Kidney Transplantation/adverse effects* ; Magnetics ; Anastomosis, Surgical ; Magnetic Phenomena

Objective:To explore the clinical efficacy of treating external iliac artery dissection in renal transplantation by artificial vascular replacement.Methods:Four sudden intraoperative cases of external iliac artery dissection were selected.After removing vascular sutures, intimal arterial peeling blocked external iliac artery( n=3)and transplanted renal artery( n=1). Artificial vascular replacement of external iliac artery was performed using artificial vessels made from puffed polytetrafluoride ethylene(ePTFE). Secondary perfusion was performed in four transplanted kidneys for anastomosing with internal iliac artery. Results:One patient regained normal renal function within 1 week post-operation.Two cases had delayed graft function.Another case had delayed graft function plus acute rejection.After hemodialysis, renal function normalized at 2-3 weeks post-operation.During a follow-up period of(0.5-5.0)years, transplanted kidney function remained stable, blood supply, skin temperature and movement of operated lower extremities normalized.Conclusions:The incidence of vascular dissection of external iliac artery is not high during renal transplantation.However, the disease has a rapid and dangerous progression.The consequences of delayed intervention are quite serious.Treating external iliac artery dissection with renal transplantation may achieve satisfactory clinical outcomes.

Objective To evaluate the efficacy and safety of basiliximab (BAS) and antithymocyte globulin (ATG) in immune induction therapy in kidney transplantation by systematic review and Meta-analysis. Methods Prospective randomized controlled clinical trials screening and comparing BAS and ATG in immune induction therapy in kidney transplantation were systematically searched from global databases, screened and compared. The quality of clinical trials was evaluated by Jadad scoring system and data extraction was performed. The effects of BAS and ATG on the incidence of acute rejection, survival rate of kidney allografts, survival rate of recipients, incidence of delayed graft function, infection, cytomegalovirus infection, malignant tumor, leukopenia and thrombocytopenia at 1 year after kidney transplantation were analyzed. Results A total of 10 clinical trials in English consisting of 1 721 kidney transplant recipients were searched, including 883 cases in the ATG group and 838 cases in the BAS group. No significant differences were observed in the incidence of acute rejection, survival rate of kidney allografts, survival rate of recipients, incidence of delayed graft function, infection, cytomegalovirus infection and thrombocytopenia at postoperative 1 year between the ATG and BAS groups (all P > 0.05). The incidence of malignant tumor and leukopenia at postoperative 1 year in the ATG group were significantly higher than those in the BAS group (both P < 0.05). Conclusions The use of ATG and BAS for immune induction therapy in kidney transplantation yield equivalent efficacy at postoperative 1 year, but BAS is safer than ATG. Clinical trials related to stratified analyses of immune risk are urgently required to achieve individualized precision treatment.

