{"paper_id":"4522d4ff-a4b9-4aff-a37a-43dfc241a9d2","body_text":"Trends and Outcomes in Kidney Retransplantation: A Two-Decade Longitudinal Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends and Outcomes in Kidney Retransplantation: A Two-Decade Longitudinal Analysis Abolfazl Jamshidi, Janice Liu, Sajedeh Jadidi, Harland Emily, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6247432/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Jun, 2025 Read the published version in International Urology and Nephrology → Version 1 posted You are reading this latest preprint version Abstract Purpose: We aimed to evaluate kidney retransplantation outcomes to optimize patient care and reduce the risk of further retransplantation. Methods: We conducted a retrospective longitudinal analysis of the SRTR database for kidney retransplants performed in the United States from January 2000 to May 2023. Patients were divided into subgroups based on transplant date and number of previous transplants. Outcomes were assessed by patient and allograft survival. Results: A total of 34,230 patients were evaluated (12,224 in 2001–2011, 22,006 in 2012–2023). The proportion of DCD donors was significantly higher in 2012–2023 (21.3% vs. 8.8%, p < 0.001). Both patient and allograft survival improved in the more recent time frame (5-year survival: 84.8% vs. 83.7% for patients; 75.9% vs. 69.3% for allografts, p < 0.001). Allograft failure rates were higher with increasing retransplant attempts (5-year survival: 73.4% vs. 71.8% vs. 62.3% for first, second, and third+ retransplants, p < 0.001). DGF increased failure risk (HR: 1.69 [1.60–1.79] in 2000–2011; HR: 1.79 [1.63–1.97] in 2012–2023), as did higher KDPI (HR: 1.96 [1.70–2.26] in 2000–2011; HR: 2.34 [1.82–3.01] in 2012–2023). Allograft thrombosis contribution as an etiology for failure increased (OR: 2.94 [2.20, 3.92] for the first; OR: 3.13 [1.58, 6.79] for the second+ retransplants). Conclusion: Kidney retransplant outcomes have improved, but each successive transplant has a poorer prognosis. Careful patient selection and risk assessment, especially regarding high KDPI and DGF, are critical. Further investigation is needed into the rising proportion of allograft thrombosis. Kidney Transplantation Retransplantation Allograft Survival Patient Survival Long-Term Outcomes Prognosis Figures Figure 1 Figure 2 Introduction Kidney transplantation is the preferred treatment for patients with end-stage renal disease (ESRD), offering better quality of life, lower long-term morbidity and mortality rates, and cost-effectiveness compared to dialysis [ 1 ]. However, allograft rejection remains a significant challenge, often leading to allograft loss. Understanding the factors contributing to allograft rejection is crucial for improving allograft survival. These factors include pre-operative considerations such as donor and recipient characteristics (age, gender, race, and immunological compatibility) [ 2 , 3 ], as well as peri-operative and post-operative factors like cold and warm ischemia durations and immunosuppressive treatment [ 4 – 6 ]. Despite advances in transplantation, the lifespan of a transplanted kidney is limited. After the first year post-transplantation, up to 4% of patients may experience allograft loss and return to dialysis. [ 7 – 9 ]. In the United States, the allograft failure rate within three years of transplantation in 2016 was 2.3% for living donor transplants and 4.8% for deceased donation transplants. [ 10 ]. As the number of transplantations increases, so does the population experiencing allograft failure, necessitating considerations for retransplantation [ 11 ]. An estimated 20% of individuals on the kidney transplant waiting list have experienced allograft failure, accounting for 10–20% of all kidney transplant procedures [ 12 ]; moreover, there has been a steadily increasing number of kidney retransplant recipients [ 13 ]. Retransplantation offers a substantial mortality benefit compared to long-term dialysis for patients with allograft failure. [ 14 ]. However, it is associated with higher immunological risks than initial transplants. [ 15 ]. Outcomes such as allograft survival and rejection rates are less favorable in retransplant patients compared to those undergoing primary transplantation [ 16 , 17 ]. Patients who experience acute rejection, delayed allograft function (DGF), or hospitalization within the first year of their primary transplant are more likely to encounter similar complications following retransplantation [ 16 ]. While long-term outcomes of kidney retransplantation are increasingly studied, comprehensive reports on these outcomes are still relatively uncommon. [ 13 ]. Effective management strategies and the identification of risk factors for kidney retransplantation are crucial for healthcare providers to optimize patient care and potentially reduce the need for additional transplants. This study aims to analyze the outcomes of kidney retransplants in the United States, focusing on allograft and patient survival rates, factors influencing these outcomes, and the changes in prognosis in more recent years. Materials and Methods A retrospective longitudinal analysis was performed utilizing data from the Scientific Registry of Transplant Recipients (SRTR) database, which provides detailed information on kidney transplant recipients and donors, including pretransplant data, baseline characteristics, follow-up data, and transplant outcomes. We extracted the information of all adult patients who underwent kidney retransplantation between January 2000, and May 2023 and divided the study period into two subgroups based on the time of the procedure: 2000–2011 and 2012–2023. We further divided our patients according to the number of previous transplants: “one”, “two”, “three or more” previous transplants for assessing survival outcomes, and “one” and “two or more” previous transplants for allograft failure etiology evaluation. Our inclusion criteria were adult patients (aged ≥ 18 years) who received at least one previous kidney transplant during this time period. We excluded people who were under 18 years of age, had multi-organ transplants, and those with incomplete follow-up data on patient and allograft survival. The primary characteristics of donors and recipients that we evaluated include age, gender, recipient BMI, recipient race, donor type (living or deceased), donation after circulatory death (DCD), kidney donor profile index (KDPI), cold ischemic time (CIT), number of HLA mismatches, primary diagnoses, and duration of hospital stay. KDPI is an objective measure of allograft quality that considers donor age, height, race, medical history (including diabetes and hypertension), kidney function indices, cause of death, and more [ 18 ]. For live donors, the KDPI is similar but includes criteria such as a BMI < 35 kg/m², absence of infections or malignancies, and good kidney function [ 18 ]. A higher KDPI indicates an allograft that is more likely to fail. An additional factor we evaluated was DGF, defined as the need for dialysis within the first week after transplantation [ 16 ]. CIT was defined as the time between the start of chilling the allograft with preservation fluid to warming the allograft with blood circulation from the recipient. A cold ischemic time of greater than 12 hours is typically considered to increase the risk of allograft failure or even the risk of delayed allograft function [ 18 ]. The primary objective of the study was to determine patient survival after retransplantation, along with the success of the allograft transplantation as a one- and five-year allograft survival rate. Allograft failure was considered to be the loss of kidney function necessitating dialysis or retransplantation as well as patient death attributed to allograft failure. Patient survival was defined as the time from retransplantation to patient death. Patients with no reported date of death were presumed to be alive as of May 2023. The secondary objective was to identify the most common contributory cause of allograft failure in each cohort and to assess the effect of different factors on the survival rate of allografts. This study followed the STROBE reporting guidelines. IBM SPSS 29 software was utilized for the analysis of baseline characteristics and outcomes of each study group. Multiple tests comprised our analysis depending on the type of variable that was measured: T-test for univariate analysis of continuous variables, chi-square for categorical variables, and Kaplan-Meier curves for patient and allograft survival rates. Associated with the continuous variables, means and standard deviations were calculated, and proportions and percentages were calculated for categorical variables. Additionally, a Cox regression analysis was performed to determine how allograft survival was influenced by multivariate factors such as donors’ BMI, KDPI, DCD donor, cold ischemia time, and DGF. Odds ratios were calculated between the different timeframe groups for one previous transplant or two or more transplants to compare the contribution of different etiologies for allograft failure. All p -values greater than 0.05 were considered significant. Results Based on the inclusion and exclusion criteria, a total of 34,230 patients – who had at least one previous kidney transplant - were evaluated. They were further divided into two groups according to the time of the retransplant; 12,224 patients had their procedure from 2001 to 2011 and 22,006 patients underwent retransplant from 2012 to 2023. Table 1 shows the difference in demographic characteristics between the two groups. Although some of the characteristics are significantly different, this is mostly due to the large sample size and does not necessarily translate to clinical significance. Notably, DCD donors were significantly higher in the 2012–2023 cohort (21.3% vs 8.8%, p -value < 0.001). The most common primary diagnosis in both timeframes was hypertensive nephropathy. Table 1 Kidney re-transplant donors and recipients’ demographic characteristics comparison between patients in 2001–2011 and 2012–2023 timeframes. Characteristics 2001–2011 (n = 12224) 2012–2023 (n = 22006) p -value Recipients’ Age (mean ± SD) 43.70 ± 13.90 46.56 ± 14.17 < 0.001 Recipients’ Gender Female Male Female Male 0.954 5116 (41.9%) 7108 (58.1%) 9218 (41.9%) 12788 (58.1%) Recipients’ BMI (mean ± SD) 26.02 ± 5.51 26.65 ± 5.45 < 0.001 Recipients’ Race < 0.001 white 7619 (62.3%) 11373 (51.7%) Black 2776 (22.7%) 5704 (25.9%) Hispanic 1280 (10.5%) 3392 (15.4%) Asian 417 (3.4%) 1184 (5.4%) Other 132 (1.1%) 353 (1.6%) Donors’Age (mean ± SD) 36.5 ± 14.61 37.76 ± 13.80 < 0.001 Donors’gender Female Male Female Male < 0.001 5421 (44.3%) 6803 (55.7%) 9454 (43%) 12552 (57%) Donor type Deceased Living Deceased Living 0.014 9019 (73.8%) 3205 (26.2%) 16785 (76.3%) 5221 (23.7%) DCD Donor (within the deceased donor population) Yes No Yes No < 0.001 796 (8.8%) 8223 (91.2%) 3578 (21.3%) 13207 (78.7%) KDPI (%) (mean ± SD) 35 ± 25 36 ± 23 0.232 Cold ischemic time (hours ± SD) 14.00 ± 10.37 14.96 ± 9.79 < 0.001 number of HLA Mismatch 0–3 4–6 0–3 4–6 0.001 5897 (48.4%) 6277 (51.6%) 10221 (46.6%) 11721 (53.4%) Duration of Hospital Stay (days ± SD) 9.87 ± 54.30 8.43 ± 55.69 0.020 Primary Diagnosis < 0.001 IgA Nephropathy 647 (5.7%) 1721 (8%) Focal Segmental Glomerular Sclerosis (FSGS) 1073 (9.5%) 2547 (11.9%) Polycystic Kidney Disease 750 (6.6%) 1393 (6.5%) Systemic Lupus Erythematosus (SLE) 548 (4.8%) 1075 (5%) Hypoplasia/Dysplasia/Dysgenesis/Agenesis 268 (2.4%) 585 (2.7%) Hypertensive Nephropathy 1811 (16%) 3627 (16.9%) Chronic Glomerulonephritis 1248 (11%) 1481 (6.9%) Congenital Obstructive Uropathy 312 (2.8%) 756 (3.5%) Type 1 Diabetes Mellitus 252 (2.2%) 444 (2.1%) Type 2 Diabetes Mellitus 273 (2.4%) 1129 (5.3%) Other Diagnoses* 4156 (36.6%) 6708 (31.2%) *Apart from the unknown causes, each of the other causes contributes to less