmqMWy4VyygeSZ28nbziQCtRxLy20g6LADZ8wMDNhuJ5sdAGphbDhMlBbzHwls55LNzj8kXouBwcG2A3ZmN4i1BeiXBMOGM8kJZjeAtiQQ4xdzibMHjP9U2NmbnU9/+OBDjQ1hLQwSB8BUIlhlAkHlIMAPMdWeKMWjYBSMglEwMgEAkq5P/7MMUtEAAAAASUVORK5CYII=","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"Bae","lastName":"Bang","suffix":""}],"badges":[],"createdAt":"2024-05-22 07:40:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4459030/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4459030/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-75474-2","type":"published","date":"2024-10-18T15:57:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60705683,"identity":"8fcb9fd4-7161-4672-9c7d-07d89eb61cc5","added_by":"auto","created_at":"2024-07-19 19:22:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":212822,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of CVP during operation between two groups. IGF: immediate graft function; SGF: slow graft function; DGF; delyed graft function\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4459030/v1/4c2429421e0f0d1aed7beb15.jpeg"},{"id":67149560,"identity":"52fdbec3-fa23-45f4-a40f-f873e11a6c20","added_by":"auto","created_at":"2024-10-21 16:13:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":694897,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4459030/v1/ba0ce325-cb79-46d0-ae47-8133c724526b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Intraoperative central venous pressures related to early graft function in deceased donor kidney transplant recipients with low immunological risks","fulltext":[{"header":"Introduction","content":"\u003cp\u003eKidney transplantation (KT) has been known as the treatment of choice for patients with end-stage renal disease. Especially for patients on waiting list who have to receive a deceased donor KT, delayed graft function (DGF) is one of the most common complication, defined as the need for the dialysis within the first week after transplantation \u003csup\u003e1\u003c/sup\u003e. The incidence of DGF varies among studies and is definition dependent, and DGF occurs more frequently in deceased donor KT than living donor KT \u003csup\u003e2,3\u003c/sup\u003e. For kidney transplant recipients, DGF had a 41% increased risk of graft loss and was associated with a 38% relative increase in the risk of acute rejection \u003csup\u003e1,4\u0026ndash;6\u003c/sup\u003e. Furthermore, cases where some level of graft dysfunction is observed even without progression to DGF are called slow graft function (SGF). SGF refers to a state in which serum creatinine decreases slowly but does not require dialysis, and has many different definitions for each study \u003csup\u003e7\u0026ndash;9\u003c/sup\u003e. Importantly, SGF is also related to acute rejection and poor long-term graft survival \u003csup\u003e7,10\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMainly, it has been shown that the occurrence of SGF of DGF is closely related to donor factors, but perioperative hemodynamic management is also known to be related to the occurrence and prevention of SGF or DGF \u003csup\u003e11,12\u003c/sup\u003e. Proper management of fluid levels is crucial in order to minimize perioperative complications, as hypovolemia can contribute to additional kidney damage while excessive fluid therapy may lead to pulmonary edema related to right ventricular dysfunction \u003csup\u003e13\u003c/sup\u003e. Therefore, intraoperative anesthetic management of kidney transplant patients is a critical aspect that significantly influences both patient and graft outcomes. As indicators for appropriate fluid management, central venous pressure (CVP) has traditionally been used as one of the anesthesiological monitoring elements for effective fluid management during transplant surgery \u003csup\u003e14\u0026ndash;16\u003c/sup\u003e. The prior way of fluid management during KT was to evaluate the volume status based on CVP and increase CVP by providing a sufficient amount of fluids. However, according to a recently published guideline, there is insufficient evidence to target high CVP with large volume fluid management \u003csup\u003e17\u003c/sup\u003e. On behalf of targeting high CVP, individualized goal-directed fluid therapy, which is not based on CVP, is suggested to be the preferred method for optimizing the fluid management \u003csup\u003e18\u003c/sup\u003e. However, it is also true that there is a possibility of hypoperfusion occurring when individualization is attempted, so there are questions about whether a target should be set when performing fluid management \u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we analyzed the CVP value during KT surgery, analyzed the correlation between CVP and SGF or DGF occurrence under conventional fluid management.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTotal 202 recipients with low immunological risks received deceased donor KT. The mean age was 46.6 years and male recipients were 119 (58.9%). According to criteria mentioned before, the incidence of SGF was 22 (10.9%) and the incidence of DGF was 8 (3.8%). 