The Outcome of Thrombotic Microangiopathy in Kidney Transplant Recipients

The Outcome of Thrombotic Microangiopathy in Kidney Transplant Recipients | 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 The Outcome of Thrombotic Microangiopathy in Kidney Transplant Recipients Kanza Haq, Shanshan Lin, Alana Dasgupta, Zainab Obaidi, Serena Bagnasco, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4688690/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2024 Read the published version in BMC Nephrology → Version 1 posted 5 You are reading this latest preprint version Abstract Background The outcome of kidney transplant recipients with a history of complement-mediated thrombotic microangiopathy (cTMA) and those who develop post-transplant de novo TMA (dnTMA) is largely unknown. Methods We retrospectively studied all kidney transplant recipients with end-stage kidney disease secondary to cTMA and those who developed dnTMA, between Jan 2000 and Dec 2020 in our center. Results We identified 134 patients, 22 with cTMA and 112 had dnTMA. Patients with cTMA were younger at the time of TMA diagnosis (age at diagnosis, 28.9 ± 16.3. vs 46.5 ± 16.0 years; P < 0.001). T-cell mediated rejection, borderline rejection, and calcineurin inhibitor toxicity were more prevalent in the first kidney transplant biopsy (P < 0.05) in the dnTMA group, and antibody-mediated rejection was more prevalent in anytime-biopsy (P = 0.027). After adjusting for potential confounders, cTMA was associated with a 6-fold increase in the hazard of transplant failure during the first-year post-transplant (adjusted hazard ratio (aHR): 6.37 [95%CI: 2.17 to18.68; P = 0.001]; the aHR decreased by 0.87 (95% CI: 0.76 to 0.99: P = 0.033) per year elapsed since transplantation. Long-term allograft survival was similar in both groups. Conclusion Post kidney transplant TMA is an important cause of poor allograft survival. More studies are needed to enhance our understanding and management of this disorder. Kidney Transplant Thrombotic Microangiopathy complement-mediated TMA de novo TMA Figures Figure 1 Figure 2 Figure 3 Background Kidney transplantation is the treatment of choice for patients with end-stage kidney disease (ESKD) secondary to thrombotic microangiopathy (TMA) [ 1 ]. TMA is a clinical syndrome characterized by microangiopathic hemolytic anemia, thrombocytopenia, organ ischemia, and dysfunction due to microvascular thrombosis [ 2 ]. Post-transplant TMA is a well-recognized complication that affects 0.8–15% of renal transplant recipients [ 3 , 4 , 5 ], and is associated with poor graft and patient outcomes [ 6 ]. TMA is caused by various factors, including infection, drug toxicity, and immunological factors [ 7 ]. Post-transplant TMA can occur at any time after kidney transplantation, but most commonly manifests in the first 6 months [ 8 ], and can be either de novo (dnTMA) with no evidence of the disease before transplant or recurrence of the native kidney TMA (cTMA) [ 9 ]. dnTMA accounts for most post-transplant cases [ 10 , 11 ], with incidence ranges from 1%−15% in different reports [ 12 ]. The pathogenesis is multifactorial, and the most common causes include medications, such as calcineurin inhibitor (CNI) toxicity, ischemia-reperfusion injury, antibody-mediated rejection (ABMR), and infections, such as cytomegalovirus [ 13 , 14 , 15 , 16 ]. The mechanism of CNI-related dnTMA includes arteriolar vasoconstriction due to the enhanced production of vasoconstrictive factors, particularly endothelin-1 and angiotensin II [ 17 , 18 ]. Genetic abnormalities in complement regulation were the precipitating factors in some dnTMA cases [ 19 ]. Atypical hemolytic uremic syndrome (aHUS) is a rare cause of ESKD that manifests as TMA in the native kidneys and is caused by uninhibited activation of the complement alternative pathway [ 20 ] [ 21 ]. Genetic mutations in the regulatory complement system were identified in approximately 50–60% of the patients [ 22 ]. Recurrence rate of aHUS post kidney transplant has been reported in 50–60% of cases [ 23 , 24 , 25 ]. The risk of recurrence depends on the individual genetic mutation [ 26 , 27 , 28 , 29 ]. The kidney transplant biopsy findings in acute TMA are similar to those of the native kidneys, including mucoid intimal edema, arteriolar or glomerular capillary loop fibrin thrombi, endothelial swelling with occlusion of capillary loops, and mesangiolysis [ 30 ]. Eculizumab use for post-transplant aHUS recurrence was first reported in 2009 [ 31 ], and it is effective in the treatment and prevention of recurrent cTMA [ 32 , 33 , 34 , 35 ]. In this study, we present our center’s comprehensive long-term outcome of adult kidney transplant recipients with cTMA and those who developed dnTMA post-transplant. Methods Study population and data collection We conducted a retrospective study including all adult patients ≥ 18-year-old kidney transplant recipients with cTMA and those who developed dnTMA post-transplant between January 2000 and December 2020 in our center. The study was approved by the Johns Hopkins Hospital’s Institutional Review Board. The data were collected from the electronic medical records. TMA before transplant, or cTMA, was defined as the disorder in the native kidneys that led to ESKD. While dnTMA was defined as any TMA disorder that occurred post kidney transplant in patients for whom the native kidney disease was not caused by cTMA. We sought to compare between TMA before and after a transplant to provide insights into the pathogenesis, risk factors, and outcomes associated with TMA in the context of transplantation. We reviewed all available clinical data, including transplant-related variables, recipient and donor information, genetic testing, histological data, and treatment modalities including the use of eculizumab. We compared the baseline characteristics, clinical and histological characteristics at the time of post-transplant TMA diagnosis, and short and long-term transplant outcomes between the two groups. All kidney biopsies were reviewed by our internal renal pathologists, employing the contemporary Banff Classification during the initial biopsy assessment. Statistical analysis We compared between the cTMA and dnTMA groups. The demographic and clinical characteristics were described using descriptive statistics. We used the Mann-Whitney test for continuous variables and Fisher's exact test for categorical variables. Patients were followed from the time of transplantation until graft failure or death, whichever came first. We estimated the crude survival probability using the Kaplan-Meier estimator. We estimated the adjusted hazard ratio (aHR) associated with cTMA using multiple Cox regression models. We fitted non-linear continuous variables with fractional polynomials and tested proportional hazard based on Schoenfeld residuals. We included biopsy diagnoses as time-varying cumulative sum (i.e. cumulative sum of each diagnosis that is updated every time the patient undergoes a new biopsy). Because the non-proportional hazard assumption did not hold, we allowed the HR associated with cTMA to vary over follow-up by including an interaction term with time. We considered two-sided P values of less than 0.05 as statistically significant. Results Patients’ characteristics We identified 134 kidney transplant recipients in our center who met the inclusion criteria. All patients had the histological diagnosis of TMA before or after kidney transplant. Out of the 134 patients, 22 (16.4%) had cTMA and 112 (83.6%) developed dnTMA post-transplant. The demographic characteristics of all patients are shown in Table 1. The causes of ESKD in the dnTMA patients were diabetic nephropathy in 24 (21.4%), glomerular diseases in 33 (29.4%), lupus nephritis in 8 (7.1%), polycystic kidney disease and other congenital kidney diseases in 22 (19.6%), hypertension in 11 (9.8%), and other causes or unknown etiology in 14 (12.5%) patients. Compared with dnTMA, patients with cTMA were younger at TMA diagnosis, mean (SD) of 28.9 ± 16.3. vs 46.5 ± 16.0 years, p<0.001, and at transplantation, mean (SD) of 38.5 ± 10.6 vs 46.1 ± 14.8, p=0.022, respectively. There were no statistical differences in race or gender between the two groups. The majority of the dnTMA group received deceased donor kidney transplantation (DDKT), 69 (61.6%), compared to 9 (40.9%) in the cTMA group; however, the difference was not statistically significant. Thirteen patients (59.1%) had previous kidney transplants in the cTMA and 63 (56.2%) in the dnTMA. Donors were significantly younger in the cTMA group with a mean (SD) of 37.0 (13.7) years, compared to 43.5 (14.9) years in the dnTMA group, p=0.038. There was no statistical difference in the number of patients who were highly sensitized in the two groups, however, preformed donor specific antibody (DSA) was more prevalent in the dnTMA group compared to the cTMA group, 50 (66.7%) vs 8 (40.0%), p=0.04. Cold ischemia time was significantly shorter in the cTMA group with a mean (SD) of 10.3 ± 10.8 hours compared with 19.7 ± 17.2 in the dnTMA group, p= 0.023; this translated into a trend toward a higher rate of delayed graft function (DGF) in the dnTMA group 45 (40.9%) vs 4 (18.2%) in the cTMA group, p=0.054. Since 2000, our center has been using mostly the same immunosuppression protocol including induction therapy with a T-cell depleting agent (mostly thymoglobulin), and maintenance therapy with calcineurin inhibitor (tacrolimus and less likely cyclosporine), steroids, and anti-metabolites mycophenolate mofetil. Most patients in our cohort received induction therapy with thymoglobulin and maintenance immunosuppression with tacrolimus, mycophenolate mofetil, and steroids. There were no statistical differences in induction and maintenance therapies between the two groups. Treatment of post-transplant TMA, before the utilization of eculizumab for this disorder, was consistent of plasmapheresis and in some cases high doses of steroids. In our cohort, treatment with plasmapheresis was implemented in 19 patients (86.4%) of the cTMA group compared to 41 patients (36.9%) of the dnTMA group, p<0.001. Eculizumab was first used off-label in our center in 2010, 39 since then it has become the treatment of choice for prevention and treatment of recurrent cTMA post-transplant. In our cohort, Eculizumab was used in 13 patients (59.1%) for recurrent or prevention of cTMA post-transplant, compared to 6 patients (5.4%) in the treatment of dnTMA group, p<0.001. Diagnostic findings of post-transplant TMA The median time (interquartile range (IQR)) to biopsy-proven TMA post-transplant was 16.4 (3.6 -79.7) months. There were 543 biopsies in the cohort, median (IQR) number per patient: of 4 (2 -5) biopsies. Twelve patients (60 %) with cTMA experienced recurrence after kidney transplantation, confirmed by kidney transplant biopsy. Pathogenic mutations were identified in 10 patients (45.5 %) while 12 (54.5 %) patients had either no identified mutation or testing was not done. Laboratories results including hemoglobin, platelets, and kidney function were not statistically significant on the day of discharge post hospitalization for kidney transplant between the two groups. At the time of TMA diagnosis post-transplant, which was confirmed by kidney transplant biopsy, the laboratory parameters did not differ significantly except for serum creatinine, table 2. Median serum creatinine (IQR) was much higher at the time of dnTMA diagnosis compared with cTMA recurrence post-transplant, 3.6 (0.4-24.0) vs 2.0 (0.7-15.6) mg/dL, p=0.043. Patients with dnTMA had a much higher rate of rejection confirmed by kidney transplant biopsy at the time of TMA diagnosis compared with cTMA, 49 (43.8%) vs 2 (10 %), p=0.005. Similarly, CNI toxicity in the diagnostic biopsy was more frequent in the dnTMA group compared to the cTMA group, 80 (71.4%) vs 5 (22.7%), p<0.001. In anytime kidney transplant biopsy, ABMR was more prevalent in the dnTMA group compared to the cTMA group, 29 (25.9%) vs 1 (4.5%) patients, p=0.027. Otherwise, there was no difference in the other Banff scores of the first kidney biopsy, including g, I, ti, t, v, ptc, C4d, cg, ci, ct, cv, cg, mm, ah, IFTA, Table 2. Allograft and patient outcome The survival analysis was performed in the 129 patients with available follow-up (109 with dnTMA, and 20 with cTMA), Figure 1. The mean follow-up was 4.5 years during which 73 (54%) had allograft failure and 22 (16%) died. Black race was associated with a higher risk of allograft failure. Pathological changes of any type of acute rejection, including borderline rejection, and tacrolimus toxicity in the kidney transplant biopsy at the time of TMA diagnosis post kidney transplant were associated with a significantly higher risk of allograft failure, table 3. After adjusting for age, gender, ethnicity, donor type, lymphodepleting agent induction and DGF patients with cTMA had a significant increase in the hazard risk of allograft failure in the first-year post-transplant, aHR: 6.37 (95% CI: 2.17 to18.68, P=0.001). However, the aHR decreased by 0.87 (95% CI: 0.76 to 0.99, P=0.033) per year elapsed since transplantation, Table 3. By the end of the study’s time, there were no statistical differences in the allograft survival between the two groups, Figure 2. In the most recent follow-up, allograft function as measured by mean (SD) eGFR (23.5 ± 22.1 vs 42.2 ± 27.3 ml/min/m 2 , p=0.003), was significantly worse in the dnTMA group comparing with cTMA group. There was a trend toward worse patients’ survival in the dnTMA group, which did not reach a statistical difference, p=0.087, Figure 3. Eculizumab effect on the allograft outcome We performed a sub-group analysis of patients who received Eculizumab; mostly cTMA. There was no difference in allograft survival between those who received eculizumab and those who did not. However, the treatment of eculizumab has been utilized only since 2010, and in many cases, it was used late in the course of post-transplant TMA. Discussion In this single-center study, we identified a total of 134 patients with TMA, 22 patients with cTMA, and 112 developed dnTMA post-transplant. Patients with cTMA were younger both at transplantation and at the time of TMA diagnosis. We found that biopsy-proven acute TCMR and ABMR rejections and biopsy-proven CNI toxicity were much more common in the dnTMA group. Rejection and CNI toxicity were most likely the causes of dnTMA post kidney transplantation. Additionally, we found that cTMA was associated with a 6-fold increase in the hazard risk of allograft failure in the first year after transplant but the aHR decreased as time elapsed after transplant. This finding may be explained by the high recurrence rate of cTMA early post-transplant triggered by several factors that lead to the activation of the alternative complement pathway, e.g., ischemia–reperfusion injury, infections, and the use of immunosuppressive drugs, especially before the utilization of anti-C5 antibodies. However, the long-term allograft survival of the two groups was similar. Before the utilization of eculizumab in the treatment of post-transplant TMA in our center, plasma exchange was the main treatment of choice for recurrent cTMA and in some cases of dnTMA. Although eculizumab improved the allograft survival in published case reports, our study did not capture this benefit. This can be explained by the underpowered sample size and the fact that the utilization of eculizumab was delayed in some cases. cTMA is a systemic disorder caused by uncontrolled activation of the alternative complement pathway and can lead to ESKD. A variety of genetic defects in complement-related factors have been identified and recurrence rate post-transplant largely depends on the pathogenetic mutations involved [ 33 ]. Before the utilization of anti-C5 antibodies in cTMA, kidney transplant outcome of recurrent cTMA was dire [ 36 ]. Although acute rejection episodes commonly occur in the first year post-transplant, mostly in the first 6 months, successful rejection treatment and allograft functional recovery may not have a negative long-term impact on the allograft survival [ 37 ]. However, the detection of dnTMA in the early post-transplant period holds significant implications for the long-term allograft outcome. Our study demonstrates that dnTMA may serve as a pivotal early pathological marker associated with poor long-term allograft survival. The incidence of recurrent cTMA or dnTMA is not very well defined, likely because most of the transplant centers do not do protocol biopsies. In a small retrospective study of 57 renal transplant recipients with early allograft dysfunction, post-transplant biopsy-proven TMA was detected in 10.5% of cases [ 38 ]. The significant advances in our understanding of the cTMA disorder and the approval of anti-C5 antibodies have resulted in a major improvement in the outcome of kidney transplants in patients with cTMA [ 39 ] [ 40 ].Eculizumab has been used for the treatment of recurrent cTMA and as a preventive measurement that decreases or prevents recurrent cTMA post-transplant [ 41 ]. On the other hand, limited options are available for dnTMA that mostly depend on the cause. In cases of CNI toxicity, many providers switch to mTOR inhibitors or belatacept with some success [ 42 ] [ 43 ]. Furthermore, there is limited data on the long-term outcome of renal transplantation in patients with post-transplant TMA. In a study from Brazil, 17 (1.1%) out of 1549 kidney transplant recipients developed dnTMA that occurred at a median of 25 (1-1755) days after transplantation. CNI withdrawal or reduction was the first step in the management of 10/15 (66%) patients, and 6 (35%) received fresh frozen plasma (FFP) and/or plasmapheresis. Eight (47%) patients needed dialysis after TMA diagnosis and 75% remained on dialysis. At 4 years of follow-up, death-censored graft survival was worse for the dnTMA group (43.0% versus 85.6%, log-rank = 0.001; hazard ratio = 3.74), with no difference in patient survival (53.1% versus 82.2%, log-rank = 0.24) [ 9 ]. In most published data the two types of post-transplant TMA were grouped. In a retrospective study of 89 patients with post-transplant TMA, underlying precipitating factors were infection (54%), acute rejection (34%), CNI toxicity (13%), and pregnancy (3%). The 1-year patient survival was 97% and graft survival