than one percent of total diagnoses in both cohorts The one-year and five-year allograft survivals were significantly higher in the 2012–2023 group compared to 2000–2011 (93.6% compared to 89.5% and 75.9% compared to 69.3%, respectively, both p -value < 000.1, Fig. 1 (a)). Although still higher in the 2012–2023 group, the difference was less prominent in one-year and five-year patient survival in the two groups (97% compared to 95.3% and 84.8% compared to 83.7%, both p -value < 000.1, Fig. 1 (b)). When evaluating the five-year allograft survival, we further divided our population based on the number of previous transplants. Figure 2 (a) indicates that the second transplant had better allograft outcomes than the third transplants and the third better than the fourth and more transplants (73.4% vs 71.8% vs 62.3%, p -value < 000.1). We also compared the difference in five-year allograft survival between the two timeframes in each of these groups (Fig. 2 (b), (c) and (d)). The five-year allograft survival in 2000–2011 vs 2012–2023 was 70.2% vs 75.9%, 67.1% vs 76.5%, and 59.1% vs 70.9% in the groups with one, two, and three or more prior transplants, respectively. A multivariant Cox regression test was conducted to demonstrate different factors that could affect allograft survival in each timeframe (Table 2 ). DGF and higher KDPI were related to less favorable allograft survival in both time frames (especially 2012–2023). Allograft survival was also slightly worse in DCD donors in 2012–2023 patients. Other factors did not seem to have statistically and/or clinically significant effects on allograft survival. Table 2 Multi-variant cox regression test with the effect of different factors as a hazard ratio with a 95% confidence interval on allograft survival in re-transplant patients in 2001–2011 and 2012–2023 time frames. Parameter HR, 95% CI 2001–2011 HR, 95% CI 2012–2023 KDPI 1.96 [1.70, 2.26] 2.34 [1.82, 3.01] Donors’ BMI 1.000 [0.996, 1.004] 1.000 [0.993, 1.006] Donors’ Age 1.004 [1.002, 1.007] 1.000 [0.996, 1.004] number of HLA Mismatch (0–3 or 4–6) 1.03 [1.01, 1.04] 1.02 [0.99, 1.04] DCD donor 1.03 [0.98, 1.08] 1.11 [1.04, 1.17] Cold ischemic time 1.005 [1.002, 1.008] 1.005 [1.000, 1.010] DGF 1.69 [1.60, 1.79] 1.79 [1.63, 1.97] The available data for the allograft failure etiology were limited; for this reason and to have a more apprehensible analysis, we divided the patients into two groups based on the number of previous transplants (instead of three, unlike our evaluation for five-year allograft survival): patients with one previous transplants and patients with two or more previous transplants. Table 3 compares the contribution of each allograft failure etiology between 2000–2011 and 2012–2023 patients in each of the mentioned groups. Interestingly, allograft thrombosis has a higher contribution percentage to allograft failure in 2012–2023 patients compared to 2000–2012 patients regardless of the number of previous transplants. Other etiologies’ differences between the two timeframes were either not significant statistically, or lower in the 2012–2023 group. Table 4 shows the difference in allograft failure etiologies between patients with one previous transplant and those with two or more previous transplants. None were statistically significant. Table 3 The etiology of allograft failure and the comparison between 2000–2011 and 2012–2023 patients in one previous transplant and the two or more groups. Allograft failure causes (% total available data) One previous transplant (n = 4114) p-value a OR a,b [95%CI] Two or More Previous Transplants (n = 754) p-value c OR c,b [95%CI] 2000–2011 (n = 3150) 2012–2023 (n = 964) 2000–2011 (n = 592) 2012–2023 (n = 162) Allograft thrombosis 109 (3.5%) 92 (9.5%) < 0.001 2.94 [2.20, 3.92] 20 (3.4%) 16 (9.9%) 0.001 3.13 [1.58, 6.19] Infection 87 (2.8%) 26 (2.7%) 0.91 0.97 [0.62. 1.52] 14 (2.4%) 6 (3.7%) 0.35 1.58 [0.60, 4.19] Primary non-function (allograft never functioned post transplant) 184 (5.8%) 17 (1.8%) < 0.001 0.28 [0.17, 0.47] 40 (6.8%) 2 (1.2%) 0.01 0.17 [0.04, 0.72] Recurrent disease 230 (7.3%) 67 (7%) 0.71 0.94 [0.71, 1.25] 43 (7.3%) 14 (8.6%) 0.55 1.20 [0.64, 2.26] Acute rejection 429 (13.6%) 148 (15.4%) 0.17 1.15 [0.93, 1.40] 92 (15.5%) 25 (15.4%) 0.97 0.99 [0.61. 1.60] Chronic rejection 1226 (38.9%) 275 (28.5%) < 0.001 0.62 [0.53, 0.73] 223 (37.7%) 41 (25.3%) 0.003 0.56 [0.37. 0.82] Other Causes d 885 (28.1%) 339 (35.2%) < 0.001 1.38 [1.19, 1.61] 160 (27%) 58 (35.8%) 0.02 1.50 [1.04, 2.17] a The calculated values are for the comparison between 2000–2011 and 2012–2023 patients in the group with one previous transplant b OR was calculated based on comparing a particular cause to all other reasons for allograft failure between 2000–2011 and 2012–2023 patients c The calculated values are for the comparison between 2000–2011 and 2012–2023 patients in the group with two or more previous transplants d Each cause contributed to less than one percent of total allograft failures in both groups Table 4 The etiology of allograft failure and the comparison between patients with one previous transplant and patients with two or more previous transplant Allograft failure causes (% total available data) One previous transplant (n = 4114) Two or More Previous Transplants (n = 754) P-value OR a [95%CI] Allograft thrombosis 201 (4.9%) 36 (4.8%) 0.89 0.97 [0.67, 1.40] Infection 113 (2.7%) 20 (2.7%) 0.88 0.96 [0.59. 1.56] Primary non-function (allograft never functioned post transplant) 201 (4.9%) 42 (5.6%) 0.42 1.14 [0.81, 1.61] Recurrent disease 297 (7.2%) 57 (7.6%) 0.74 1.05 [0.78, 1.41] Acute rejection 577 (14%) 117 (15.5%) 0.28 1.12 [0.90, 1.39] Chronic rejection 1501 (38.9%) 264 (35%) 0.43 0.93 [0.79, 1.10] Other causes b 1224 (29.8%) 218 (28.9%) 0.64 0.96 [0.80, 1.13] a OR was calculated based on comparing a particular cause to all other reasons for allograft failure between patients with one previous transplant and patients with two or more previous transplant b Each cause contributed to less than one percent of total allograft failures in both groups Discussion Kidney retransplantation benefits patients who experience allograft failure after a previous transplant. It provides an opportunity for improved renal function, enhancing quality of life, and reducing reliance on dialysis, a demanding and restrictive treatment [ 19 ]. Several studies have also analyzed the long-term survival benefit of kidney retransplantation, including the work of Sandal et al., who found that retransplantation offers a 68% lower adjusted risk of death compared to dialysis. [ 20 ] Extensive evaluations of factors influencing allograft and patient survival outcomes have been conducted to understand the relationship between retransplantation and these outcomes. By dividing the study cohort into two timeframes, we tracked survival progression over the years. Our findings demonstrate significant improvements in allograft and patient survival in the more recent years, reflecting advancements in surgical techniques, immunosuppressive therapies, and post-transplant care. [ 21 ] These results align with other studies documenting improved outcomes over the years as management strategies have evolved [ 21 , 22 ]. However, several critical challenges remain, particularly in mitigating risk factors and improving adverse outcomes. Some studies comparing survival outcomes between first and second kidney transplants have found that retransplantation offers similar allograft and patient survival rates as the initial transplant [ 23 , 24 ]. However, Redfield et al. identified that patients requiring a third kidney transplant had an increased incidence of DGF and a higher likelihood of allograft failure. Despite these challenges, they also noted that five-year survival following a second allograft is a strong predictor of survival for a third allograft [ 25 ]. Our study corroborates previous reports indicating that the risk of allograft failure increases with the number of prior transplants, suggesting that immunological challenges and cumulative ischemic injuries play crucial roles in determining long-term outcomes [ 10 ]. As the need for kidney transplants has increased, there has been a growing use of DCD and expanded criteria donors, which were previously considered suboptimal for donation [ 26 ]. It is well established that DCD kidneys carry an increased risk of allograft failure and poorer patient survival outcomes [ 27 , 28 ]. Nevertheless, implementing DCD kidney transplantation can safely enlarge the donor pool, despite a higher risk of primary non-function (PNF) and delayed allograft function (DGF) [ 29 ]. Our analysis of the 2012–2023 cohort indicates that patients receiving DCD kidneys exhibited slightly lower allograft survival rates compared to those receiving kidneys from donation after brain death (DBD) donors. This finding aligns with the systematic review by Vijayan et al. which reported that uncontrolled DCD kidney transplants had a median 1-year allograft survival of 82.7%, compared to 87.5% for controlled DCD transplants [ 30 ]. Our analysis confirms that higher KDPI scores and the presence of DGF are strong predictors of reduced allograft survival, consistent with findings in the literature suggesting that suboptimal donor quality and early post-transplant complications negatively impact long-term outcomes [ 31 , 32 ]. Similarly, studies executed by Poggio et al. have emphasized the importance of optimizing perioperative management strategies to enhance allograft longevity [ 33 ]. We noted that KDPI and DGF have a slightly higher risk for allograft failure in the more recent timeframe. This could be attributed to expanding donor criteria, particularly the higher utilization of DCD donors. While high KDPI and DGF are widely recognized as risk factors for allograft survival, the impact of cold ischemic time remains contentious. Some studies have found that longer cold ischemic times increase the risk of allograft failure, especially in DCD donors [ 34 , 35 ]. However, other research has not identified a significant impact of prolonged cold ischemic time on allograft survival [ 36 , 37 ]. To mitigate the effects of extended cold ischemic time, hypothermic machine perfusion has been shown to reduce the incidence of delayed allograft function, improving overall transplant outcomes [ 38 ], which could potentially explain our findings demonstrating cold ischemic time did not show a significant association with allograft survival in either cohort. One of the more notable findings of our study is the increased incidence of allograft thrombosis in the 2012–2023 cohort, emerging as a leading cause of allograft failure. Studies conducted outside the United States have examined the etiologies of allograft failure and provided insights into regional differences. For instance, a 2022 study reported that venous allograft thrombosis occurs in 1–6% of cases and is the primary cause of early allograft loss within the first month post-transplant [ 39 ]. Given the concurrent significance of DCD kidney use and allograft thrombosis in this cohort, we aimed to explore the underlying cause of this association. Allograft thrombosis has been identified as a cause of early allograft loss in both DCD and DBD transplants, possibly due to endothelial activation in the renal vasculature [ 40 ]. A study by Hamed et al. aimed to examine risk factors for early allograft rejection following transplantation found a higher incidence of acute venous and arterial thromboses in DCD donors than in DBD donors [ 28 ]. Since the 2010s, administering pre-mortem heparin to DCD donors before organ procurement has been standard practice in the U.S. [ 41 ]; however, no significant differences in survival were observed between allografts from heparin and no-heparin DCD donors [ 41 ]. Guerra et al. examined the use of anticoagulants and antiplatelets post-transplant [ 39 ], finding that aspirin use was more effective