Objective:To establish risk stratifying criteria for acute rejection(AR)after kidney transplantation(KT)through analyzing the preoperative risk factors of KT recipients from deceased donor(DD).Methods:A retrospective study is conducted for 1 382 KT recipients of DD kidney at First Affiliated Hospital of Xi'an Jiaotong University from January 2015 to December 2020.According to the presence or absence of AR within 1 year post-KT, they are divided into two groups of acute rejection(group AR, 115 cases)and non-rejection(group non-AR, 1 267 cases). Clinical data of two groups are examined by univariate and multivariate analyses for determining the risk factors of AR and a scoring standard is established on the basis of regression coefficients.They are divided into three groups of low-risk(907 cases), middle-risk(450 cases)and high-risk(25 cases)according to the scoring results and the incidence of AR is compared among different scoring groups.Results:Univariate analysis indicates that donor age(AR, 793 cases; non-AR, 474 cases, P=0.033), age difference between recipients and donors≥25 years(AR, 63 cases; non-AR; 315 cases; P<0.001), recipient panel-reactive antibodies(PRA)plus donor-specific antibody(DSA)(+ )(AR, 96 cases; non-AR, 1 169 cases, P=0.002), donor kidney cold ischemic time≥12h(AR, 81 cases; non-AR, 1 064 cases, P<0.001), donor/recipient HLA mismatch≥3(AR, 70 cases; non-AR, 984 cases, P<0.001)and expanded criteria donor(ECD)(AR, 50 cases; non-AR, 790 cases, P<0.001)are high risk factors for AR(all P<0.05). Variables with statistical significance during univariate analysis are included for multivariate analysis.Five variables are finally determined, including age difference between recipients and donors≥25 years(β=0.61, P=0.006), PRA+ DSA(+ )(β=0.74, P=0.008), donor kidney cold ischemic time≥12 h(β=0.74, P<0.001), HLA mismatch(≥3)(β=0.81, P<0.001)and ECD(β=0.82, P<0.001). Score for each risk factor is calculated according to the relevant regression coefficient and scoring standard formulate on the basis of the above five risk factors with a total score of 36.With an overall incidence of AR at 8.32%(115/1 382), the incidence of AR is 4.3%, 14.7% and 40.0% in low/middle/high-risk group and the difference is statistically significant.It hints that immune risk stratification can effectively determine the risk of postoperative AR for KT recipients.The incidence of AR is significantly higher in middle/high-risk group than that in low-risk group ( P<0.001). Conclusions:For recipients with middle/high immune risk, intensity and dose of immunosuppressants should be appropriately boosted during preoperative induction and maintenance period.And the occurrences of AR and infection should be dynamically monitored.

Objective:To explore the clinical data of acute rejection in kidney transplant recipients of different ages with elderly donor kidneys.Methods:During January 2012 and June 2020, a retrospective review was conducted for clinical data of 298 recipients undergoing kidney transplantation from elderly donors aged ≥60 years after citizen's death.According to the age, recipients were divided into group A(age<30 yr, 59 cases), group B(30~39 yr, 125 cases), group C(40~49 yr, 83 cases)and group D(age≥50 yr, 31 cases). The incidence of acute rejection(AR)was analyzed.Also based upon age difference between donors and recipients, they were divided into two groups of(30~39 yr)and (40~49 yr)and the occurrence of AR was recorded.Results:The incidence of AR within 1 year post-transplantation in groups A, B, C, and D were 15.3%(9/59), 8.8%(11/125), 7.2%(6/83) and 3.2%(1/31)respectively.The incidence of AR in age difference≥25 yr group(12.5%)and age difference <25 yr group(5.3%) had significant difference( P<0.05). The proportion and absolute value of peripheral blood lymphocytes in each group at 1 week/month post-transplantation had significant difference( P<0.05). No significant difference was observed in serum level of creatinine(SCr), the incidence of pulmonary infection and urinary tract infection or the survival rate of recipients and transplanted kidneys in each group within 1 year post-transplantation among four groups( P>0.05). Conclusions:Elderly donor kidneys can obtain better transplant outcomes in kidney transplant recipients of different ages.As the age of recipients decreases, AR shows an upward trend.Clinicians should pay more attention to the prevention and treatment of AR in recipients with large age difference between donors and recipients.

Objective:To explore the prognostic utility of LifePort perfusion parameters plus perfusate biomarkers for predicting delayed graft function(DGF)and recovery time during deceased donor kidney transplantation(KT).Methods:From January 1, 2019 to August 31, 2019, retrospective analysis was performed for clinical data of 113 KT recipients. Based upon whether or not DGF occurred within 3 months, they were divided into two groups of DGF group(20 cases)and non-DGF (93 cases). Two groups were compared using LifePort perfusion parameters, biomarker concentrations, incidence of DGF and kidney recovery time. Statistical analysis was performed.Results:The incidence of DGF was 17.7%(20/113); Multivariate Logistic regression results indicated that terminal resistance(OR 1.879, 95% CI 1.145~3.56)and glutathione S-transferase(GST)(OR 1.62, 95% CI 1.23~2.46)were independent risk factors for DGF; Cox hazard model revealed that terminal resistance was a risk factor for recovery time of renal function(HR=0.823, 95% CI 0.735~0.981). The model combining terminal resistance and GST(AUC=0.888, 95% CI 0.842~0.933)significantly improved the predictive efficacy for DGF as compared with using terminal resistance(AUC=0.756, 95% CI 0.693~0.818)or GST alone(AUC=0.729, 95% CI 0.591~0.806).Conclusions:Combining LifePort perfusion parameters and fluid biomarkers can improve the predictive utility of DGF.