was 66%. Allograft survival was inferior when ABMR occurred (with 41%; without 70%, p = 0.01) [ 44 ]. Despite the significant novel findings of our study, it has several limitations, primarily stemming from its retrospective nature. Additionally, the absence of protocol biopsy might have led to the oversight of numerous other patients with post-transplant TMA. Furthermore, our understanding of cTMA, primarily attributed to its association with genetic disorders within the complement alternative pathway, remains relatively new. Consequently, treatment modalities for both cTMA and dnTMA were notably limited in the first ten years of our study. However, despite these limitations, our study represents one of the largest cohorts of kidney transplant recipients with TMA. Moreover, the outcomes derived from our study carry substantial implications for advancing comprehension of this disorder and elucidating its ramifications on allograft outcomes. Conclusion Post-transplant recurrent cTMA is an important cause of poor allograft survival in the first-year post kidney transplant. On the other hand, dnTMA is associated strongly with poor long-term allograft survival. More studies are needed to enhance our understanding and management of this complex disorder. Abbreviations cTMA: complement-mediated thrombotic microangiopathy. dnTMA: de novo thrombotic microangiopathy. aHR: adjusted hazard ratio. ESKD: end-stage kidney disease. CNI: calcineurin inhibitor toxicity. ABMR: antibody-mediated rejection. TCMR: T cell-mediated rejection. aHUS: Atypical hemolytic uremic syndrome. MCP: membrane cofactor protein. DDKT: deceased donor kidney transplant. LURT: living unrelated kidney transplant. LRT: living-related kidney transplant. GN: Glomerulonephritis. DSA: donor-specific antibodies. IFTA: Interstitial Fibrosis Tubular Atrophy. eGFR: Estimated glomerular filtration rate. rATG: rabbit anti-thymocyte globulins. MMF: mycophenolate mofetil. mTOR, mammalian target of rapamycin. Declarations Ethics approval and consent to participate The study was approved by the Johns Hopkins Hospital’s Institutional Review Board. This is a retrospective study, data were collected from the electronic medical records, consents were waived. Consent for publication The authors give their consent for publication of this manuscript in BMC Nephrology. Availability of data and materials The datasets generated and analyzed during the current study are not publicly available, as it is a center’s owned data but limited unidentified data are available from the corresponding author on reasonable request. Competing interests The authors declare no competing interests. Funding None. Authors' contributions KH participated in collecting data, analysis, and writing the manuscript SL participated in collecting data and writing the manuscript AD participated in collecting data and writing the manuscript ZO participated in collecting data and writing the manuscript SB participated in collecting data and writing the manuscript UM participated in study design, statistical analysis, and writing the manuscript NA participated in study design, collecting data, analysis, and writing the manuscript Acknowledgements None. References Hariharan S, Israni AK, Danovitch G. Long-Term Survival after Kidney Transplantation. N Engl J Med. 2021;385(8):729–43. Moake JL. Thrombotic microangiopathies. N Engl J Med. 2002;347(8):589–600. Ávila A, Gavela E, Sancho A. Thrombotic Microangiopathy After Kidney Transplantation: An Underdiagnosed and Potentially Reversible Entity. Front Med (Lausanne). 2021;8:642864. 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Outcomes of patients with atypical haemolytic uraemic syndrome with native and transplanted kidneys treated with eculizumab: a pooled post hoc analysis. Transpl Int. 2017;30(12):1275–83. de Andrade LGM, Contti MM, Nga HS, Bravin AM, Takase HM, Viero RM, et al. Long-term outcomes of the Atypical Hemolytic Uremic Syndrome after kidney transplantation treated with eculizumab as first choice. PLoS ONE. 2017;12(11):e0188155. Levi C, Frémeaux-Bacchi V, Zuber J, Rabant M, Devriese M, Snanoudj R, et al. Midterm Outcomes of 12 Renal Transplant Recipients Treated With Eculizumab to Prevent Atypical Hemolytic Syndrome Recurrence. Transplantation. 2017;101(12):2924–30. Koppula S, Yost SE, Sussman A, Bracamonte ER, Kaplan B. Successful conversion to belatacept after thrombotic microangiopathy in kidney transplant patients. Clin Transpl. 2013;27(4):591–7. Ashman N, Chapagain A, Dobbie H, Raftery MJ, Sheaff MT, Yaqoob MM. Belatacept as maintenance immunosuppression for postrenal transplant de novo drug-induced thrombotic microangiopathy. Am J Transpl. 2009;9(2):424–7. Teixeira CM, Tedesco Silva Junior H, de Moura LAR, Proença HM, de Marco S, Gerbase R, de Lima M, et al. Clinical and pathological features of thrombotic microangiopathy influencing long-term kidney transplant outcomes. PLoS ONE. 2020;15(1):e0227445. Tables Table 1. Baseline Patients Characteristic dnTMA cTMA p-value N 112 (83.6%) 22 (16.4%) † Mean (SD) Age at TMA diagnosis, years 46.5 ± 16.0 28.9 ± 16.3 <0.001 Mean (SD) Age at transplant, years 46.1 ± 14.8 38.5 ± 10.6 0.022 Ethnicity White 66 (58.9%) 17 (77.3%) 0.287 Black 42 (37.5%) 5 (22.7%) Other 4 (3.6%) 0 (0.0%) Gender, Female 56 (50.0%) 15 (68.2%) 0.161 Donor type Deceased donor 69 (61.6%) 9 (40.9%) 0.185 Living unrelated 20 (17.9%) 6 (27.3%) Living related 23 (20.5%) 7 (31.8%) Donor's age, years 43.5 ± 14.9 37.0 ± 13.7 0.038 Donor's terminal Creatinine, mg/dL 1.1 (0.4-4.0) 1.4 (0.5-6.5) 0.540 Highly sensitized 47 (67.1%) 15 (75.0%) 0.592 ‡ HLAi or ABOi transplant (required desensitization) 46 (51.1%) 6 (30.0%) 0.136 § Pre-transplant DSA 50 (66.7%) 8 (40.0%) 0.04 Re-transplantation 63 (56.2%) 13 (59.1%) 1 Warm ischemic time, minutes 47.2 ± 24.8 42.5 ± 11.8 0.641 Cold ischemic time, hours 19.7 ± 17.2 10.3 ± 10.8 0.023 Delayed graft function 45 (40.9%) 4 (18.2%) 0.054 Reason for previous graft loss TMA 4 (5.3%) 15 (93.8%) <0.001 ¶ Acute ABMR 9 (11.8%) 0 (0.0%) Chronic ABMR 30 (39.5%) 0 (0.0%) BK nephropathy 3 (3.9%) 0 (0.0%) † SD, standard deviation; TMA, thrombotic microangiopathy; ‡ HLAi, Human leukocyte antigens incompatible; ABOi, ABO-incompatible; § DSA, donor specific antibody; ¶ ABMR, antibody mediated rejection. Table 2. Clinical and pathological findings at the time of post-transplant TMA diagnosis dnTMA (N=112) cTMA (N=22) p-value Number of graft biopsies 4.0 (1.0-12.0) 3.5 (0.0-10.0) 0.134 Time from first to last biopsy, months 18.8 (0.0-296.2) 45.2 (0.6-1290.0) 0.197 † Median (IQR) of SCr at time of diagnostic biopsy, mg/dL 3.6 (0.4-24.0) 2.0 (0.7-15.6) 0.043 ‡ Mean (SD) of Hg at time of diagnostic biopsy, g/dL 9.4 ± 2.0 9.6 ± 1.5 0.449 Median (IQR) of platelets count at time of diagnostic biopsy, x1000/dL 167 (21.0-459) 176 (47.0-396) 0.855 Median (IQR) of LDH at time of diagnostic biopsy, UI/L [Ref. 100-200] 312 (91-1547) 286 (200-1183) 0.753 Median (IQR) of last SCr, mg/dL 3.1 (0.3-17.8) 2.3 (0.4-5.0) 0.025 § Mean (SD) of last eGFR, mL/min/1.73 m 2 23.5 ± 22.1 42.2 ± 27.3 0.003 Mean (SD) of last Hemoglobin, g/dL 10.6 ± 2.2 9.5 ± 2.7 0.212 Rejection in the diagnostic biopsy 49 (43.8%) 2 (10.0%) 0.005 ¶ TCMR in diagnostic biopsy 26 (23.2%) 0 (0.0%) 0.007 # CNI toxicity in diagnostic biopsy 34 (30.4%) 1 (5.0%) 0.025 Rejection, at least in one biopsy 90 (80.4%) 11 (50.0%) 0.005 †† ABMR, at least in one biopsy 29 (25.9%) 1 (4.5%) 0.027 ‡‡ CTG, at least in one biopsy 11 (9.8%) 3 (13.6%) 0.701 CNI toxicity, at least in one biopsy 80 (71.4%) 5 (22.7%) <0.001 † SCr, serum creatinine; ‡ Hg, Hemoglobin; § eGFR, estimated glomerular filtration rate; ¶ TCMR, T cell mediated rejection; antibody-mediated rejection; # CNI, calcineurin inhibitor; †† ABMR, antibody mediated rejection; ‡‡ CTG, chronic transplant glomerulopathy. Table 3. Hazard ratio of transplant failure from Cox proportional hazards regression model HR 95% CI P value Male gender 1.70 (1.06 to 2.75) 0.029 Ethnicity (vs White) Black 1.76 (1.06 to 2.93) 0.029 Other 0.37 (0.09 to 1.57) 0.176 Donor type (vs Deceased donor) Living unrelated 1.22 (0.65 to 2.29) 0.526 Living related 0.47 (0.22 to 1.00) 0.051 Delayed graft function 1.38 (0.78 to 2.42) 0.267 Recurrent cTMA, first year 6.37 (2.17 to18.68) 0.001 † ABMR 1.23 (0.90 to 1.67) 0.188 ‡ TCMR grade 1 1.37 (1.12 to 1.67) 0.002 TCMR grade 2 1.55 (1.22 to 1.98) <0.001 Borderline rejection 1.47 (1.08 to 2.00) 0.013 § CNI toxicity 1.65 (1.28 to 2.12) <0.001 Yearly change of the HR associated with cTMA 0.87 (0.76 to 0.99) 0.033 † ABMR, antibody mediated rejection; ‡ TCMR, T cell mediated rejection; § CNI, calcineurin inhibitor. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2024 Read the published version in BMC Nephrology → Version 1 posted Editorial decision: Revision requested 25 Jul, 2024 Editor invited by journal 16 Jul, 2024 Editor assigned by journal 12 Jul, 2024 Submission checks completed at journal 12 Jul, 2024 First submitted to journal 04 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4688690","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":331524208,"identity":"41442e09-e2bf-47a1-9aa4-7c570355798d","order_by":0,"name":"Kanza Haq","email":"","orcid":"","institution":"The Johns Hopkins University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kanza","middleName":"","lastName":"Haq","suffix":""},{"id":331524209,"identity":"1002b0c0-272c-4b2c-9699-44493f62a2a7","order_by":1,"name":"Shanshan Lin","email":"","orcid":"","institution":"The Johns Hopkins University School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"Shanshan","middleName":"","lastName":"Lin","suffix":""},{"id":331524210,"identity":"04bc47b8-b318-415b-b015-6925f8081ddd","order_by":2,"name":"Alana Dasgupta","email":"","orcid":"","institution":"The Ohio State University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Alana","middleName":"","lastName":"Dasgupta","suffix":""},{"id":331524211,"identity":"d1f54951-fb78-4873-81b2-365b258ff0ce","order_by":3,"name":"Zainab Obaidi","email":"","orcid":"","institution":"University of Chicago","correspondingAuthor":false,"prefix":"","firstName":"Zainab","middleName":"","lastName":"Obaidi","suffix":""},{"id":331524212,"identity":"026f8829-b8b6-492d-8bfa-7b2438d75f72","order_by":4,"name":"Serena Bagnasco","email":"","orcid":"","institution":"The Johns Hopkins University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Serena","middleName":"","lastName":"Bagnasco","suffix":""},{"id":331524213,"identity":"3b6da8d7-62fc-4db7-b755-6fe84f19d00f","order_by":5,"name":"Umberto Maggiore","email":"","orcid":"","institution":"University of Parma","correspondingAuthor":false,"prefix":"","firstName":"Umberto","middleName":"","lastName":"Maggiore","suffix":""},{"id":331524214,"identity":"3e76f1ea-9b5c-4468-9de5-7dbda9e54396","order_by":6,"name":"Nada Alachkar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYFAC5gYGxoYEHn6GMwwMCQxANmEtjGAtMpINpGqxMTjAA+MSAObsBxs//NyRxmN88OzRDQ8YbGQ3HCCgxbInsVmy90wOj9mBc2k3EhjSjAlqMTiQ2CDN2FYB1HLGDKjlcCJhLecfNv8GaTFuAGv5T4SWG4ltQFtyeAwYwFoOEKPlYZtlb1sajwTYYQbJxjMJOyz58I2fbcn2/DPOmN38UWEn20dICwJIgJQaEK0cBPgbSFI+CkbBKBgFIwgAABDFTg86UG3WAAAAAElFTkSuQmCC","orcid":"","institution":"The Johns Hopkins University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Nada","middleName":"","lastName":"Alachkar","suffix":""}],"badges":[],"createdAt":"2024-07-04 22:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4688690/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4688690/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12882-024-03846-x","type":"published","date":"2024-11-28T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":62190889,"identity":"8cfa9e14-0671-4d99-a33c-fb2128968b31","added_by":"auto","created_at":"2024-08-10 12:35:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":105047,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier plot of transplant survival (death or end-stage kidney disease, ESKD) of primary cTMA vs dnTMA. Time at risk starts from transplantation and includes patients with available follow-up. The population is divided into those who had known cTMA before transplantation (red) and those who had dnTMA (blue). There was a sudden drop by 10% in cTMA patients shortly after follow-up, but survival was similar between the groups in the long term; cTMA.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4688690/v1/fa31e9b36cd8566fb82d388c.png"},{"id":62190444,"identity":"ecb49d53-531a-4269-95ce-8c9fc745aca3","added_by":"auto","created_at":"2024-08-10 12:27:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":103791,"visible":true,"origin":"","legend":"\u003cp\u003eTime-varying adjusted hazard ratio (HR) of transplant failure (death or end-stage kidney disease, ESKD) of patients with cTMA compared to dnTMA. The hazard ratio is highest shortly after transplantation, and then decreases with time. The model is adjusted for age, gender, ethnicity, donor type, induction with lymphodepleting agents, DGF, eculizumab use (any time), and biopsy diagnosis (time-varying cumulative sum). The line represents the hazard ratio estimates, the blue shaded area represents the 95 percent confidence interval; cTMA, complement-mediated thrombotic microangiopathy.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4688690/v1/7f7bace33628c4cb318fdaf6.png"},{"id":62190446,"identity":"e9f94511-454f-4f10-8bfa-b79eed5204bc","added_by":"auto","created_at":"2024-08-10 12:27:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":99693,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier patient survival estimates in cTMA and dnTMA. Time at risk started from transplantation and included patients with available follow-up. Patients starting dialysis were censored.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4688690/v1/8775f963878cbd82a0e59400.png"},{"id":70382024,"identity":"caddf9fc-a077-49ef-bfd0-4be0054f99bd","added_by":"auto","created_at":"2024-12-02 16:21:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":742632,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4688690/v1/fe4061fb-262e-451c-a628-5265a47d42b4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Outcome of Thrombotic Microangiopathy in Kidney Transplant Recipients","fulltext":[{"header":"Background","content":"\u003cp\u003eKidney transplantation is the treatment of choice for patients with end-stage kidney disease (ESKD) secondary to thrombotic microangiopathy (TMA) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. TMA is a clinical syndrome characterized by microangiopathic hemolytic anemia, thrombocytopenia, organ ischemia, and dysfunction due to microvascular thrombosis [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Post-transplant TMA is a well-recognized complication that affects 0.8\u0026ndash;15% of renal transplant recipients [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and is associated with poor graft and patient outcomes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. TMA is caused by various factors, including infection, drug toxicity, and immunological factors [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePost-transplant TMA can occur at any time after kidney transplantation, but most commonly manifests in the first 6 months [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and can be either de novo (dnTMA) with no evidence of the disease before transplant or recurrence of the native kidney TMA (cTMA) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. dnTMA accounts for most post-transplant cases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], with incidence ranges from 1%\u0026minus;15% in different reports [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The pathogenesis is multifactorial, and the most common causes include medications, such as calcineurin inhibitor (CNI) toxicity, ischemia-reperfusion injury, antibody-mediated rejection (ABMR), and infections, such as cytomegalovirus [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The mechanism of CNI-related dnTMA includes arteriolar vasoconstriction due to the enhanced production of vasoconstrictive factors, particularly endothelin-1 and angiotensin II [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Genetic abnormalities in complement regulation were the precipitating factors in some dnTMA cases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAtypical hemolytic uremic syndrome (aHUS) is a rare cause of ESKD that manifests as TMA in the native kidneys and is caused by uninhibited activation of the complement alternative pathway [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Genetic mutations in the regulatory complement system were identified in approximately 50\u0026ndash;60% of the patients [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Recurrence rate of aHUS post kidney transplant has been reported in 50\u0026ndash;60% of cases [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The risk of recurrence depends on the individual genetic mutation [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe kidney transplant biopsy findings in acute TMA are similar to those of the native kidneys, including mucoid intimal edema, arteriolar or glomerular capillary loop fibrin thrombi, endothelial swelling with occlusion of capillary loops, and mesangiolysis [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEculizumab use for post-transplant aHUS recurrence was first reported in 2009 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and it is effective in the treatment and prevention of recurrent cTMA [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we present our center\u0026rsquo;s comprehensive long-term outcome of adult kidney transplant recipients with cTMA and those who developed dnTMA post-transplant.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and data collection\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective study including all adult patients\u0026thinsp;\u0026ge;\u0026thinsp;18-year-old kidney transplant recipients with cTMA and those who developed dnTMA post-transplant between January 2000 and December 2020 in our center. The study was approved by the Johns Hopkins Hospital\u0026rsquo;s Institutional Review Board. The data were collected from the electronic medical records.