in reducing allograft thrombosis occurrence than anticoagulants. It is possible that DCD donor status was not the sole contributor to the high correlation with allograft thrombosis in the 2012–2023 cohort. Other factors, such as DGF and prolonged cold ischemic times, may have exacerbated this finding. Ponticelli et al. described a mechanism in which DGF is influenced by ischemia-reperfusion injury, a process affected by cold ischemic time [ 42 ]. They explained how reperfusion triggers the activation of inflammatory pathways due to endothelial cell injury, leading to platelet aggregation, increased coagulation factors, and ultimately, vessel thrombosis. In the 2012–2023 group, cold ischemic time was slightly higher and DGF was shown to be a strong predictor of allograft failure, further emphasizing the need for strategies to minimize ischemic injury. Several other risk factors for allograft thrombosis have been identified, including coagulopathies, extreme donor age (either very young or old), and hemodynamic instability in the recipient; however, in a significant percentage of cases, the exact etiology of thrombosis remains unclear [ 43 ]. Future studies should investigate potential modifiable factors contributing to this complication to optimize post-transplant outcomes. While our study provides valuable insights, certain limitations must be acknowledged. Reliance on a single data registry introduces potential selection bias. Additionally, registry-based data may not fully capture all relevant clinical and socioeconomic factors influencing retransplantation outcomes. The retrospective design of the study may also lead to missing data points. Namely, conclusions regarding the etiology of allograft failure may not be entirely reliable, as only about a quarter of patients had available data (this was especially more prominent in the more recent cohort). Other limitations include the potential for unmeasured confounders and variability in clinical practice across transplant centers. Future prospective studies with more comprehensive and diverse data sources are needed to validate our findings and explore additional variables impacting post-transplant success. Over the past two decades, significant progress has been made in kidney retransplantation outcomes, reflected in higher survival rates and more effective management strategies for transplant recipients. However, despite these improvements, several critical challenges persist. These include the rising incidence of allograft thrombosis, the cumulative decline in allograft survival with each subsequent transplant, and persisting concerns regarding donor organ quality and recipient-specific risk factors. Future studies should focus on identifying modifiable risk factors for DGF and improving organ preservation techniques for high KDPI and DCD donors. Additionally, further investigation is warranted to identify the risk factors and targeted interventions for allograft thrombosis in order to mitigate its impact on long-term survival. Abbreviations ESRD End-stage renal disease SRTR Scientific Registry of Transplant Recipients BMI Body Mass Index DCD Donation after cardiac death KDPI Kidney donor profile index CIT Cold ischemia time HLA Human Leukocyte Antigens DGF Delayed graft function HR Hazard ratio OR Odds ratio Declarations Conflict of interest The authors declare they do not have any personal or financial conflicts of interest. Funding statement The authors declare that there was no source of funding for this project. Keywords : Kidney Transplantation, Retransplantation, Allograft Survival, Patient Survival, Long-Term Outcomes, Prognosis Author Contribution Abolfazl Jamshidi: investigation, writing-original draft, writing-review and editing, formal analysis, data curation.Janice Liu: writing-original draft. Sajedeh Jadidi: writing-original draft. Emily Harland: writing-original draft. Mahmoudreza Moein: writing-review and editing, formal analysis, data curation. Reza Saidi: supervision, study design. 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Am J Kidney Dis. 2007;49(2):294–300. doi: 10.1053/j.ajkd.2006.11.022 Pardinhas C, Leal R, Figueiredo C, Fernandes M, Rodrigues L, Guedes M, Santos L, Romãozinho C, Escada L, Martinho A, Sá HO, Alves R, Figueiredo A. Kidney Retransplantation Outcomes: A Paired Recipient Control Study. Transplant Proc. 2022;54(5):1236–1241. doi: 10.1016/j.transproceed.2022.04.005 Magee JC, Barr ML, Basadonna GP, Johnson MR, Mahadevan S, McBride MA, Schaubel DE, Leichtman AB. Repeat organ transplantation in the United States, 1996–2005. Am J Transplant. 2007;7(5 Pt 2):1424–33. doi: 10.1111/j.1600-6143.2007.01786.x Lubetzky M, Tantisattamo E, Molnar MZ, Lentine KL, Basu A, Parsons RF, Woodside KJ, Pavlakis M, Blosser CD, Singh N, Concepcion BP, Adey D, Gupta G, Faravardeh A, Kraus E, Ong S, Riella LV, Friedewald J, Wiseman A, Aala A, Dadhania DM, Alhamad T. The failing kidney graft: A review and recommendations for the care and management of a complex group of patients. Am J Transplant. 2021;21(9):2937–2949. doi: 10.1111/ajt.16717 . Epub 2021 Jul 19 Loban K, Horton A, Robert JT, Hales L, Parajuli S, McAdams-DeMarco M, Sandal S. Perspectives and experiences of kidney transplant recipients with graft failure: A systematic review and meta-synthesis. Transplant Rev (Orlando). 2023;37(2):100761. doi: 10.1016/j.trre.2023.100761 . Epub 2023 Apr 13 Heaphy EL, Poggio ED, Flechner SM, Goldfarb DA, Askar M, Fatica R, Srinivas TR, Schold JD. Risk factors for retransplant kidney recipients: relisting and outcomes from patients' primary transplant. Am J Transplant. 2014;14(6):1356–67. doi: 10.1111/ajt.12690 El-Husseini A, Aghil A, Ramirez J, Sawaya B, Rajagopalan N, Baz M, Mei X, Davenport DL, Gedaly R. Outcome of kidney transplant in primary, repeat, and kidney-after-nonrenal solid-organ transplantation: 15-year analysis of recent UNOS database. Clin Transplant. 2017;31(11). doi: 10.1111/ctr.13108 Nieto-Ríos JF, Ochoa-García CL, Serna-Campuzano A, et al. Time of Cold Ischemia and Delayed Graft Function in a Cohort of Renal Transplant Patients in a Reference Center. Indian J Nephrol. 2019;29(1):8–14. doi: 10.4103/ijn.IJN_162_18 Sibulesky L, Leca N, Bakthavatsalam R, Perkins JD. Kidney retransplantation outcomes in adults aged 70 and older: Analysis of risk factors and survival. Clin Transplant. 2024;38(1):e15170. doi: 10.1111/ctr.15170 Sandal S, Ahn JB, Chen Y, Massie AB, Clark-Cutaia MN, Wu W, Cantarovich M, Segev DL, McAdams-DeMarco MA. Trends in the survival benefit of repeat kidney transplantation over the past 3 decades. Am J Transplant. 2023;23(5):666–672. doi: 10.1016/j.ajt.2023.01.008. Epub 2023 Jan 31 Hariharan S, Israni AK, Danovitch G. Long-Term Survival after Kidney Transplantation. N Engl J Med. 2021;385(8):729–743. doi: 10.1056/NEJMra2014530 Tonelli M, Wiebe N, Knoll G, Bello A, Browne S, Jadhav D, Klarenbach S, Gill J. Systematic review: kidney transplantation compared with dialysis in clinically relevant outcomes. Am J Transplant. 2011;11(10):2093–109. doi: 10.1111/j.1600-6143.2011.03686.x . Epub 2011 Aug 30 Ingsathit A, Kantachuvesiri S, Rattanasiri S, et al. Long-term outcome of kidney retransplantation in comparison with first kidney transplantation: a report from the Thai Transplantation Registry. Transplant Proc. 2013;45(4):1427–1430. doi: 10.1016/j.transproceed.2012.08.029 Barocci S, Valente U, Fontana I, et al. Long-term outcome on kidney retransplantation: a review of 100 cases from a single center. Transplant Proc. 2009;41(4):1156–1158. doi: 10.1016/j.transproceed.2009.03.083 Redfield RR, Gupta M, Rodriguez E, Wood A, Abt PL, Levine MH. Graft and patient survival outcomes of a third kidney transplant. Transplantation. 2015;99(2):416–423. doi: 10.1097/TP.0000000000000332 Barreda Monteoliva P, Redondo-Pachón D, Miñambres García E, Rodrigo Calabia E. Kidney transplant outcome of expanded criteria donors after circulatory death. Nefrologia (Engl Ed). 2022;42(2):135–144. doi: 10.1016/j.nefroe.2021.01.005 Alsolami E, Lotfy K, Alkhunaizi A, Cuerden M, Weir MA, House AA. Impact of Donation After Circulatory Death on Outcomes of Expanded Criteria Donor Kidney Transplants. Transplant Proc. 2024;56(1):50–57. doi: 10.1016/j.transproceed.2023.11.028 Hamed MO, Chen Y, Pasea L, et al. Early graft loss after kidney transplantation: risk factors and consequences. Am J Transplant. 2015;15(6):1632–1643. doi: 10.1111/ajt.13162 Rijkse E, Ceuppens S, Qi H, IJzermans JNM, Hesselink DA, Minnee RC. Implementation of donation after circulatory death kidney transplantation can safely enlarge the donor pool: A systematic review and meta-analysis. Int J Surg. 2021;92:106021. doi: 10.1016/j.ijsu.2021.106021 . Epub 2021 Jul 10 Vijayan K, Schroder HJ, Hameed A, Hitos K, Lo W, Laurence JM, Yoon PD, Nahm C, Lim WH, Lee T, Yuen L, Wong G, Pleass H. Kidney Transplantation Outcomes From Uncontrolled Donation After Circulatory Death: A Systematic Review and Meta-analysis. Transplantation. 2024;108(6):1422–1429. doi: 10.1097/TP.0000000000004937 . Epub 2024 Feb 16 Bachmann Q, Haberfellner F, Büttner-Herold M, Torrez C, Haller B, Assfalg V, Renders L, Amann K, Heemann U, Schmaderer C, Kemmner S. The Kidney Donor Profile Index (KDPI) Correlates With Histopathologic Findings in Post-reperfusion Baseline Biopsies and Predicts Kidney Transplant Outcome. Front Med (Lausanne). 2022;9:875206. doi: 10.3389/fmed.2022.875206 Pippias M, Stel VS, Arnol M, et al. Temporal trends in the quality of deceased donor kidneys and kidney transplant outcomes in Europe: an analysis by the ERA-EDTA Registry. Nephrol Dial Transplant. 2021;37(1):175–186. doi: 10.1093/ndt/gfab156 Poggio ED, Augustine JJ, Arrigain S, Brennan DC, Schold JD. Long-term kidney transplant graft survival-Making progress when most needed. Am J Transplant. 2021;21(8):2824–2832. doi: 10.1111/ajt.16463 . Epub 2021 Feb 8 Debout A, Foucher Y, Trébern-Launay K, et al. Each additional hour of cold ischemia time significantly increases the risk of graft failure and mortality following renal transplantation. Kidney Int. 2015;87(2):343–349. doi: 10.1038/ki.2014.304 Peters-Sengers H, Houtzager JHE, Idu MM, et al. Impact of Cold Ischemia Time on Outcomes of Deceased Donor Kidney Transplantation: An Analysis of a National Registry. Transplant Direct. 2019;5(5):e448. Published 2019 Apr 25. doi: 10.1097/TXD.0000000000000888 Lum EL, Homkrailas P, Abdalla B, Danovitch GM, Bunnapradist S. Cold Ischemia Time, Kidney Donor Profile Index, and Kidney Transplant Outcomes: A Cohort Study. Kidney Med. 2022;5(1):100570. Published 2022 Nov 13. doi: 10.1016/j.xkme.2022.100570 Ahlmark A, Sallinen V, Eerola V, Lempinen M, Helanterä I. Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study. Transpl Int. 2024;37:12309. Published 2024 Mar 1. doi: 10.3389/ti.2024.12309 Malinoski D, Saunders C, Swain S, et al. Hypothermia or Machine Perfusion in Kidney Donors. N Engl J Med. 2023;388(5):418–426. doi: 10.1056/NEJMoa2118265 Guerra R, Kawano PR, Amaro MP, et al. Acute graft thrombosis in patients who underwent renal transplant and received anticoagulant or antiplatelet agents. A systematic review and meta-analysis. Am J Clin Exp Urol. 2022;10(3):129–141 Narvaez JRF, Noyes K, Nie J, Kayler LK. Outcomes of DCD kidneys recovered for transplantation with versus without pre-mortem heparin administration. Clin Transplant. 2019;33(7):e13624. doi: 10.1111/ctr.13624 Kramer AH, Holliday K, Keenan S, et al. Premortem anticoagulation timing and dose in donation after circulatory death: multicentre study of associations with graft function. Can J Surg. 2022;65(4):E474-E484. Published 2022 Jul 28. doi: 10.1503/cjs.023120 Ponticelli C, Reggiani F, Moroni G. Delayed graft Function in Kidney Transplant: Risk Factors, Consequences and Prevention Strategies. J Pers Med. 2022;12(10):1557. Published 2022 Sep 21. doi: 10.3390/jpm12101557 Bakir N, Sluiter WJ, Ploeg RJ, van Son WJ, Tegzess AM. Primary renal graft thrombosis. Nephrol Dial Transplant. 