172 recipients recovered their graft function immediately (85.1%). The basic characteristics between IGF and SGF\u0026thinsp;+\u0026thinsp;DGF group were expressed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean age of patients were not different and more male patients were in SGF\u0026thinsp;+\u0026thinsp;DGF group (70.0%). The mean body mass index (BMI) was significantly higher in SGF\u0026thinsp;+\u0026thinsp;DGF group than IGF group (21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9 \u003cem\u003evs\u003c/em\u003e 23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). The mean duration of anesthesia time were 283.3\u0026thinsp;\u0026plusmn;\u0026thinsp;46.9 minutes in IGF group and 300.3\u0026thinsp;\u0026plusmn;\u0026thinsp;145.0 minutes in SGF\u0026thinsp;+\u0026thinsp;DGF group and the mean operation time were 223.2\u0026thinsp;\u0026plusmn;\u0026thinsp;46.5 minutes in IFG group and 222.6\u0026thinsp;\u0026plusmn;\u0026thinsp;56.1 minutes in SGF\u0026thinsp;+\u0026thinsp;DGF group. Mean total ischemic time of two groups were 286.4\u0026thinsp;\u0026plusmn;\u0026thinsp;92.9 minutes in IGF group and 317.9\u0026thinsp;\u0026plusmn;\u0026thinsp;90.8 minutes in SGF\u0026thinsp;+\u0026thinsp;DGF group. In terms of ischemic time, warm ischemic time of SGF\u0026thinsp;+\u0026thinsp;DGF group was significantly longer than IGF group (54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5 \u003cem\u003evs\u003c/em\u003e 43.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 minutes, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021). More total fluid was administered in the SGF\u0026thinsp;+\u0026thinsp;DGF group than IFG group (4133.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1136.5 \u003cem\u003evs\u003c/em\u003e 3645.5\u0026thinsp;\u0026plusmn;\u0026thinsp;954.5, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013). In addition, total bleeding and transfusion amounts were greater in SGF\u0026thinsp;+\u0026thinsp;DGF group. The mean donor creatinine levels were 0.83 mg/dL in IGF group and 1.1 mg/dL in SGF\u0026thinsp;+\u0026thinsp;DGF group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Also, there was no difference in 1- and 3-year graft survival rates depending on whether SGF or DGF occurred or not (98.8% vs 100.0% at 1-year and 97.1% vs 96.7% at 3-year, respectively).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic characteristics between two groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIGF group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;172)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSGF\u0026thinsp;+\u0026thinsp;DGF group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRecipients variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.7\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (56.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (70.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis modality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemodialysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e152 (87.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (86.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeritoneal dialysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDialysis duration (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101.04\u0026thinsp;\u0026plusmn;\u0026thinsp;262.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;51.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePRA positivity at transplantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHLA mismatches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.552\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOperation time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e223.2\u0026thinsp;\u0026plusmn;\u0026thinsp;46.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222.6\u0026thinsp;\u0026plusmn;\u0026thinsp;56.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnesthesia time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e283.3\u0026thinsp;\u0026plusmn;\u0026thinsp;46.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300.3\u0026thinsp;\u0026plusmn;\u0026thinsp;145.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal ischemic time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e286.4\u0026thinsp;\u0026plusmn;\u0026thinsp;92.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317.9\u0026thinsp;\u0026plusmn;\u0026thinsp;90.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWarm ischemic time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;23.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCold ischemic time (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242.9\u0026thinsp;\u0026plusmn;\u0026thinsp;90.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e263.8\u0026thinsp;\u0026plusmn;\u0026thinsp;91.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal fluid intake during operation (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3645.5\u0026thinsp;\u0026plusmn;\u0026thinsp;954.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4133.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1136.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal fluid intake per body weight (mL/kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.2\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.9\u0026thinsp;\u0026plusmn;\u0026thinsp;17.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal bleeding (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e379.5\u0026thinsp;\u0026plusmn;\u0026thinsp;340.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e654.3\u0026thinsp;\u0026plusmn;\u0026thinsp;990.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransfusion during operation (mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e423.0\u0026thinsp;\u0026plusmn;\u0026thinsp;285.