BACKGROUND: Delayed graft function (DGF) is the main cause of renal function failure after kidney transplantation. This study aims at investigating the value of hypothermic machine perfusion (HMP) parameters combined with perfusate biomarkers on predicting DGF and the time of renal function recovery after deceased donor (DD) kidney transplantation. METHODS: HMP parameters, perfusate biomarkers and baseline characteristics of 113 DD kidney transplantations from January 1, 2019 to August 31, 2019 in the First Affiliated Hospital of Xi'an Jiaotong University were retrospectively analyzed using univariate and multivariate logistic regression analysis. RESULTS: In this study, the DGF incidence was 17.7% (20/113); The multivariate logistic regression results showed that terminal resistance (OR: 1.879, 95% CI 1.145-3.56) and glutathione S-transferase (GST)(OR = 1.62, 95% CI 1.23-2.46) were risk factors for DGF; The Cox model analysis indicated that terminal resistance was an independent hazard factor for renal function recovery time (HR = 0.823, 95% CI 0.735-0.981). The model combining terminal resistance and GST (AUC = 0.888, 95% CI: 0.842-0.933) significantly improved the DGF predictability compared with the use of terminal resistance (AUC = 0.756, 95% CI 0.693-0.818) or GST alone (AUC = 0.729, 95% CI 0.591-0.806). CONCLUSION According to the factors analyzed in this study, the combination of HMP parameters and perfusate biomarkers displays a potent DGF predictive value.
Biomarkers ; Delayed Graft Function ; Graft Survival ; Humans ; Kidney/physiology* ; Kidney Transplantation/adverse effects* ; Organ Preservation ; Perfusion ; Retrospective Studies ; Tissue Donors

Objective To compare the clinical efficacy of different T lymphocyte polyclonal antibodies in renal transplantation from donor kidney of organ donation after citizen's death. Methods Clinical data of 691 donors and recipients undergoing renal transplantation from donor kidney of organ donation after citizen's death were retrospectively analyzed. According to different T lymphocyte polyclonal antibodies used for induction, all recipients were divided into the rabbit anti human T lymphocyte immunoglobulin (rALG) group (n=414) and rabbit anti human thymocyte immunoglobulin (rATG) group (n=277). The recovery of renal graft function in recipients of the two groups were collected, including the incidence of delayed graft function (DGF) and acute rejection (AR), and the changes of serum creatinine level after renal transplantation. The 1-year survival rate of the recipients and renal grafts was collected. The incidence of adverse effects within 1 year after operation was calculated. According to the DGF risk score of donors, all recipients were divided into 5 groups. The use proportion of rALG and rATG in the recipients of each group was calculated. Results The incidence of DGF in the recipients of rALG and rATG groups was 14.5% (60/414) and 11.9% (33/277), respectively. The duration of DGF in the recipients of rALG and rATG groups was (7±4) d and (12±7) d respectively, with no statistically significant difference between two groups (P > 0.05). The incidence of AR in the rALG group was 7.5% (31/414), significantly higher than 4.0% (11/277) in the rATG group (P < 0.05). The serum creatinine levels of recipients within 6 months after renal transplantation tended to gradually decline in both groups. In renal transplantation for donor kidney with a DGF risk score of 0-15, the use proportion of rALG was significantly higher than that of rATG. However, the use proportion of rATG was significantly higher than that of rALG in renal transplantation for donor kidney with a DGF risk score over 16 (P < 0.05). The 1-year survival rates of the recipients and renal grafts in the rALG and rATG groups were 99.8% and 99.6%, 98.1% and 98.2%, respectively. There was no significant difference between two groups (both P > 0.05). The incidence of acute pulmonary edema and leukopenia in the recipients of rATG group was significantly higher than that in the rALG group (both P < 0.05). Conclusions Both rALG and rATG can effectively reduce the incidence of DGF and AR and achieve good clinical efficacy after renal transplantation from donor kidney of organ donation after citizen's death. The incidence of leukopenia and acute pulmonary edema induced by rATG is higher than that by rALG in the renal transplant recipients.