1996;11(1):140–7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Jun, 2025 Read the published version in International Urology and Nephrology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6247432\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":443193692,\"identity\":\"3bccfb9e-47f3-4de9-bfc9-f2fa3fcc9a7a\",\"order_by\":0,\"name\":\"Abolfazl Jamshidi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Abolfazl\",\"middleName\":\"\",\"lastName\":\"Jamshidi\",\"suffix\":\"\"},{\"id\":443193693,\"identity\":\"140831e6-6092-4c06-8034-f95d69167877\",\"order_by\":1,\"name\":\"Janice Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Janice\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":443193694,\"identity\":\"82328981-80e3-440f-a213-c447d20ff05e\",\"order_by\":2,\"name\":\"Sajedeh Jadidi\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sajedeh\",\"middleName\":\"\",\"lastName\":\"Jadidi\",\"suffix\":\"\"},{\"id\":443193695,\"identity\":\"dca7b25b-850a-4be2-ad24-cc49b83a4e7d\",\"order_by\":3,\"name\":\"Harland Emily\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Harland\",\"middleName\":\"\",\"lastName\":\"Emily\",\"suffix\":\"\"},{\"id\":443193696,\"identity\":\"c81c1e1a-d5be-4289-ad01-25af775ac990\",\"order_by\":4,\"name\":\"Mahmoudreza Moein\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mahmoudreza\",\"middleName\":\"\",\"lastName\":\"Moein\",\"suffix\":\"\"},{\"id\":443193697,\"identity\":\"933cb717-702f-4439-8b1d-0c8d9cfb1f1f\",\"order_by\":5,\"name\":\"Reza F. Saidi\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBAC+QbGBonEPzZIQgcIaDE4ANLSlgZkMkNVE9QCxBKMbYdJ0cJ+uPHGw7bzidv5zx/8/KGCQY7vRgJ+LfI9ic0WiX9uJ+6ckcwsceAMg7EkIS0MBxLbJBI/3E7ccIOZQeJgGwOQQUjL+YdALTPOJW44f5j5x8F/DPWEtdwA2dJzIHHDgWQ2iYMNDAkGhLQY3HgI9EtbsjHQL2YWZ45JGM488wC/Fvn+9Ic3f7bZyW7nP/j4RkWNjTzfcUIOg1sHoSSIVI6kZRSMglEwCkYBJgAA/XhSv+ZSfhoAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"SUNY Upstate Medical University\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Reza\",\"middleName\":\"F.\",\"lastName\":\"Saidi\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-03-17 20:08:11\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6247432/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6247432/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1007/s11255-025-04585-0\",\"type\":\"published\",\"date\":\"2025-06-06T15:57:05+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":81025474,\"identity\":\"3949b842-18d3-4d7e-9e10-1311006f8279\",\"added_by\":\"auto\",\"created_at\":\"2025-04-21 10:33:02\",\"extension\":\"jpg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":461309,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAllograft and patient survival comparison between 2000-2011 and 2012-2023\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture1.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6247432/v1/69476f5033ad5e4fdf76d184.jpg\"},{\"id\":81026596,\"identity\":\"4420ebc9-08d6-41ed-bb50-f63c43e86862\",\"added_by\":\"auto\",\"created_at\":\"2025-04-21 10:41:02\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":966342,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAllograft survival rate comparison based on the number of previous transplants\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Picture2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6247432/v1/12f39dfaeb841fc9adfc2498.jpg\"},{\"id\":84242627,\"identity\":\"6c2da2b7-da9f-4b6d-bfdf-1f7c9232fc27\",\"added_by\":\"auto\",\"created_at\":\"2025-06-09 16:10:27\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2225918,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6247432/v1/8b4d925c-5bf0-4cf4-9ddf-36e0ea3697cc.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Trends and Outcomes in Kidney Retransplantation: A Two-Decade Longitudinal Analysis\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eKidney transplantation is the preferred treatment for patients with end-stage renal disease (ESRD), offering better quality of life, lower long-term morbidity and mortality rates, and cost-effectiveness compared to dialysis [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. However, allograft rejection remains a significant challenge, often leading to allograft loss. Understanding the factors contributing to allograft rejection is crucial for improving allograft survival. These factors include pre-operative considerations such as donor and recipient characteristics (age, gender, race, and immunological compatibility) [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e], as well as peri-operative and post-operative factors like cold and warm ischemia durations and immunosuppressive treatment [\\u003cspan additionalcitationids=\\\"CR5\\\" citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eDespite advances in transplantation, the lifespan of a transplanted kidney is limited. After the first year post-transplantation, up to 4% of patients may experience allograft loss and return to dialysis. [\\u003cspan additionalcitationids=\\\"CR8\\\" citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]. In the United States, the allograft failure rate within three years of transplantation in 2016 was 2.3% for living donor transplants and 4.8% for deceased donation transplants. [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e]. As the number of transplantations increases, so does the population experiencing allograft failure, necessitating considerations for retransplantation [\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e]. An estimated 20% of individuals on the kidney transplant waiting list have experienced allograft failure, accounting for 10\\u0026ndash;20% of all kidney transplant procedures [\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e]; moreover, there has been a steadily increasing number of kidney retransplant recipients [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eRetransplantation offers a substantial mortality benefit compared to long-term dialysis for patients with allograft failure. [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]. However, it is associated with higher immunological risks than initial transplants. [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]. Outcomes such as allograft survival and rejection rates are less favorable in retransplant patients compared to those undergoing primary transplantation [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]. Patients who experience acute rejection, delayed allograft function (DGF), or hospitalization within the first year of their primary transplant are more likely to encounter similar complications following retransplantation [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. While long-term outcomes of kidney retransplantation are increasingly studied, comprehensive reports on these outcomes are still relatively uncommon. [\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eEffective management strategies and the identification of risk factors for kidney retransplantation are crucial for healthcare providers to optimize patient care and potentially reduce the need for additional transplants. This study aims to analyze the outcomes of kidney retransplants in the United States, focusing on allograft and patient survival rates, factors influencing these outcomes, and the changes in prognosis in more recent years.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cp\\u003eA retrospective longitudinal analysis was performed utilizing data from the Scientific Registry of Transplant Recipients (SRTR) database, which provides detailed information on kidney transplant recipients and donors, including pretransplant data, baseline characteristics, follow-up data, and transplant outcomes.\\u003c/p\\u003e \\u003cp\\u003eWe extracted the information of all adult patients who underwent kidney retransplantation between January 2000, and May 2023 and divided the study period into two subgroups based on the time of the procedure: 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023. We further divided our patients according to the number of previous transplants: \\u0026ldquo;one\\u0026rdquo;, \\u0026ldquo;two\\u0026rdquo;, \\u0026ldquo;three or more\\u0026rdquo; previous transplants for assessing survival outcomes, and \\u0026ldquo;one\\u0026rdquo; and \\u0026ldquo;two or more\\u0026rdquo; previous transplants for allograft failure etiology evaluation. Our inclusion criteria were adult patients (aged\\u0026thinsp;\\u0026ge;\\u0026thinsp;18 years) who received at least one previous kidney transplant during this time period. We excluded people who were under 18 years of age, had multi-organ transplants, and those with incomplete follow-up data on patient and allograft survival.\\u003c/p\\u003e \\u003cp\\u003eThe primary characteristics of donors and recipients that we evaluated include age, gender, recipient BMI, recipient race, donor type (living or deceased), donation after circulatory death (DCD), kidney donor profile index (KDPI), cold ischemic time (CIT), number of HLA mismatches, primary diagnoses, and duration of hospital stay. KDPI is an objective measure of allograft quality that considers donor age, height, race, medical history (including diabetes and hypertension), kidney function indices, cause of death, and more [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. For live donors, the KDPI is similar but includes criteria such as a BMI\\u0026thinsp;\\u0026lt;\\u0026thinsp;35 kg/m\\u0026sup2;, absence of infections or malignancies, and good kidney function [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e]. A higher KDPI indicates an allograft that is more likely to fail. An additional factor we evaluated was DGF, defined as the need for dialysis within the first week after transplantation [\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]. CIT was defined as the time between the start of chilling the allograft with preservation fluid to warming the allograft with blood circulation from the recipient. A cold ischemic time of greater than 12 hours is typically considered to increase the risk of allograft failure or even the risk of delayed allograft function [\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eThe primary objective of the study was to determine patient survival after retransplantation, along with the success of the allograft transplantation as a one- and five-year allograft survival rate. Allograft failure was considered to be the loss of kidney function necessitating dialysis or retransplantation as well as patient death attributed to allograft failure. Patient survival was defined as the time from retransplantation to patient death. Patients with no reported date of death were presumed to be alive as of May 2023. The secondary objective was to identify the most common contributory cause of allograft failure in each cohort and to assess the effect of different factors on the survival rate of allografts. This study followed the STROBE reporting guidelines.\\u003c/p\\u003e \\u003cp\\u003eIBM SPSS 29 software was utilized for the analysis of baseline characteristics and outcomes of each study group. Multiple tests comprised our analysis depending on the type of variable that was measured: T-test for univariate analysis of continuous variables, chi-square for categorical variables, and Kaplan-Meier curves for patient and allograft survival rates. Associated with the continuous variables, means and standard deviations were calculated, and proportions and percentages were calculated for categorical variables. Additionally, a Cox regression analysis was performed to determine how allograft survival was influenced by multivariate factors such as donors\\u0026rsquo; BMI, KDPI, DCD donor, cold ischemia time, and DGF. Odds ratios were calculated between the different timeframe groups for one previous transplant or two or more transplants to compare the contribution of different etiologies for allograft failure. All \\u003cem\\u003ep\\u003c/em\\u003e-values greater than 0.05 were considered significant.