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e697.2\u0026thinsp;\u0026plusmn;\u0026thinsp;853.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraft weight (gram)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207.7\u0026thinsp;\u0026plusmn;\u0026thinsp;40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202.7\u0026thinsp;\u0026plusmn;\u0026thinsp;62.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDonor variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.7\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (65.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (63.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonor creatinine level (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eThe continuous variable were expressed by mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard deviation and number of cases with percentages were for the categorical variables.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003ePRA\u0026thinsp;=\u0026thinsp;panel reactive antibody.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eIntraoperative CVP changes\u003c/h2\u003e \u003cp\u003eAmong intraoperative variables, CVP, systolic blood pressure (SBP), mean arterial pressure (MAP) were measured and analyzed for evaluating risk factors. The change in mean CVP during operation in the IGF group and SGF\u0026thinsp;+\u0026thinsp;DGF group is shown graphically in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Mean CVPs at baseline were 9.7 mmHg in recipients with IGF group and 11.7 mmHg in recipients with SGF or DGF group. The mean CVP values of SGF\u0026thinsp;+\u0026thinsp;DGF group were significantly high up to 30 minutes before reperfusion, including the baseline value. After reperfusion, there was no significant difference between two groups, but SGF or DGF group still had a higher mean CVP value. Overall, an overall increase in CVP was seen in both groups throughout operation. When the cut off value of baseline CVP was set according to normal range of CVP in all patients and divided into groups above 12mmHg and below, SGF or DGF occurrence occurred significantly more when baseline CVP was above 12mmHg (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors for occurrence of SGF or DGF\u003c/h2\u003e \u003cp\u003eIn a logistic regression test conducted including all relevant factors to identify risk factors, baseline CVP, recipient\u0026rsquo;s BMI, donor serum creatinine, warm ischemic time and total fluid intake were associated with SGF or DGF development (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among these variables, only baseline CVP and fluid intake related to anesthesiological factors during operation were selected and a logistic regression test was performed, and it was found that baseline CVP was a significantly involved risk factor in the development of SGF or DGF. (Odds ratio 1.186, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLogistic regression analysis of anesthesiologic risk factors developing SGF or DGF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted OR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (per 1 year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.513\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline CVP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecipient\u0026rsquo;s BMI (per 1 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDonor Cr (per 1 mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWarm ischemic time (per min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal fluid intake (per liter)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.094\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCVP\u0026thinsp;=\u0026thinsp;central venous pressure, SBP\u0026thinsp;=\u0026thinsp;systolic blood pressure, Cr\u0026thinsp;=\u0026thinsp;creatinine,\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eThe relationship between baseline CVP and right ventricular systolic pressure (RVSP)\u003c/h2\u003e \u003cp\u003eTo determine the relationship between CVP and pulmonary HTN, we retrospectively examined the echocardiogram results from preoperative period. Among them, the RVSP value, which is related to pulmonary hypertension, was analyzed. The RVSP value was significantly higher in the patient group with a CVP of 12 mmHg or more (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049). As a result of dividing the RVSP into 35, 40, and 45 mmHg standards, the overall probability of RVSP being high was higher in the group with higher CVP, but the result was not significant (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between baseline central venous pressure and right ventricular systolic pressure\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCVP\u0026thinsp;\u0026lt;\u0026thinsp;12 mmHg\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;121*)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCVP\u0026thinsp;\u0026gt;\u0026thinsp;12mmHg\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;35*)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean Right ventricular systolic pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVSP below or above 35mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90 / 31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 / 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVSP below or above 40mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 / 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 / 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRVSP below or above 45mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 / 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 / 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eCVP, central venous pressure; RVSP, right ventricular systolic pressure\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*: Of the total 202 patients, 56 patients without RVSP data were excluded.