Objective To evaluate the clinical effect of hypothermic machine perfusion (HMP) in the storage of renal grafts from deceased donor (DD) with high-risk delayed graft function (DGF). Methods Clinical data of 52 donors with high-risk DGF were collected in this prospective randomized controlled study. Two renal grafts from each donor were randomly divided into the HMP group (n=52) and static cold storage (SCS) group (n=52). In the HMP group, the renal grafts were stored by LifePort under HMP, whereas the renal grafts in the SCS group were preserved in University of Wisconsin solution (UW solution). The incidence of DGF and primary nonfunction (PNF) after renal transplantation was statistically compared between two groups. The recovery of renal graft function, the survival rates of the recipients and renal grafts within postoperative 1 year were observed in two groups. Results The incidence of DGF in the HMP group was 4%(2/52), significantly lower than 17% (9/52) in the SCS group (P < 0.05). No PNF was reported in the HMP group and 1 case of PND was noted in the SCS group, the difference was not statistically significant (P > 0.05). The recovery time of graft function of the recipients in the HMP and SCS groups were (7.2±0.6) d and (7.7±1.0) d with no statistical significance (P > 0.05). In the HMP group, the urine volume of the recipients on the day of operation, postoperative 1 and2 d was significantly larger than that in the SCS group (all P < 0.05). In the HMP group, the levels of serum creatinine at each time point after operation were significantly lower than those in the SCS group (all P < 0.05). The 1-year survival rates of the recipient and kidney were 98.1%, 92.3% and 100%, 96.2% in the HMP and SCS groups with no statistical significance (all P > 0.05). Conclusions HMP can significantly reduce the incidence of DGF after renal transplantation from DD with high-risk DGF and promote the early recovery of graft function.

Objective To analyze the prediction efficiency of scoring models at home and abroad on delayed graft function (DGF) after renal transplantation in China. Methods The clinical data of 112 donors and 220 recipients undergoing renal transplantation were prospectively analyzed. The DGF predicted by KDRI model, Jeldres model, and model of our center was compared with actual DGF incidence of renal transplant recipients. The prediction efficiency of each model was analyzed. The predictive accuracy was compared by the area under curve (AUC) of receiver operating characteristic (ROC) curve. Results The DGF incidence of 220 renal transplant recipients was 14.1% (31/220). DGF prediction using KDRI model showed that 41 cases were high risk donors, the AUC was 0.57, the sensitivity was 0.37, the specificity was 0.66, and the positive predictive value was 22%. DGF prediction using Jedres model showed that 22 cases were high risk recipients, the AUC was 0.56, the sensitivity was 0.13, the specificity was 0.92 and the positive predictive value was 20%. DGF prediction using the model of our center showed that 25 cases were high risk donors, the AUC was 0.80, the sensitivity was 0.53, the specificity was 0.84, the positive predictive value was 40%. Conclusions Compared with the KDRI and Jedres models, the prediction model of our center has higher AUC and sensitivity with a better prediction efficiency on DGF. Therefore, it is a suitable evaluation system of donors from donation after citizen's death in Chinese.