\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eBased on the inclusion and exclusion criteria, a total of 34,230 patients \\u0026ndash; who had at least one previous kidney transplant - were evaluated. They were further divided into two groups according to the time of the retransplant; 12,224 patients had their procedure from 2001 to 2011 and 22,006 patients underwent retransplant from 2012 to 2023.\\u003c/p\\u003e \\u003cp\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e shows the difference in demographic characteristics between the two groups. Although some of the characteristics are significantly different, this is mostly due to the large sample size and does not necessarily translate to clinical significance. Notably, DCD donors were significantly higher in the 2012\\u0026ndash;2023 cohort (21.3% vs 8.8%, \\u003cem\\u003ep\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001). The most common primary diagnosis in both timeframes was hypertensive nephropathy.\\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\\u003eKidney re-transplant donors and recipients\\u0026rsquo; demographic characteristics comparison between patients in 2001\\u0026ndash;2011 and 2012\\u0026ndash;2023 timeframes.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\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=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCharacteristics\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e2001\\u0026ndash;2011\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;12224)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e2012\\u0026ndash;2023\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;22006)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\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\\u003eRecipients\\u0026rsquo; Age (mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e43.70\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e46.56\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;14.17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eRecipients\\u0026rsquo; Gender\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e0.954\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5116 (41.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e7108 (58.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9218 (41.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e12788 (58.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRecipients\\u0026rsquo; BMI (mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e26.02\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e26.65\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;5.45\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRecipients\\u0026rsquo; Race\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ewhite\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e7619 (62.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e11373 (51.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eBlack\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e2776 (22.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e5704 (25.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHispanic\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e1280 (10.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e3392 (15.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAsian\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e417 (3.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1184 (5.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e132 (1.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e353 (1.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDonors\\u0026rsquo;Age (mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e36.5\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;14.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e37.76\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;13.80\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eDonors\\u0026rsquo;gender\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eFemale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eMale\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5421 (44.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6803 (55.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e9454 (43%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e12552 (57%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eDonor type\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eDeceased\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eLiving\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eDeceased\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eLiving\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e0.014\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e9019 (73.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3205 (26.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e16785 (76.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e5221 (23.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eDCD Donor (within the deceased donor population)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eYes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eNo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eYes\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eNo\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e796 (8.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e8223 (91.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e3578 (21.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e13207 (78.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKDPI (%)\\u003c/p\\u003e \\u003cp\\u003e(mean\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e35\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;25\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e36\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.232\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCold ischemic time (hours\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e14.00\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;10.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e14.96\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;9.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003enumber of HLA Mismatch\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e0\\u0026ndash;3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u0026ndash;6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0\\u0026ndash;3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e4\\u0026ndash;6\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e5897 (48.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e6277 (51.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e10221 (46.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e11721 (53.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDuration of Hospital Stay\\u003c/p\\u003e \\u003cp\\u003e(days\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;SD)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e9.87\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;54.30\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e8.43\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;55.69\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.020\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary Diagnosis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"11\\\" rowspan=\\\"12\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eIgA Nephropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e647 (5.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1721 (8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eFocal Segmental Glomerular Sclerosis (FSGS)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e1073 (9.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e2547 (11.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePolycystic Kidney Disease\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e750 (6.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1393 (6.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eSystemic Lupus Erythematosus (SLE)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e548 (4.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1075 (5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHypoplasia/Dysplasia/Dysgenesis/Agenesis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e268 (2.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e585 (2.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eHypertensive Nephropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e1811 (16%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e3627 (16.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChronic Glomerulonephritis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e1248 (11%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1481 (6.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCongenital Obstructive Uropathy\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e312 (2.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e756 (3.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eType 1 Diabetes Mellitus\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e252 (2.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e444 (2.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eType 2 Diabetes Mellitus\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e273 (2.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e1129 (5.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther Diagnoses*\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003e4156 (36.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c5\\\" namest=\\\"c4\\\"\\u003e \\u003cp\\u003e6708 (31.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003e*Apart from the unknown causes, each of the other causes contributes to less than one percent of total diagnoses in both cohorts\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe one-year and five-year allograft survivals were significantly higher in the 2012\\u0026ndash;2023 group compared to 2000\\u0026ndash;2011 (93.6% compared to 89.5% and 75.9% compared to 69.3%, respectively, both \\u003cem\\u003ep\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;000.1, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e (a)). Although still higher in the 2012\\u0026ndash;2023 group, the difference was less prominent in one-year and five-year patient survival in the two groups (97% compared to 95.3% and 84.8% compared to 83.7%, both \\u003cem\\u003ep\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;000.1, Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e (b)).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eWhen evaluating the five-year allograft survival, we further divided our population based on the number of previous transplants. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e (a) indicates that the second transplant had better allograft outcomes than the third transplants and the third better than the fourth and more transplants (73.4% vs 71.8% vs 62.3%, \\u003cem\\u003ep\\u003c/em\\u003e-value\\u0026thinsp;\\u0026lt;\\u0026thinsp;000.1). We also compared the difference in five-year allograft survival between the two timeframes in each of these groups (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e (b), (c) and (d)). The five-year allograft survival in 2000\\u0026ndash;2011 vs 2012\\u0026ndash;2023 was 70.2% vs 75.9%, 67.1% vs 76.5%, and 59.1% vs 70.9% in the groups with one, two, and three or more prior transplants, respectively.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eA multivariant Cox regression test was conducted to demonstrate different factors that could affect allograft survival in each timeframe (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). DGF and higher KDPI were related to less favorable allograft survival in both time frames (especially 2012\\u0026ndash;2023). Allograft survival was also slightly worse in DCD donors in 2012\\u0026ndash;2023 patients. Other factors did not seem to have statistically and/or clinically significant effects on allograft survival.