\u003c/p\u003e \u003cp\u003eTMA before transplant, or cTMA, was defined as the disorder in the native kidneys that led to ESKD. While dnTMA was defined as any TMA disorder that occurred post kidney transplant in patients for whom the native kidney disease was not caused by cTMA. We sought to compare between TMA before and after a transplant to provide insights into the pathogenesis, risk factors, and outcomes associated with TMA in the context of transplantation.\u003c/p\u003e \u003cp\u003e We reviewed all available clinical data, including transplant-related variables, recipient and donor information, genetic testing, histological data, and treatment modalities including the use of eculizumab. We compared the baseline characteristics, clinical and histological characteristics at the time of post-transplant TMA diagnosis, and short and long-term transplant outcomes between the two groups.\u003c/p\u003e \u003cp\u003eAll kidney biopsies were reviewed by our internal renal pathologists, employing the contemporary Banff Classification during the initial biopsy assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eWe compared between the cTMA and dnTMA groups. The demographic and clinical characteristics were described using descriptive statistics. We used the Mann-Whitney test for continuous variables and Fisher's exact test for categorical variables. Patients were followed from the time of transplantation until graft failure or death, whichever came first. We estimated the crude survival probability using the Kaplan-Meier estimator. We estimated the adjusted hazard ratio (aHR) associated with cTMA using multiple Cox regression models. We fitted non-linear continuous variables with fractional polynomials and tested proportional hazard based on Schoenfeld residuals. We included biopsy diagnoses as time-varying cumulative sum (i.e. cumulative sum of each diagnosis that is updated every time the patient undergoes a new biopsy). Because the non-proportional hazard assumption did not hold, we allowed the HR associated with cTMA to vary over follow-up by including an interaction term with time. We considered two-sided P values of less than 0.05 as statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatients\u0026rsquo; characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe identified 134 kidney transplant recipients in our center who met the inclusion criteria. All patients had the histological diagnosis of TMA before or after kidney transplant.\u0026nbsp;Out of the 134 patients, 22 (16.4%) had cTMA and 112 (83.6%) developed dnTMA post-transplant.\u0026nbsp;The demographic characteristics of all patients are shown in Table 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe causes of ESKD in the dnTMA patients were diabetic nephropathy in 24 (21.4%), glomerular diseases in 33 (29.4%), lupus nephritis in 8 (7.1%), polycystic kidney disease and other congenital kidney diseases in 22 (19.6%), hypertension in 11 (9.8%), and other causes or unknown etiology in 14 (12.5%) patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared with dnTMA, patients with cTMA were younger at TMA diagnosis, mean (SD) of 28.9 \u0026plusmn; 16.3. vs 46.5 \u0026plusmn; 16.0 years, p\u0026lt;0.001, and at transplantation, mean (SD) of 38.5 \u0026plusmn; 10.6 vs 46.1 \u0026plusmn; 14.8, p=0.022, respectively. There were no statistical differences in race or gender between the two groups.\u0026nbsp;The majority of the dnTMA group received deceased donor kidney transplantation (DDKT),\u0026nbsp;69 (61.6%), compared to\u0026nbsp;9 (40.9%) in the cTMA group; however, the difference was not statistically significant. Thirteen patients (59.1%) had previous kidney transplants in the cTMA and\u0026nbsp;63 (56.2%) in the dnTMA.\u0026nbsp;Donors were significantly younger in the cTMA group with a mean (SD) of 37.0 (13.7) years, compared to 43.5 (14.9) years in the dnTMA group, p=0.038.\u003c/p\u003e\n\u003cp\u003eThere was no statistical difference in the number of patients who were highly sensitized in the two groups, however, preformed donor specific antibody (DSA) was more prevalent in the dnTMA group compared to the cTMA group, 50 (66.7%) vs 8 (40.0%), p=0.04.\u003c/p\u003e\n\u003cp\u003eCold ischemia time was significantly shorter in the cTMA group with a mean (SD) of 10.3 \u0026plusmn; 10.8 hours compared with 19.7 \u0026plusmn; 17.2 in the dnTMA group, p= 0.023; this translated into a trend toward a higher rate of delayed graft function (DGF) in the dnTMA group 45 (40.9%) vs 4 (18.2%) in the cTMA group, p=0.054.\u003c/p\u003e\n\u003cp\u003eSince 2000, our center has been using mostly the same immunosuppression protocol including induction therapy with a T-cell depleting agent (mostly thymoglobulin), and maintenance therapy with calcineurin inhibitor (tacrolimus and less likely cyclosporine), steroids, and anti-metabolites mycophenolate mofetil.\u0026nbsp;Most patients in our cohort received induction therapy with thymoglobulin and maintenance immunosuppression with tacrolimus, mycophenolate mofetil, and steroids. There were no statistical differences in induction and maintenance therapies between the two groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTreatment of post-transplant TMA,\u0026nbsp;before the utilization of eculizumab for this disorder, was consistent of plasmapheresis and in some cases high doses of steroids. In our cohort, treatment with plasmapheresis was implemented in 19 patients (86.4%) of the cTMA group compared to 41 patients (36.9%) of the dnTMA group, p\u0026lt;0.001.\u003c/p\u003e\n\u003cp\u003eEculizumab was first used off-label in our center in 2010,\u003csup\u003e39\u003c/sup\u003e since then it has become the treatment of choice for prevention and treatment of recurrent cTMA post-transplant. In our cohort, Eculizumab was used in 13 patients (59.1%) for recurrent or prevention of cTMA post-transplant, compared to 6 patients (5.4%) in the treatment of dnTMA group, p\u0026lt;0.001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic findings of post-transplant TMA\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe median time (interquartile range (IQR)) to biopsy-proven TMA post-transplant was 16.4 (3.6 -79.7) months. There were 543 biopsies in the cohort, median (IQR) number per patient: of 4 (2 -5) biopsies.\u003c/p\u003e\n\u003cp\u003eTwelve patients (60 %) with cTMA experienced recurrence after kidney transplantation, confirmed by kidney transplant biopsy. \u0026nbsp;Pathogenic mutations were identified in 10 patients (45.5 %) while 12 (54.5 %) patients had either no identified mutation or testing was not done.\u003c/p\u003e\n\u003cp\u003eLaboratories results including hemoglobin, platelets, and kidney function were not statistically significant on the day of discharge post hospitalization for kidney transplant between the two groups. At the time of TMA diagnosis post-transplant, which was confirmed by kidney transplant biopsy, the laboratory parameters did not differ significantly except for serum creatinine, table 2. Median serum creatinine (IQR) was much higher at the time of dnTMA diagnosis compared with cTMA recurrence post-transplant, 3.6 (0.4-24.0) vs\u0026nbsp;2.0 (0.7-15.6) mg/dL, p=0.043.\u003c/p\u003e\n\u003cp\u003ePatients with dnTMA had a much higher rate of rejection confirmed by kidney transplant biopsy at the time of TMA diagnosis compared with cTMA, 49 (43.8%) vs 2 (10 %), p=0.005. Similarly, CNI toxicity in the diagnostic biopsy was more frequent in the dnTMA group compared to the cTMA group, 80 (71.4%) vs 5 (22.7%), p\u0026lt;0.001. In anytime kidney transplant biopsy, ABMR was more prevalent in the dnTMA group compared to the cTMA group, 29 (25.9%) vs 1 (4.5%) patients, p=0.027. Otherwise, there was no difference in the other Banff scores of the first kidney biopsy, including g, I, ti, t, v, ptc, C4d, cg, ci, ct, cv, cg, mm, ah, IFTA, Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAllograft and patient outcome\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe survival analysis was performed in the 129 patients with available follow-up (109 with dnTMA, and 20 with cTMA), Figure 1. The mean follow-up was 4.5 years during which 73 (54%) had allograft failure and 22 (16%) died. Black race was associated with a higher risk of allograft failure. Pathological changes of any type of acute rejection, including borderline rejection, and tacrolimus toxicity in the kidney transplant biopsy at the time of TMA diagnosis post kidney transplant were associated with a significantly higher risk of allograft failure, table 3.\u003c/p\u003e\n\u003cp\u003eAfter adjusting for age, gender, ethnicity, donor type, lymphodepleting agent induction and DGF patients with cTMA had a significant increase in the hazard risk of allograft failure in the first-year post-transplant, aHR: 6.37 (95% CI: 2.17 to18.68, P=0.001). However, the aHR decreased by 0.87 (95% CI: 0.76 to 0.99, P=0.033) per year elapsed since transplantation, Table 3. \u0026nbsp;By the end of the study\u0026rsquo;s time, there were no statistical differences in the allograft survival between the two groups, Figure 2.