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this retrospective study, we investigated CVP values during KT surgery, and analyzed the correlation between CVP and SGF or DGF occurrence under conventional fluid management. The relationship between CVP and early renal graft function has been reported for a long time \u003csup\u003e20\u003c/sup\u003e. Hypovolemia along with prolonged ischemic time and previous acute tubular necrosis can lead to further graft injury during operation. To optimize volume status of kidney transplant recipients, CVP was used as indicator for fluid management. Many studies suggested that maintaining proper CVP during operation especially at reperfusion period should be achieved by administrating fluid excessively \u003csup\u003e21\u003c/sup\u003e. However, according to recent studies, fluid management targeting CVP is not effective in preventing SGF or DGF and conventional treatment that supplies large fluid is not necessary is gaining persuasiveness \u003csup\u003e17\u003c/sup\u003e. Similar to these suggestions, the results of this study showed that when conventional fluid management was performed, SGF or DGF occurred more frequently in kidney transplant recipients with higher CVP. Therefore, this study can support the recommendation that larger volume fluid management targeting higher CVP is no longer beneficial.\u003c/p\u003e \u003cp\u003eIn the perioperative setting, the primary objective is to prevent tissue hypoxia, which is a significant factor leading to organ dysfunction. Conventional indicators such as CVP may appear normal even in cases of tissue hypoxia, making them unreliable for predicting a potential mismatch between oxygen supply and demand. This is especially true if these indicators are not evaluated alongside perfusion markers like cardiac output, lactates, and central venous saturation \u003csup\u003e22\u0026ndash;24\u003c/sup\u003e. Therefore, it is true natural that tissue perfusion cannot be measured by targeting CVP alone. However, the reason why CVP or other variables have been used so far is because it is relatively easy to measure the responsiveness to fluid administration during operation.\u003c/p\u003e \u003cp\u003ePreviously, investigations into the relationship between CVP and DGF have predominantly centered on single-point CVP measurements. These measurements were typically taken at specific junctures, such as baseline, reperfusion, or post-anesthesia, to establish this connection. In our study, however, CVP was monitored continuously throughout the surgical procedure, allowing us to track CVP fluctuations in both the SGF\u0026thinsp;+\u0026thinsp;DGF group and the IGF group. This methodology distinguishes our study from others in the field. As a result of measuring and comparing CVP at various time points, including baseline CVP, it was found that when conventional fluid management was implemented, CVP continued to rise, peaked around the time of reperfusion, and was maintained. This is interpreted because most conventional fluid management is performed by targeting blood pressure or CVP at reperfusion period. Considering these changes in CVP, it can be seen that the value of CVP itself is more important than the CVP value at a specific point in time. Since there is no difference in the amount of fluid intake between the SGF\u0026thinsp;+\u0026thinsp;DGF and IGF groups, the value of baseline CVP can be considered to increase proportionally according to fluid intake. Therefore, if CVP is within the normal range based on baseline CVP, it could be concluded that increasing fluid intake to increase CVP does not help early graft function recovery.\u003c/p\u003e \u003cp\u003eHigh CVP values have a negative effect on graft function due to complications that may occur when fluid overload occurs when CVP is high \u003csup\u003e25\u003c/sup\u003e. Additionally, since most KT candidate patients have a high risk of developing cardiac complications, fluid overload may make them more vulnerable to heart-related complications. Therefore, in the pre-anesthesia evaluation performed before kidney transplant surgery, it would be important to examine indicators that can predict problems caused by volume overload more accurately than the CVP value, such as RVSP. RVSP represents pulmonary hypertension, which is related to right ventricular function \u003csup\u003e26,27\u003c/sup\u003e. According to guidelines, more than 35 mmHg of RVSP indicates pulmonary hypertension [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. As RVSP value increases, the severity of pulmonary hypertension is also increased. In this study, we investigated the RVSP values obtained from preoperative echocardiography results and compared them with the patients' CVP results. As a result, it was found that the average RVSP value was significantly higher in patients with CVP of 12 mmHg or higher. Therefore, if the baseline CVP value is high enough to be outside the normal range, it is expected that the RVSP value will also be high, and it is important to perform passive fluid intake during the operation to prevent cardio-pulmonary complications that may occur.