\\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\\u003eMulti-variant cox regression test with the effect of different factors as a hazard ratio with a 95% confidence interval on allograft survival in re-transplant patients in 2001\\u0026ndash;2011 and 2012\\u0026ndash;2023 time frames.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"3\\\"\\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 \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eParameter\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eHR, 95% CI\\u003c/p\\u003e \\u003cp\\u003e2001\\u0026ndash;2011\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eHR, 95% CI\\u003c/p\\u003e \\u003cp\\u003e2012\\u0026ndash;2023\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKDPI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.96 [1.70, 2.26]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2.34 [1.82, 3.01]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDonors\\u0026rsquo; BMI\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.000 [0.996, 1.004]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.000 [0.993, 1.006]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDonors\\u0026rsquo; Age\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.004 [1.002, 1.007]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.000 [0.996, 1.004]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003enumber of HLA Mismatch (0\\u0026ndash;3 or 4\\u0026ndash;6)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.03 [1.01, 1.04]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.02 [0.99, 1.04]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDCD donor\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.03 [0.98, 1.08]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.11 [1.04, 1.17]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCold ischemic time\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.005 [1.002, 1.008]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.005 [1.000, 1.010]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eDGF\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1.69 [1.60, 1.79]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e1.79 [1.63, 1.97]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003eThe available data for the allograft failure etiology were limited; for this reason and to have a more apprehensible analysis, we divided the patients into two groups based on the number of previous transplants (instead of three, unlike our evaluation for five-year allograft survival): patients with one previous transplants and patients with two or more previous transplants. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e compares the contribution of each allograft failure etiology between 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023 patients in each of the mentioned groups. Interestingly, allograft thrombosis has a higher contribution percentage to allograft failure in 2012\\u0026ndash;2023 patients compared to 2000\\u0026ndash;2012 patients regardless of the number of previous transplants. Other etiologies\\u0026rsquo; differences between the two timeframes were either not significant statistically, or lower in the 2012\\u0026ndash;2023 group. Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e shows the difference in allograft failure etiologies between patients with one previous transplant and those with two or more previous transplants. None were statistically significant.\\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\\u003eThe etiology of allograft failure and the comparison between 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023 patients in one previous transplant and the two or more groups.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"9\\\"\\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=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAllograft failure causes (% total available data)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eOne previous transplant\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;4114)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003ep-value\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eOR\\u003csup\\u003ea,b\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003e[95%CI]\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e \\u003cp\\u003eTwo or More Previous Transplants\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;754)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003ep-value\\u003csup\\u003ec\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003eOR\\u003csup\\u003ec,b\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003e[95%CI]\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e2000\\u0026ndash;2011\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;3150)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2012\\u0026ndash;2023\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;964)\\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 \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e2000\\u0026ndash;2011\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;592)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e2012\\u0026ndash;2023\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;162)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAllograft thrombosis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e109 (3.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e92 (9.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e2.94 [2.20, 3.92]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e20 (3.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e16 (9.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e3.13 [1.58, 6.19]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eInfection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e87 (2.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e26 (2.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.97 [0.62. 1.52]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e14 (2.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e6 (3.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e1.58 [0.60, 4.19]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary non-function (allograft never functioned post transplant)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e184 (5.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e17 (1.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.28 [0.17, 0.47]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e40 (6.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e2 (1.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.17 [0.04, 0.72]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRecurrent disease\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e230 (7.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e67 (7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.94 [0.71, 1.25]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e43 (7.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e14 (8.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e1.20 [0.64, 2.26]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAcute rejection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e429 (13.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e148 (15.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e0.17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.15 [0.93, 1.40]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e92 (15.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e25 (15.4%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.99 [0.61. 1.60]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChronic rejection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1226 (38.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e275 (28.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.62 [0.53, 0.73]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e223 (37.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e41 (25.3%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.003\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e0.56 [0.37. 0.82]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther Causes\\u003csup\\u003ed\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e885 (28.1%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e339 (35.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e1.38 [1.19, 1.61]\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e160 (27%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e58 (35.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e0.02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e1.50 [1.04, 2.17]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e The calculated values are for the comparison between 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023 patients in the group with one previous transplant\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003eb\\u003c/sup\\u003e OR was calculated based on comparing a particular cause to all other reasons for allograft failure between 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023 patients\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003ec\\u003c/sup\\u003e The calculated values are for the comparison between 2000\\u0026ndash;2011 and 2012\\u0026ndash;2023 patients in the group with two or more previous transplants\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"9\\\"\\u003e\\u003csup\\u003ed\\u003c/sup\\u003e Each cause contributed to less than one percent of total allograft failures in both groups\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab4\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eThe etiology of allograft failure and the comparison between patients with one previous transplant and patients with two or more previous transplant\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"6\\\"\\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=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAllograft failure causes (% total available data)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c3\\\" namest=\\\"c2\\\"\\u003e \\u003cp\\u003eOne previous transplant\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;4114)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eTwo or More Previous Transplants\\u003c/p\\u003e \\u003cp\\u003e(n\\u0026thinsp;=\\u0026thinsp;754)\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003eP-value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eOR\\u003csup\\u003ea\\u003c/sup\\u003e\\u003c/p\\u003e \\u003cp\\u003e[95%CI]\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAllograft thrombosis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e201 (4.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e36 (4.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.97 [0.67, 1.40]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eInfection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e113 (2.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e20 (2.7%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.88\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.96 [0.59. 1.56]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003ePrimary non-function (allograft never functioned post transplant)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e201 (4.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e42 (5.