\u003c/p\u003e\n\u003cp\u003eIn the most recent follow-up, allograft function as measured by mean (SD) eGFR (23.5 \u0026plusmn; 22.1 vs 42.2 \u0026plusmn; 27.3 ml/min/m\u003csup\u003e2\u003c/sup\u003e, p=0.003), was significantly worse in the dnTMA group comparing with cTMA group. There was a trend toward worse patients\u0026rsquo; survival in the dnTMA group, which did not reach a statistical difference, p=0.087, Figure 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEculizumab effect on the allograft outcome\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe performed a sub-group analysis of patients who received Eculizumab; mostly cTMA. There was no difference in allograft survival between those who received eculizumab and those who did not. However, the treatment of eculizumab has been utilized only since 2010, and in many cases, it was used late in the course of post-transplant TMA.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-center study, we identified a total of 134 patients with TMA, 22 patients with cTMA, and 112 developed dnTMA post-transplant. Patients with cTMA were younger both at transplantation and at the time of TMA diagnosis. We found that biopsy-proven acute TCMR and ABMR rejections and biopsy-proven CNI toxicity were much more common in the dnTMA group. Rejection and CNI toxicity were most likely the causes of dnTMA post kidney transplantation.\u003c/p\u003e \u003cp\u003eAdditionally, we found that cTMA was associated with a 6-fold increase in the hazard risk of allograft failure in the first year after transplant but the aHR decreased as time elapsed after transplant. This finding may be explained by the high recurrence rate of cTMA early post-transplant triggered by several factors that lead to the activation of the alternative complement pathway, e.g., ischemia\u0026ndash;reperfusion injury, infections, and the use of immunosuppressive drugs, especially before the utilization of anti-C5 antibodies. However, the long-term allograft survival of the two groups was similar.\u003c/p\u003e \u003cp\u003eBefore the utilization of eculizumab in the treatment of post-transplant TMA in our center, plasma exchange was the main treatment of choice for recurrent cTMA and in some cases of dnTMA. Although eculizumab improved the allograft survival in published case reports, our study did not capture this benefit. This can be explained by the underpowered sample size and the fact that the utilization of eculizumab was delayed in some cases.\u003c/p\u003e \u003cp\u003ecTMA is a systemic disorder caused by uncontrolled activation of the alternative complement pathway and can lead to ESKD. A variety of genetic defects in complement-related factors have been identified and recurrence rate post-transplant largely depends on the pathogenetic mutations involved [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Before the utilization of anti-C5 antibodies in cTMA, kidney transplant outcome of recurrent cTMA was dire [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough acute rejection episodes commonly occur in the first year post-transplant, mostly in the first 6 months, successful rejection treatment and allograft functional recovery may not have a negative long-term impact on the allograft survival [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, the detection of dnTMA in the early post-transplant period holds significant implications for the long-term allograft outcome. Our study demonstrates that dnTMA may serve as a pivotal early pathological marker associated with poor long-term allograft survival.\u003c/p\u003e \u003cp\u003eThe incidence of recurrent cTMA or dnTMA is not very well defined, likely because most of the transplant centers do not do protocol biopsies. In a small retrospective study of 57 renal transplant recipients with early allograft dysfunction, post-transplant biopsy-proven TMA was detected in 10.5% of cases [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe significant advances in our understanding of the cTMA disorder and the approval of anti-C5 antibodies have resulted in a major improvement in the outcome of kidney transplants in patients with cTMA [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].Eculizumab has been used for the treatment of recurrent cTMA and as a preventive measurement that decreases or prevents recurrent cTMA post-transplant [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. On the other hand, limited options are available for dnTMA that mostly depend on the cause. In cases of CNI toxicity, many providers switch to mTOR inhibitors or belatacept with some success [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, there is limited data on the long-term outcome of renal transplantation in patients with post-transplant TMA. In a study from Brazil, 17 (1.1%) out of 1549 kidney transplant recipients developed dnTMA that occurred at a median of 25 (1-1755) days after transplantation. CNI withdrawal or reduction was the first step in the management of 10/15 (66%) patients, and 6 (35%) received fresh frozen plasma (FFP) and/or plasmapheresis. Eight (47%) patients needed dialysis after TMA diagnosis and 75% remained on dialysis. At 4 years of follow-up, death-censored graft survival was worse for the dnTMA group (43.0% versus 85.6%, log-rank\u0026thinsp;=\u0026thinsp;0.001; hazard ratio\u0026thinsp;=\u0026thinsp;3.74), with no difference in patient survival (53.1% versus 82.2%, log-rank\u0026thinsp;=\u0026thinsp;0.24) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn most published data the two types of post-transplant TMA were grouped. In a retrospective study of 89 patients with post-transplant TMA, underlying precipitating factors were infection (54%), acute rejection (34%), CNI toxicity (13%), and pregnancy (3%). The 1-year patient survival was 97% and graft survival was 66%. Allograft survival was inferior when ABMR occurred (with 41%; without 70%, p\u0026thinsp;=\u0026thinsp;0.01) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the significant novel findings of our study, it has several limitations, primarily stemming from its retrospective nature. Additionally, the absence of protocol biopsy might have led to the oversight of numerous other patients with post-transplant TMA. Furthermore, our understanding of cTMA, primarily attributed to its association with genetic disorders within the complement alternative pathway, remains relatively new. Consequently, treatment modalities for both cTMA and dnTMA were notably limited in the first ten years of our study. However, despite these limitations, our study represents one of the largest cohorts of kidney transplant recipients with TMA. Moreover, the outcomes derived from our study carry substantial implications for advancing comprehension of this disorder and elucidating its ramifications on allograft outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePost-transplant recurrent cTMA is an important cause of poor allograft survival in the first-year post kidney transplant. On the other hand, dnTMA is associated strongly with poor long-term allograft survival. More studies are needed to enhance our understanding and management of this complex disorder.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ecTMA: complement-mediated thrombotic microangiopathy. dnTMA: de novo thrombotic microangiopathy. aHR: adjusted hazard ratio. ESKD: end-stage kidney disease. CNI: calcineurin inhibitor toxicity. ABMR: antibody-mediated rejection. TCMR: T cell-mediated rejection. aHUS: Atypical hemolytic uremic syndrome. MCP: membrane cofactor protein. DDKT: deceased donor kidney transplant. LURT: living unrelated kidney transplant. LRT: living-related kidney transplant. GN: Glomerulonephritis. DSA: donor-specific antibodies. IFTA: Interstitial Fibrosis Tubular Atrophy. eGFR: Estimated glomerular filtration rate. rATG: rabbit anti-thymocyte globulins. MMF: mycophenolate mofetil. mTOR, mammalian target of rapamycin.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Johns Hopkins Hospital\u0026rsquo;s Institutional Review Board. This is a retrospective study, data were collected from the electronic medical records, consents were waived. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eThe authors give their consent for publication of this manuscript in BMC Nephrology.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available, as it is a center\u0026rsquo;s owned data but limited unidentified data are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eNone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions\u003c/p\u003e\n\u003cp\u003eKH participated in collecting data, analysis, and writing the manuscript\u003c/p\u003e\n\u003cp\u003eSL participated in collecting data and writing the manuscript\u003c/p\u003e\n\u003cp\u003eAD participated in collecting data and writing the manuscript\u003c/p\u003e\n\u003cp\u003eZO participated in collecting data and writing the manuscript\u003c/p\u003e\n\u003cp\u003eSB participated in collecting data and writing the manuscript\u003c/p\u003e\n\u003cp\u003eUM participated in study design, statistical analysis, and writing the manuscript\u003c/p\u003e\n\u003cp\u003eNA participated in study design, collecting data, analysis, and writing the manuscript\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHariharan S, Israni AK, Danovitch G. 