\u003c/p\u003e \u003cp\u003eSeveral limitations of our study were existed. First, this study was conducted at a single center in Korea and was conducted in an area with a relatively low incidence of SGF or DGF. Therefore, in this study where the incidence of DGF is important, it can be said that the low incidence of DGF is a disadvantage in studying DGF risk factors. Second, although all echocardiograms measuring RVSP were performed before surgery, the date of surgery and the date of examination were different for each patient, which may slightly reduce the reliability of the research results. Finally, our study population was relatively small, compared with similar studies on evaluating CVP and graft function.\u003c/p\u003e \u003cp\u003eIn this retrospective study, higher CVP was significant intraoperative risk factors for SGF or DGF during deceased donor kidney transplantation. Other factors, such as high body mass index, prolonged ischemic time, and higher donor creatinine level were also revealed as risk factors. Considering anesthesiological factors that can be monitored during operation, CVP are important factors affecting short-term function after kidney transplantation and should be monitored to prevent excessive fluid intake.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed the recipients who underwent deceased donor kidney transplantation from March 2010 to December 2020. Before evaluation, we excluded recipients with extended criteria donor, donor creatinine level above 1.5 mg/dL and acute rejection within 2 weeks after transplantation to consider the impact of the donor's condition on the early graft function. After exclusion, total 202 recipients were consisted of the eligible population for evaluation. Immunosuppressive regimen consisted of basiliximab as induction therapy, tacrolimus, mycophenolate mofetil and corticosteroids. Basiliximab was administered just prior to transplantation and 4 days after transplantation. Tacrolimus was initiated at 2 days before KT with an initial dose of 0.05\u0026ndash;0.1 mg/kg. Steroids were administrated intravenously at 500 mg on the day of transplantation, 250 mg on the next day after transplantation, and were gradually tapered to a maintenance dose of more than 5 mg a day until 6-months post-transplant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAnesthetic protocol and fluid management\u003c/h2\u003e \u003cp\u003eIn the operating room, all patients were monitored with electrocardiogram (ECG), non-invasive blood pressure, pulse oximetry, and bispectral index (BIS). General anesthesia was achieved by administering 2 mg/kg propofol and 2\u0026ndash;3 mcg/kg fentanyl intravenously, followed by the administration of 0.6 mg/kg rocuronium. After the loss of consciousness, sevoflurane was started with 3\u0026ndash;5 vol% until endotracheal intubation. After intubation, the anesthetic gas was changed to desflurane, and desflurane was adjusted to maintain BIS between 40\u0026ndash;60 at 5\u0026ndash;7 vol%. A tidal volume of 8 mL/kg of the patients\u0026rsquo; ideal body weight was set, with a respiratory rate of 12\u0026ndash;14 bpm to maintain normocapnia conditions. Furthermore, a radial artery catheter was placed, and a central venous catheter was positioned to allow hemodynamic and CVP monitoring. All anesthesiologic variables including heart rate, arterial blood pressure, O\u003csub\u003e2\u003c/sub\u003e saturation, CVP and respiratory rate were monitored and recorded every 5 minutes in the electronic medical record chart. The fluid management strategy involved administering 10\u0026ndash;20 mL/kg/h of a combination of 0.9% normal saline, 0.45% half saline, and 5% human albumin throughout the entire surgical procedure. When severe hypotensive episodes (systolic blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;100 mmHg or mean arterial pressure\u0026thinsp;\u0026lt;\u0026thinsp;65 mmHg) occurred, ephedrine and phenylephrine were considered the preferred vasopressor for management of hypotension during operation. All patients received 20 mg of furosemide 5 minutes before vascular declamping and 500 mg of methylprednisone at reperfusion intravenously.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy outcomes and data collection\u003c/h2\u003e \u003cp\u003eThe primary outcome of this study was incidence of DGF and SGF. The definition of DGF was the need for dialysis within 7 days after transplantation, and the definition of SGF was serum creatinine level greater than 3.0 mg/dL on post-operative day 5 \u003csup\u003e7\u003c/sup\u003e. To investigate the incidence of SGF, serum creatinine levels and urine volume were collected until discharge. Patients whose renal function recovered immediately after transplantation were classified into immediate graft function (IGF) group, and patients who developed SGF or DGF were classified into one group and the values between the two groups were compared. In addition, we evaluated 1 and 3 year graft, patient survival rates in this study.\u003c/p\u003e \u003cp\u003eIntraoperative hemodynamic factors were recorded in the electronic medical record every 5 minutes, but the time from the start of surgery to reperfusion was different for each patient. Therefore, we unified these data based on the reperfusion time and collected records from 1 hour and 30 minutes before reperfusion to 1 hour after reperfusion.