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.42\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.14 [0.81, 1.61]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eRecurrent disease\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e297 (7.2%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e57 (7.6%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.74\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.05 [0.78, 1.41]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eAcute rejection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e577 (14%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e117 (15.5%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.28\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e1.12 [0.90, 1.39]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eChronic rejection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1501 (38.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e264 (35%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.93 [0.79, 1.10]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eOther causes\\u003csup\\u003eb\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003e1224 (29.8%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003e218 (28.9%)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.64\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003e0.96 [0.80, 1.13]\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003ctfoot\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003e\\u003csup\\u003ea\\u003c/sup\\u003e OR was calculated based on comparing a particular cause to all other reasons for allograft failure between patients with one previous transplant and patients with two or more previous transplant\\u003c/td\\u003e\\u003c/tr\\u003e \\u003ctr\\u003e\\u003ctd colspan=\\\"6\\\"\\u003e\\u003csup\\u003eb\\u003c/sup\\u003e Each cause contributed to less than one percent of total allograft failures in both groups\\u003c/td\\u003e\\u003c/tr\\u003e \\u003c/tfoot\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eKidney retransplantation benefits patients who experience allograft failure after a previous transplant. It provides an opportunity for improved renal function, enhancing quality of life, and reducing reliance on dialysis, a demanding and restrictive treatment [\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]. Several studies have also analyzed the long-term survival benefit of kidney retransplantation, including the work of Sandal et al., who found that retransplantation offers a 68% lower adjusted risk of death compared to dialysis. [\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e] Extensive evaluations of factors influencing allograft and patient survival outcomes have been conducted to understand the relationship between retransplantation and these outcomes.\\u003c/p\\u003e \\u003cp\\u003eBy dividing the study cohort into two timeframes, we tracked survival progression over the years. Our findings demonstrate significant improvements in allograft and patient survival in the more recent years, reflecting advancements in surgical techniques, immunosuppressive therapies, and post-transplant care. [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e] These results align with other studies documenting improved outcomes over the years as management strategies have evolved [\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]. However, several critical challenges remain, particularly in mitigating risk factors and improving adverse outcomes.\\u003c/p\\u003e \\u003cp\\u003eSome studies comparing survival outcomes between first and second kidney transplants have found that retransplantation offers similar allograft and patient survival rates as the initial transplant [\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]. However, Redfield et al. identified that patients requiring a third kidney transplant had an increased incidence of DGF and a higher likelihood of allograft failure. Despite these challenges, they also noted that five-year survival following a second allograft is a strong predictor of survival for a third allograft [\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e]. Our study corroborates previous reports indicating that the risk of allograft failure increases with the number of prior transplants, suggesting that immunological challenges and cumulative ischemic injuries play crucial roles in determining long-term outcomes [\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eAs the need for kidney transplants has increased, there has been a growing use of DCD and expanded criteria donors, which were previously considered suboptimal for donation [\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]. It is well established that DCD kidneys carry an increased risk of allograft failure and poorer patient survival outcomes [\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Nevertheless, implementing DCD kidney transplantation can safely enlarge the donor pool, despite a higher risk of primary non-function (PNF) and delayed allograft function (DGF) [\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]. Our analysis of the 2012\\u0026ndash;2023 cohort indicates that patients receiving DCD kidneys exhibited slightly lower allograft survival rates compared to those receiving kidneys from donation after brain death (DBD) donors. This finding aligns with the systematic review by Vijayan et al. which reported that uncontrolled DCD kidney transplants had a median 1-year allograft survival of 82.7%, compared to 87.5% for controlled DCD transplants [\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eOur analysis confirms that higher KDPI scores and the presence of DGF are strong predictors of reduced allograft survival, consistent with findings in the literature suggesting that suboptimal donor quality and early post-transplant complications negatively impact long-term outcomes [\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]. Similarly, studies executed by Poggio et al. have emphasized the importance of optimizing perioperative management strategies to enhance allograft longevity [\\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]. We noted that KDPI and DGF have a slightly higher risk for allograft failure in the more recent timeframe. This could be attributed to expanding donor criteria, particularly the higher utilization of DCD donors.\\u003c/p\\u003e \\u003cp\\u003eWhile high KDPI and DGF are widely recognized as risk factors for allograft survival, the impact of cold ischemic time remains contentious. Some studies have found that longer cold ischemic times increase the risk of allograft failure, especially in DCD donors [\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e]. However, other research has not identified a significant impact of prolonged cold ischemic time on allograft survival [\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e]. To mitigate the effects of extended cold ischemic time, hypothermic machine perfusion has been shown to reduce the incidence of delayed allograft function, improving overall transplant outcomes [\\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e], which could potentially explain our findings demonstrating cold ischemic time did not show a significant association with allograft survival in either cohort.\\u003c/p\\u003e \\u003cp\\u003eOne of the more notable findings of our study is the increased incidence of allograft thrombosis in the 2012\\u0026ndash;2023 cohort, emerging as a leading cause of allograft failure. Studies conducted outside the United States have examined the etiologies of allograft failure and provided insights into regional differences. For instance, a 2022 study reported that venous allograft thrombosis occurs in 1\\u0026ndash;6% of cases and is the primary cause of early allograft loss within the first month post-transplant [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e]. Given the concurrent significance of DCD kidney use and allograft thrombosis in this cohort, we aimed to explore the underlying cause of this association. Allograft thrombosis has been identified as a cause of early allograft loss in both DCD and DBD transplants, possibly due to endothelial activation in the renal vasculature [\\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e40\\u003c/span\\u003e]. A study by Hamed et al. aimed to examine risk factors for early allograft rejection following transplantation found a higher incidence of acute venous and arterial thromboses in DCD donors than in DBD donors [\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]. Since the 2010s, administering pre-mortem heparin to DCD donors before organ procurement has been standard practice in the U.S. [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]; however, no significant differences in survival were observed between allografts from heparin and no-heparin DCD donors [\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e]. Guerra et al. examined the use of anticoagulants and antiplatelets post-transplant [\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e], finding that aspirin use was more effective in reducing allograft thrombosis occurrence than anticoagulants. It is possible that DCD donor status was not the sole contributor to the high correlation with allograft thrombosis in the 2012\\u0026ndash;2023 cohort. Other factors, such as DGF and prolonged cold ischemic times, may have exacerbated this finding. Ponticelli et al. described a mechanism in which DGF is influenced by ischemia-reperfusion injury, a process affected by cold ischemic time [\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e]. They explained how reperfusion triggers the activation of inflammatory pathways due to endothelial cell injury, leading to platelet aggregation, increased coagulation factors, and ultimately, vessel thrombosis. In the 2012\\u0026ndash;2023 group, cold ischemic time was slightly higher and DGF was shown to be a strong predictor of allograft failure, further emphasizing the need for strategies to minimize ischemic injury. Several other risk factors for allograft thrombosis have been identified, including coagulopathies, extreme donor age (either very young or old), and hemodynamic instability in the recipient; however, in a significant percentage of cases, the exact etiology of thrombosis remains unclear [\\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e43\\u003c/span\\u003e]. Future studies should investigate potential modifiable factors contributing to this complication to optimize post-transplant outcomes.\\u003c/p\\u003e \\u003cp\\u003eWhile our study provides valuable insights, certain limitations must be acknowledged. Reliance on a single data registry introduces potential selection bias. Additionally, registry-based data may not fully capture all relevant clinical and socioeconomic factors influencing retransplantation outcomes. The retrospective design of the study may also lead to missing data points. Namely, conclusions regarding the etiology of allograft failure may not be entirely reliable, as only about a quarter of patients had available data (this was especially more prominent in the more recent cohort). Other limitations include the potential for unmeasured confounders and variability in clinical practice across transplant centers. Future prospective studies with more comprehensive and diverse data sources are needed to validate our findings and explore additional variables impacting post-transplant success.\\u003c/p\\u003e \\u003cp\\u003eOver the past two decades, significant progress has been made in kidney retransplantation outcomes, reflected in higher survival rates and more effective management strategies for transplant recipients. However, despite these improvements, several critical challenges persist. These include the rising incidence of allograft thrombosis, the cumulative decline in allograft survival with each subsequent transplant, and persisting concerns regarding donor organ quality and recipient-specific risk factors. Future studies should focus on identifying modifiable risk factors for DGF and improving organ preservation techniques for high KDPI and DCD donors. Additionally, further investigation is warranted to identify the risk factors and targeted interventions for allograft thrombosis in order to mitigate its impact on long-term survival.