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Kidney Int Rep. 2019;4(3):434\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatar D, Naqvi F, Racusen LC, Carter-Monroe N, Montgomery RA, Alachkar N. Atypical hemolytic uremic syndrome recurrence after kidney transplantation. Transplantation. 2014;98(11):1205\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlachkar N, Bagnasco SM, Montgomery RA. Eculizumab for the treatment of two recurrences of atypical hemolytic uremic syndrome in a kidney allograft. Transpl Int. 2012;25(8):e93\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlasfar S, Alachkar N. Atypical hemolytic uremic syndrome post-kidney transplantation: two case reports and review of the literature. Front Med (Lausanne). 2014;1:52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZuber J, Frimat M, Caillard S, Kamar N, Gatault P, Petitprez F, et al. Use of Highly Individualized Complement Blockade Has Revolutionized Clinical Outcomes after Kidney Transplantation and Renal Epidemiology of Atypical Hemolytic Uremic Syndrome. J Am Soc Nephrol. 2019;30(12):2449\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOpelz G, D\u0026ouml;hler B, Collaborative Transplant Study Report. Influence of time of rejection on long-term graft survival in renal transplantation. Transplantation. 2008;85(5):661\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArdalan MR, Shoja MM, Tubbs RS, Etemadi J, Esmaili H, Khosroshahi HT. Thrombotic microangiopathy in the early post-renal transplant period. Ren Fail. 2008;30(2):199\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegendre CM, Campistol JM, Feldkamp T, Remuzzi G, Kincaid JF, Lommel\u0026eacute; \u0026Aring;, et al. Outcomes of patients with atypical haemolytic uraemic syndrome with native and transplanted kidneys treated with eculizumab: a pooled post hoc analysis. Transpl Int. 2017;30(12):1275\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Andrade LGM, Contti MM, Nga HS, Bravin AM, Takase HM, Viero RM, et al. Long-term outcomes of the Atypical Hemolytic Uremic Syndrome after kidney transplantation treated with eculizumab as first choice. PLoS ONE. 2017;12(11):e0188155.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevi C, Fr\u0026eacute;meaux-Bacchi V, Zuber J, Rabant M, Devriese M, Snanoudj R, et al. Midterm Outcomes of 12 Renal Transplant Recipients Treated With Eculizumab to Prevent Atypical Hemolytic Syndrome Recurrence. Transplantation. 2017;101(12):2924\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoppula S, Yost SE, Sussman A, Bracamonte ER, Kaplan B. Successful conversion to belatacept after thrombotic microangiopathy in kidney transplant patients. Clin Transpl. 2013;27(4):591\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshman N, Chapagain A, Dobbie H, Raftery MJ, Sheaff MT, Yaqoob MM. Belatacept as maintenance immunosuppression for postrenal transplant de novo drug-induced thrombotic microangiopathy. Am J Transpl. 2009;9(2):424\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeixeira CM, Tedesco Silva Junior H, de Moura LAR, Proen\u0026ccedil;a HM, de Marco S, Gerbase R, de Lima M, et al. Clinical and pathological features of thrombotic microangiopathy influencing long-term kidney transplant outcomes. PLoS ONE. 2020;15(1):e0227445.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eTable 1. Baseline Patients Characteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003ednTMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003ecTMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e112 (83.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e22 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eMean (SD) Age at TMA diagnosis, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.5 \u0026plusmn; 16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e28.9 \u0026plusmn; 16.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eMean (SD) Age at transplant, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e46.1 \u0026plusmn; 14.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e38.5 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e66 (58.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e17 (77.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.287\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e42 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e5 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eGender, Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e56 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e15 (68.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eDonor type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Deceased donor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e69 (61.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e9 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Living unrelated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e20 (17.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e6 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Living related\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e23 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e7 (31.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eDonor\u0026apos;s age, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e43.5 \u0026plusmn; 14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e37.0 \u0026plusmn; 13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eDonor\u0026apos;s terminal Creatinine, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.1 (0.4-4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e1.4 (0.5-6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.540\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eHighly sensitized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e47 (67.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e15 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eHLAi or ABOi transplant (required desensitization)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e46 (51.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e6 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003ePre-transplant DSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e50 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e8 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eRe-transplantation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e63 (56.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e13 (59.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eWarm ischemic time, minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e47.2 \u0026plusmn; 24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.5 \u0026plusmn; 11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eCold ischemic time, hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e19.7 \u0026plusmn; 17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e10.3 \u0026plusmn; 10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eDelayed graft function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e45 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003eReason for previous graft loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; TMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e4 (5.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e15 (93.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u003csup\u003e\u0026para;\u0026nbsp;\u003c/sup\u003eAcute ABMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e9 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; Chronic ABMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e30 (39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"39.64686998394863%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; BK nephropathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.86677367576244%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.619582664526483%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eSD, standard deviation; TMA, thrombotic microangiopathy; \u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eHLAi, Human leukocyte antigens incompatible; ABOi, ABO-incompatible; \u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eDSA, donor specific antibody; \u003csup\u003e\u0026para;\u0026nbsp;\u003c/sup\u003eABMR, antibody mediated rejection.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eTable 2. Clinical and pathological findings at the time of post-transplant TMA diagnosis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003ednTMA (N=112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003ecTMA (N=22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eNumber of graft biopsies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e4.0 (1.0-12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.5 (0.0-10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.134\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eTime from first to last biopsy, months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e18.8 (0.0-296.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e45.2 (0.6-1290.