\u003c/p\u003e \u003cp\u003eAdditionally, results of echocardiogram performed within 1 year before transplant surgery were collected in all patients for identifying patients who may be more susceptible to elevated CVP.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eFor categorical variables, data were expressed as a number of patients and a percentage of derived groups, analyzed by Pearson\u0026rsquo;s \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e test and Fisher\u0026rsquo;s exact test. Continuous variables were expressed as a mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and analyzed by using the student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test and Mann-whitney test. Logistic regression analysis was used to confirm independent risk factors for the development of SGF or DGF. The \u003cem\u003eP\u003c/em\u003e-value less than 0.05 was considered significant. Data analysis was conducted using SPSS version 20.0 (SPSS Inc., Chicago, IL, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e This study was approved by the Ajou University Hospital Institutional Review Board (AJOUIRB-MDB-2020-387). Patients authorized the use of their health records for research and had waived informed consent because this study was a retrospective study. For the deceased donor kidney transplants, informed consent was obtained either from the donor previously or from a relative or kin at the time of transplantation. This retrospective study was conducted in accordance with the principles of the Declaration of Helsinki. Also, this study was conducted in accordance with the Declaration of Istanbul on organ trafficking and transplant tourism. This study did not involve organs or tissues procured from prisoners.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJun Bae Bang and Hyo Eun Ahn contributed to the conceptualization, methodology, formal analysis, and investigation of the study. Hyo Eun Ahn was responsible for writing the original draft of the manuscript. Jun Bae Bang reviewed and edited the manuscript, supervised the project, and acquired the necessary funding and resources. Both authors read and approved the final manuscript\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYarlagadda, S. G. \u003cem\u003eet al.\u003c/em\u003e Marked variation in the definition and diagnosis of delayed graft function: a systematic review. Nephrol Dial Transplant 23, 2995\u0026ndash;3003, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ndt/gfn158\u003c/span\u003e\u003cspan address=\"10.1093/ndt/gfn158\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchr\u0026ouml;ppel, B. \u0026amp; Legendre, C. Delayed kidney graft function: from mechanism to translation. Kidney Int 86, 251\u0026ndash;258, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ki.2014.18\u003c/span\u003e\u003cspan address=\"10.1038/ki.2014.18\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrish, W. D. \u003cem\u003eet al.\u003c/em\u003e Nomogram for predicting the likelihood of delayed graft function in adult cadaveric renal transplant recipients. J Am Soc Nephrol 14, 2967\u0026ndash;2974, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.asn.0000093254.31868.85\u003c/span\u003e\u003cspan address=\"10.1097/01.asn.0000093254.31868.85\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eP\u0026eacute;rez Font\u0026aacute;n, M. \u003cem\u003eet al.\u003c/em\u003e Outcome of grafts with long-lasting delayed function after renal transplantation. Transplantation 62, 42\u0026ndash;47, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00007890-199607150-00009\u003c/span\u003e\u003cspan address=\"10.1097/00007890-199607150-00009\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1996).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOjo, A. O., Wolfe, R. A., Held, P. J., Port, F. K. \u0026amp; Schmouder, R. L. Delayed graft function: risk factors and implications for renal allograft survival. Transplantation 63, 968\u0026ndash;974, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/00007890-199704150-00011\u003c/span\u003e\u003cspan address=\"10.1097/00007890-199704150-00011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eButala, N. M., Reese, P. P., Doshi, M. D. \u0026amp; Parikh, C. R. Is delayed graft function causally associated with long-term outcomes after kidney transplantation? Instrumental variable analysis. Transplantation 95, 1008\u0026ndash;1014, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/TP.0b013e3182855544\u003c/span\u003e\u003cspan address=\"10.1097/TP.0b013e3182855544\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHumar, A. \u003cem\u003eet al.\u003c/em\u003e Effect of initial slow graft function on renal allograft rejection and survival. Clin Transplant 11, 623\u0026ndash;627 (1997).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeraati, A. A., Naghibi, M., Kianoush, S. \u0026amp; Ashraf, H. Impact of slow and delayed graft function on kidney graft survival between various subgroups among renal transplant patients. Transplant Proc 41, 2777\u0026ndash;2780, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.transproceed.2009.07.038\u003c/span\u003e\u003cspan address=\"10.1016/j.transproceed.2009.07.038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee, S. Y. \u003cem\u003eet al.