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cdiv class=\\\"DefinitionList\\\"\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eESRD\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eEnd-stage renal disease\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eSRTR\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eScientific Registry of Transplant Recipients\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eBMI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eBody Mass Index\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDCD\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eDonation after cardiac death\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eKDPI\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eKidney donor profile index\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eCIT\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eCold ischemia time\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHLA\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHuman Leukocyte Antigens\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eDGF\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eDelayed graft function\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eHR\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eHazard ratio\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003cdiv class=\\\"DefinitionListEntry\\\"\\u003e \\u003cdiv class=\\\"Term\\\"\\u003eOR\\u003c/div\\u003e \\u003cdiv class=\\\"Description\\\"\\u003e \\u003cp\\u003eOdds ratio\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eConflict of interest\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare they do not have any personal or financial conflicts of interest.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding statement\\u003c/h2\\u003e \\u003cp\\u003eThe authors declare that there was no source of funding for this project.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eKeywords\\u003c/b\\u003e: Kidney Transplantation, Retransplantation, Allograft Survival, Patient Survival, Long-Term Outcomes, Prognosis\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eAbolfazl Jamshidi: investigation, writing-original draft, writing-review and editing, formal analysis, data curation.Janice Liu: writing-original draft. Sajedeh Jadidi: writing-original draft. Emily Harland: writing-original draft. Mahmoudreza Moein: writing-review and editing, formal analysis, data curation. Reza Saidi: supervision, study design.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eObadiah M, Carl S, Ahmed H. Kidney transplantation versus dialysis in Zimbabwe: a systematic review of the cost-effectiveness. J Egypt Soc Nephrol Transplant. 2022 Apr-Jun;22(2):71\\u0026ndash;85. doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.4103/jesnt.jesnt_31_21\\u003c/span\\u003e\\u003cspan address=\\\"10.4103/jesnt.jesnt_31_21\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLemoine M, Titeca Beauport D, Lobbedez T, Choukroun G, Hurault de Ligny B, Hazzan M, Guerrot D, Bertrand D. Risk Factors for Early Graft Failure and Death After Kidney Transplantation in Recipients Older Than 70 Years. Kidney Int Rep. 2019;4(5):656\\u0026ndash;666. doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.ekir.2019.01.014\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.ekir.2019.01.014\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eForoutan F, Friesen EL, Clark KE, Motaghi S, Zyla R, Lee Y, Kamran R, Ali E, De Snoo M, Orchanian-Cheff A, Ribic C, Treleaven DJ, Guyatt G, Meade MO. Risk Factors for 1-Year Graft Loss After Kidney Transplantation: Systematic Review and Meta-Analysis. 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Front Med (Lausanne). 2022;9:875206. doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/fmed.2022.875206\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/fmed.2022.875206\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePippias M, Stel VS, Arnol M, et al. Temporal trends in the quality of deceased donor kidneys and kidney transplant outcomes in Europe: an analysis by the ERA-EDTA Registry. Nephrol Dial Transplant. 2021;37(1):175\\u0026ndash;186. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1093/ndt/gfab156\\u003c/span\\u003e\\u003cspan address=\\\"10.1093/ndt/gfab156\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePoggio ED, Augustine JJ, Arrigain S, Brennan DC, Schold JD. Long-term kidney transplant graft survival-Making progress when most needed. Am J Transplant. 2021;21(8):2824\\u0026ndash;2832. doi: \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1111/ajt.16463\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/ajt.16463\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e. Epub 2021 Feb 8\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDebout A, Foucher Y, Tr\\u0026eacute;bern-Launay K, et al. Each additional hour of cold ischemia time significantly increases the risk of graft failure and mortality following renal transplantation. Kidney Int. 2015;87(2):343\\u0026ndash;349. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1038/ki.2014.304\\u003c/span\\u003e\\u003cspan address=\\\"10.1038/ki.2014.304\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePeters-Sengers H, Houtzager JHE, Idu MM, et al. Impact of Cold Ischemia Time on Outcomes of Deceased Donor Kidney Transplantation: An Analysis of a National Registry. Transplant Direct. 2019;5(5):e448. Published 2019 Apr 25. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1097/TXD.0000000000000888\\u003c/span\\u003e\\u003cspan address=\\\"10.1097/TXD.0000000000000888\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLum EL, Homkrailas P, Abdalla B, Danovitch GM, Bunnapradist S. Cold Ischemia Time, Kidney Donor Profile Index, and Kidney Transplant Outcomes: A Cohort Study. Kidney Med. 2022;5(1):100570. Published 2022 Nov 13. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1016/j.xkme.2022.100570\\u003c/span\\u003e\\u003cspan address=\\\"10.1016/j.xkme.2022.100570\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAhlmark A, Sallinen V, Eerola V, Lempinen M, Helanter\\u0026auml; I. Characteristics of Delayed Graft Function and Long-Term Outcomes After Kidney Transplantation From Brain-Dead Donors: A Single-Center and Multicenter Registry-Based Retrospective Study. Transpl Int. 2024;37:12309. Published 2024 Mar 1. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3389/ti.2024.12309\\u003c/span\\u003e\\u003cspan address=\\\"10.3389/ti.2024.12309\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMalinoski D, Saunders C, Swain S, et al. Hypothermia or Machine Perfusion in Kidney Donors. N Engl J Med. 2023;388(5):418\\u0026ndash;426. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1056/NEJMoa2118265\\u003c/span\\u003e\\u003cspan address=\\\"10.1056/NEJMoa2118265\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGuerra R, Kawano PR, Amaro MP, et al. Acute graft thrombosis in patients who underwent renal transplant and received anticoagulant or antiplatelet agents. A systematic review and meta-analysis. Am J Clin Exp Urol. 2022;10(3):129\\u0026ndash;141\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNarvaez JRF, Noyes K, Nie J, Kayler LK. Outcomes of DCD kidneys recovered for transplantation with versus without pre-mortem heparin administration. Clin Transplant. 2019;33(7):e13624. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1111/ctr.13624\\u003c/span\\u003e\\u003cspan address=\\\"10.1111/ctr.13624\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKramer AH, Holliday K, Keenan S, et al. Premortem anticoagulation timing and dose in donation after circulatory death: multicentre study of associations with graft function. Can J Surg. 2022;65(4):E474-E484. Published 2022 Jul 28. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.1503/cjs.023120\\u003c/span\\u003e\\u003cspan address=\\\"10.1503/cjs.023120\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePonticelli C, Reggiani F, Moroni G. Delayed graft Function in Kidney Transplant: Risk Factors, Consequences and Prevention Strategies. J Pers Med. 2022;12(10):1557. Published 2022 Sep 21. doi:\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.3390/jpm12101557\\u003c/span\\u003e\\u003cspan address=\\\"10.3390/jpm12101557\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBakir N, Sluiter WJ, Ploeg RJ, van Son WJ, Tegzess AM. Primary renal graft thrombosis. Nephrol Dial Transplant. 1996;11(1):140\\u0026ndash;7\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Kidney Transplantation, Retransplantation, Allograft Survival, Patient Survival, Long-Term Outcomes, Prognosis\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6247432/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6247432/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003ePurpose:\\u003c/strong\\u003e We aimed to evaluate kidney retransplantation outcomes to optimize patient care and reduce the risk of further retransplantation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods:\\u003c/strong\\u003e We conducted a retrospective longitudinal analysis of the SRTR database for kidney retransplants performed in the United States from January 2000 to May 2023. Patients were divided into subgroups based on transplant date and number of previous transplants. Outcomes were assessed by patient and allograft survival.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults:\\u003c/strong\\u003e A total of 34,230 patients were evaluated (12,224 in 2001–2011, 22,006 in 2012–2023). The proportion of DCD donors was significantly higher in 2012–2023 (21.3% vs. 8.8%, p \\u0026lt; 0.001). Both patient and allograft survival improved in the more recent time frame (5-year survival: 84.8% vs. 83.7% for patients; 75.9% vs. 69.3% for allografts, p \\u0026lt; 0.001). Allograft failure rates were higher with increasing retransplant attempts (5-year survival: 73.4% vs. 71.8% vs. 62.3% for first, second, and third+ retransplants, p \\u0026lt; 0.001). DGF increased failure risk (HR: 1.69 [1.60–1.79] in 2000–2011; HR: 1.79 [1.63–1.97] in 2012–2023), as did higher KDPI (HR: 1.96 [1.70–2.26] in 2000–2011; HR: 2.34 [1.82–3.01] in 2012–2023). Allograft thrombosis contribution as an etiology for failure increased (OR: 2.94 [2.20, 3.92] for the first; OR: 3.13 [1.58, 6.79] \\u0026nbsp;for the second+ retransplants).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConclusion:\\u003c/strong\\u003e Kidney retransplant outcomes have improved, but each successive transplant has a poorer prognosis. Careful patient selection and risk assessment, especially regarding high KDPI and DGF, are critical. Further investigation is needed into the rising proportion of allograft thrombosis.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Trends and Outcomes in Kidney Retransplantation: A Two-Decade Longitudinal Analysis\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-04-21 10:32:57\",\"doi\":\"10.21203/rs.3.rs-6247432/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"85fa6eee-20c0-4427-9d84-d41fc5f9c36b\",\"owner\":[],\"postedDate\":\"April 21st, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-06-09T16:04:13+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6247432\",\"link\":\"https://doi.org/10.1007/s11255-025-04585-0\",\"journal\":{\"identity\":\"international-urology-and-nephrology\",\"isVorOnly\":false,\"title\":\"International Urology and Nephrology\"},\"publishedOn\":\"2025-06-06 15:57:05\",\"publishedOnDateReadable\":\"June 6th, 2025\"},\"versionCreatedAt\":\"2025-04-21 10:32:57\",\"video\":\"\",\"vorDoi\":\"10.1007/s11255-025-04585-0\",\"vorDoiUrl\":\"https://doi.org/10.1007/s11255-025-04585-0\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6247432\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6247432\",\"identity\":\"rs-6247432\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}