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eMedian (IQR) of SCr at time of diagnostic biopsy, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.6 (0.4-24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.0 (0.7-15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eMean (SD) of Hg at time of diagnostic biopsy, g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.4 \u0026plusmn; 2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.6 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eMedian (IQR) of platelets count at time of diagnostic biopsy, x1000/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e167 (21.0-459)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e176 (47.0-396)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eMedian (IQR) of LDH at time of diagnostic biopsy, UI/L [Ref. 100-200]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e312 (91-1547)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e286 (200-1183)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eMedian (IQR) of last SCr, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e3.1 (0.3-17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e2.3 (0.4-5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eMean (SD) of last eGFR, mL/min/1.73 m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e23.5 \u0026plusmn; 22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e42.2 \u0026plusmn; 27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eMean (SD) of last Hemoglobin, g/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e10.6 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e9.5 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eRejection in the diagnostic biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e49 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e2 (10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026para;\u0026nbsp;\u003c/sup\u003eTCMR in diagnostic biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e26 (23.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e#\u003c/sup\u003e CNI toxicity in diagnostic biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e34 (30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (5.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eRejection, at least in one biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e90 (80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e11 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026dagger;\u003c/sup\u003eABMR, at least in one biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e29 (25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e1 (4.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026Dagger;\u0026nbsp;\u003c/sup\u003eCTG, at least in one biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e11 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e3 (13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.81410256410256%\" valign=\"bottom\"\u003e\n \u003cp\u003eCNI toxicity, at least in one biopsy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.557692307692307%\" valign=\"bottom\"\u003e\n \u003cp\u003e80 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.435897435897434%\" valign=\"bottom\"\u003e\n \u003cp\u003e5 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.192307692307693%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eSCr, serum creatinine; \u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eHg, Hemoglobin; \u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eeGFR, estimated glomerular filtration rate; \u003csup\u003e\u0026para;\u0026nbsp;\u003c/sup\u003eTCMR, T cell mediated rejection; antibody-mediated rejection; \u003csup\u003e#\u003c/sup\u003e CNI, calcineurin inhibitor; \u003csup\u003e\u0026dagger;\u0026dagger;\u003c/sup\u003eABMR, antibody mediated rejection; \u003csup\u003e\u0026Dagger;\u0026Dagger;\u0026nbsp;\u003c/sup\u003eCTG, chronic transplant glomerulopathy.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eTable 3. Hazard ratio of transplant failure from Cox proportional hazards regression model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMale gender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.06 to 2.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEthnicity (vs White)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.06 to 2.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.09 to 1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDonor type (vs Deceased donor)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Living unrelated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.65 to 2.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Living related\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.22 to 1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDelayed graft function\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.78 to 2.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRecurrent cTMA, first year\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(2.17 to18.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eABMR\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.90 to 1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eTCMR grade 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.12 to 1.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTCMR grade 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.22 to 1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBorderline rejection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.08 to 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eCNI toxicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(1.28 to 2.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eYearly change of the HR associated with cTMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e(0.76 to 0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003csup\u003e\u0026dagger;\u0026nbsp;\u003c/sup\u003eABMR, antibody mediated rejection;\u0026nbsp;\u003csup\u003e\u0026Dagger;\u0026nbsp;\u003c/sup\u003eTCMR, T cell mediated rejection;\u0026nbsp;\u003csup\u003e\u0026sect;\u0026nbsp;\u003c/sup\u003eCNI, calcineurin inhibitor.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Kidney, Transplant, Thrombotic Microangiopathy, complement-mediated TMA, de novo TMA","lastPublishedDoi":"10.21203/rs.3.rs-4688690/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4688690/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe outcome of kidney transplant recipients with a history of complement-mediated thrombotic microangiopathy (cTMA) and those who develop post-transplant de novo TMA (dnTMA) is largely unknown.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively studied all kidney transplant recipients with end-stage kidney disease secondary to cTMA and those who developed dnTMA, between Jan 2000 and Dec 2020 in our center.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe identified 134 patients, 22 with cTMA and 112 had dnTMA. Patients with cTMA were younger at the time of TMA diagnosis (age at diagnosis, 28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3. vs 46.5\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0 years; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). T-cell mediated rejection, borderline rejection, and calcineurin inhibitor toxicity were more prevalent in the first kidney transplant biopsy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the dnTMA group, and antibody-mediated rejection was more prevalent in anytime-biopsy (P\u0026thinsp;=\u0026thinsp;0.027). After adjusting for potential confounders, cTMA was associated with a 6-fold increase in the hazard of transplant failure during the first-year post-transplant (adjusted hazard ratio (aHR): 6.37 [95%CI: 2.17 to18.68; P\u0026thinsp;=\u0026thinsp;0.001]; the aHR decreased by 0.87 (95% CI: 0.76 to 0.99: P\u0026thinsp;=\u0026thinsp;0.033) per year elapsed since transplantation. Long-term allograft survival was similar in both groups.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePost kidney transplant TMA is an important cause of poor allograft survival. More studies are needed to enhance our understanding and management of this disorder.\u003c/p\u003e","manuscriptTitle":"The Outcome of Thrombotic Microangiopathy in Kidney Transplant Recipients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-10 12:27:40","doi":"10.21203/rs.3.rs-4688690/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-25T05:55:48+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-16T06:44:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-12T08:16:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-12T08:15:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2024-07-04T22:42:15+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9c14886d-9651-422f-8746-ab569b01199f","owner":[],"postedDate":"August 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T16:00:06+00:00","versionOfRecord":{"articleIdentity":"rs-4688690","link":"https://doi.org/10.1186/s12882-024-03846-x","journal":{"identity":"bmc-nephrology","isVorOnly":false,"title":"BMC Nephrology"},"publishedOn":"2024-11-28 15:57:09","publishedOnDateReadable":"November 28th, 2024"},"versionCreatedAt":"2024-08-10 12:27:40","video":"","vorDoi":"10.1186/s12882-024-03846-x","vorDoiUrl":"https://doi.org/10.1186/s12882-024-03846-x","workflowStages":[]},"version":"v1","identity":"rs-4688690","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4688690","identity":"rs-4688690","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}