\u003c/em\u003e Clinical significance of slow recovery of graft function in living donor kidney transplantation. Transplantation 90, 38\u0026ndash;43, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/TP.0b013e3181e065a2\u003c/span\u003e\u003cspan address=\"10.1097/TP.0b013e3181e065a2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHumar, A. \u003cem\u003eet al.\u003c/em\u003e Risk factors for slow graft function after kidney transplants: a multivariate analysis. Clin Transplant 16, 425\u0026ndash;429, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1034/j.1399-0012.2002.02055.x\u003c/span\u003e\u003cspan address=\"10.1034/j.1399-0012.2002.02055.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampos, L. \u003cem\u003eet al.\u003c/em\u003e Do intraoperative hemodynamic factors of the recipient influence renal graft function? Transplant Proc 44, 1800\u0026ndash;1803, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.transproceed.2012.05.042\u003c/span\u003e\u003cspan address=\"10.1016/j.transproceed.2012.05.042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSnoeijs, M. G. \u003cem\u003eet al.\u003c/em\u003e Recipient hemodynamics during non-heart-beating donor kidney transplantation are major predictors of primary nonfunction. Am J Transplant 7, 1158\u0026ndash;1166, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1600-6143.2007.01744.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1600-6143.2007.01744.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2007).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChappell, D., Jacob, M., Hofmann-Kiefer, K., Conzen, P. \u0026amp; Rehm, M. A rational approach to perioperative fluid management. Anesthesiology 109, 723\u0026ndash;740, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ALN.0b013e3181863117\u003c/span\u003e\u003cspan address=\"10.1097/ALN.0b013e3181863117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAulakh, N. K. \u003cem\u003eet al.\u003c/em\u003e Influence of hemodynamics and intra-operative hydration on biochemical outcome of renal transplant recipients. J Anaesthesiol Clin Pharmacol 31, 174\u0026ndash;179, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/0970-9185.155144\u003c/span\u003e\u003cspan address=\"10.4103/0970-9185.155144\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBacchi, G. \u003cem\u003eet al.\u003c/em\u003e The influence of intraoperative central venous pressure on delayed graft function in renal transplantation: a single-center experience. Transplant Proc 42, 3387\u0026ndash;3391, doi:10.1016/j.transproceed.2010.08.042 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOthman, M. M., Ismael, A. Z. \u0026amp; Hammouda, G. E. The impact of timing of maximal crystalloid hydration on early graft function during kidney transplantation. Anesth Analg 110, 1440\u0026ndash;1446, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1213/ANE.0b013e3181d82ca8\u003c/span\u003e\u003cspan address=\"10.1213/ANE.0b013e3181d82ca8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWagener, G. \u003cem\u003eet al.\u003c/em\u003e Fluid Management During Kidney Transplantation: A Consensus Statement of the Committee on Transplant Anesthesia of the American Society of Anesthesiologists. Transplantation 105, 1677\u0026ndash;1684, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/tp.0000000000003581\u003c/span\u003e\u003cspan address=\"10.1097/tp.0000000000003581\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCavaleri, M. \u003cem\u003eet al.\u003c/em\u003e Perioperative Goal-Directed Therapy during Kidney Transplantation: An Impact Evaluation on the Major Postoperative Complications. J Clin Med 8, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/jcm8010080\u003c/span\u003e\u003cspan address=\"10.3390/jcm8010080\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarbell, M. W., Kraus, M. B., Bucker-Petty, S. A. \u0026amp; Harbell, J. W. Intraoperative fluid management and kidney transplantation outcomes: A retrospective cohort study. Clin Transplant 35, e14489, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ctr.14489\u003c/span\u003e\u003cspan address=\"10.1111/ctr.14489\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomsen, H. S., Lokkegaard, H. \u0026amp; Munck, O. Influence of normal central venous pressure on onset of function in renal allografts. Scand J Urol Nephrol 21, 143\u0026ndash;145, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3109/00365598709180310\u003c/span\u003e\u003cspan address=\"10.3109/00365598709180310\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1987).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalixto Fernandes, M. H., Schricker, T., Magder, S. \u0026amp; Hatzakorzian, R. Perioperative fluid management in kidney transplantation: a black box. Crit Care 22, 14, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13054-017-1928-2\u003c/span\u003e\u003cspan address=\"10.1186/s13054-017-1928-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagder, S. Current tools for assessing heart function and perfusion adequacy. Curr Opin Crit Care 20, 294\u0026ndash;300, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/mcc.0000000000000100\u003c/span\u003e\u003cspan address=\"10.1097/mcc.0000000000000100\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarik, P. E. \u0026amp; Cavallazzi, R. Does the central venous pressure predict fluid responsiveness? An updated meta-analysis and a plea for some common sense. Crit Care Med 41, 1774\u0026ndash;1781, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/CCM.0b013e31828a25fd\u003c/span\u003e\u003cspan address=\"10.1097/CCM.0b013e31828a25fd\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagder, S. How to use central venous pressure measurements. Curr Opin Crit Care 11, 264\u0026ndash;270, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.ccx.0000163197.70010.33\u003c/span\u003e\u003cspan address=\"10.1097/01.ccx.0000163197.70010.33\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2005).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSrivastava, D. \u003cem\u003eet al.\u003c/em\u003e Effect of intraoperative transesophageal Doppler-guided fluid therapy versus central venous pressure-guided fluid therapy on renal allograft outcome in patients undergoing living donor renal transplant surgery: a comparative study. J Anesth 29, 842\u0026ndash;849, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00540-015-2046-4\u003c/span\u003e\u003cspan address=\"10.1007/s00540-015-2046-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudski, L. G. \u003cem\u003eet al.\u003c/em\u003e Guidelines for the echocardiographic assessment of the right heart in adults: a report from the American Society of Echocardiography endorsed by the European Association of Echocardiography, a registered branch of the European Society of Cardiology, and the Canadian Society of Echocardiography. J Am Soc Echocardiogr 23, 685\u0026ndash;713; quiz 786\u0026thinsp;\u0026ndash;\u0026thinsp;688, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.echo.2010.05.010\u003c/span\u003e\u003cspan address=\"10.1016/j.echo.2010.05.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSubias, P. E. Comments on the 2015 ESC/ERS Guidelines for the Diagnosis and Treatment of Pulmonary Hypertension. \u003cem\u003eRev Esp Cardiol (Engl Ed)\u003c/em\u003e 69, 102\u0026ndash;108, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.rec.2015.11.030\u003c/span\u003e\u003cspan address=\"10.1016/j.rec.2015.11.030\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4459030/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4459030/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study aims to analyze data from patients who received kidney transplantation from deceased donors to investigate the anesthetic factors influencing early and late graft outcomes, including the incidence of slow graft function (SGF), delayed graft function (DGF), and 3-year graft outcomes. We retrospectively analyzed 202 recipients who underwent deceased donor kidney transplantation from March 2010 to December 2020. Anesthetic monitoring data during the intraoperative period was analyzed at 5-minute intervals, and basic clinical parameters were evaluated. The mean recipient age was 46.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3 years, and the mean donor age was 41.7\u0026thinsp;\u0026plusmn;\u0026thinsp;12.7 years. Anesthetic time averaged 285.8\u0026thinsp;\u0026plusmn;\u0026thinsp;70.2 minutes, and operation time averaged 223.1\u0026thinsp;\u0026plusmn;\u0026thinsp;44.0 minutes. The incidence of SGF was 11.8%, and the incidence of DGF was 3.9%. Mean central venous pressures (CVPs) were higher in recipients with SGF or DGF (11.7 mmHg) compared to those with immediate graft function (9.7 mmHg). Higher CVP was identified as an independent risk factor for SGF or DGF (odds ratio 1.219, p\u0026thinsp;=\u0026thinsp;0.006). This study suggests that intraoperative monitoring of CVP is crucial for predicting short-term graft function in deceased donor kidney transplantation and should be managed to prevent excessive fluid intake.\u003c/p\u003e","manuscriptTitle":"Intraoperative central venous pressures related to early graft function in deceased donor kidney transplant recipients with low immunological risks","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 19:21:59","doi":"10.21203/rs.3.rs-4459030/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-18T02:55:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-14T08:08:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122367656221062935203973428774554495421","date":"2024-09-11T16:39:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"42085596025735200501637583953979318262","date":"2024-07-22T07:54:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-19T11:43:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"96254447447173636845215887946928749419","date":"2024-07-10T19:17:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-05T18:25:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-05T18:19:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-26T07:18:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-26T07:15:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-22T07:39:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cc77b77c-7c73-45ef-9f8d-9e6722379e04","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":34642226,"name":"Health sciences/Nephrology"},{"id":34642227,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-21T16:08:31+00:00","versionOfRecord":{"articleIdentity":"rs-4459030","link":"https://doi.org/10.1038/s41598-024-75474-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-18 15:57:57","publishedOnDateReadable":"October 18th, 2024"},"versionCreatedAt":"2024-07-19 19:21:59","video":"","vorDoi":"10.1038/s41598-024-75474-2","vorDoiUrl":"https://doi.org/10.1038/s41598-024-75474-2","workflowStages":[]},"version":"v1","identity":"rs-4459030","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4459030","identity":"rs-4459030","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}