Acute Kidney Injury, Microvascular Rarefaction, and Estimated Glomerular Filtration Rate in Kidney Transplant Recipients

2021 ◽  
pp. CJN.07270520
Author(s):  
Alice Doreille ◽  
Féryel Azzi ◽  
Stéphanie Larivière-Beaudoin ◽  
Annie Karakeussian-Rimbaud ◽  
Dominique Trudel ◽  
...  
Keyword(s):  
Graft Function ◽  
Capillary Density ◽  
Interquartile Range ◽  
Delayed Graft Function ◽  
Kidney Transplant Recipients ◽  
Peritubular Capillary ◽  
Post Transplant ◽  
Peritubular Capillaries ◽  
Microvascular Rarefaction

Background and objectivesAnimal studies suggest that microvascular rarefaction is a key factor in the acute kidney disease to CKD transition. Hence, delayed graft function appears as a unique human model of AKI to further explore the role of microvascular rarefaction in kidney transplant recipients. Here, we assessed whether delayed graft function is associated with peritubular capillary loss and evaluated the association between this loss and long-term kidney graft function.Design, setting, participants, & measurementsThis observational, retrospective cohort study included 61 participants who experienced delayed graft function and 130 who had immediate graft function. We used linear regression models to evaluate associations between delayed graft function and peritubular capillary density expressed as the percentage of efficient cortical area occupied by peritubular capillaries in pre- and post-transplant graft biopsies. eGFRs 1 and 3 years post-transplant were secondary outcomes.ResultsPost-transplant biopsies were performed at a median of 113 days (interquartile range, 101–128) after transplantation. Peritubular capillary density went from 15.4% to 11.5% in patients with delayed graft function (median change, −3.7%; interquartile range, −6.6% to −0.8%) and from 19.7% to 15.1% in those with immediate graft function (median change, −4.5%; interquartile range, −8.0% to −0.8%). Although the unadjusted change in peritubular capillary density was similar between patients with and without delayed graft function, delayed graft function was associated with more peritubular capillary loss in the multivariable analysis (adjusted difference in change, −2.9%; 95% confidence interval, −4.0 to −1.8). Pretransplant peritubular capillary density and change in peritubular capillary density were associated with eGFR 1 and 3 years post-transplantation.ConclusionsPerioperative AKI is associated with lower density in peritubular capillaries before transplantation and with loss of peritubular capillaries following transplantation. Lower peritubular capillary density is linked to lower long-term eGFR.

scholarly journals Associations of pre-transplant anemia management with post-transplant delayed graft function in kidney transplant recipients

2012 ◽  
Vol 26 (5) ◽  
pp. 782-791 ◽  
Author(s):  
Miklos Z. Molnar ◽  
Csaba P. Kovesdy ◽  
Laszlo Rosivall ◽  
Suphamai Bunnapradist ◽  
Junichi Hoshino ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Graft Function ◽  
Delayed Graft Function ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Post Transplant ◽  
Anemia Management

MO941CLINICAL OUTCOMES IN KIDNEY RE-TRANSPLANTATION

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Clara Pardinhas ◽  
Rita Leal ◽  
Francisco Caramelo ◽  
Teofilo Yan ◽  
Carolina Figueiredo ◽  
...  
Keyword(s):  
Acute Rejection ◽  
Kidney Transplant ◽  
Graft Survival ◽  
Graft Failure ◽  
Graft Function ◽  
Delayed Graft Function ◽  
First Year ◽  
Kidney Transplant Recipients ◽  
Post Transplant

Abstract Background and Aims As kidney transplants are growing in absolute numbers, so are patients with failed allografts and thus potential candidates for re-transplantation. Re-transplantation is challenging due to immunological barriers, surgical difficulties and clinical complexities but it has been proven that successful second transplantation improves life expectancy over dialysis. It is important to evaluate re-transplantation outcomes since 20% of patients on the waiting list are waiting for a second graft. Our aim was to compare major clinical outcomes such as acute rejection, graft and patient survival, between patients receiving a first or a second kidney transplant. Method We performed a retrospective study, that included 1552 patients submitted to a first (N=1443, 93%) or a second kidney transplant (N=109, 7%), between January 2008 and December 2018. Patients with more than 2 grafts or multi-organ transplant were excluded. Demographic, clinical and histocompatibility characteristics of both groups were registered from our unit database and compared. Delayed graft function was defined has the need of dialysis in the first week post-transplant. All acute rejection episodes were biopsy proven, according to Banff 2017 criteria. Follow-up time was defined at 1st June 2020 for functioning grafts or at graft failure (including death with a functioning graft). Results Recipients of a second graft were significantly younger (43 ±12 vs 50 ± 13 years old, p<0.001) and there were significantly fewer expanded-criteria donors in the second transplant group (31.5% vs 57.5%, p<0.001). The waiting time for a second graft was longer (63±50 vs 48±29 months, p=0.011). HLA mismatch was similar for both groups but PRA was significantly higher for second KT patients (21.6±25% versus 3±9%; p<0.001). All patients submitted to a second KT had thymoglobulin as induction therapy compared to 16% of the first KT group (p<0.001). We found no difference in primary dysfunction or delayed graft function between groups. Acute rejection was significantly more frequent in second kidney transplant recipients (19% vs 5%, p<0.001), being 10 acute cellular rejections, 7 were antibody mediated and 3 were borderline changes. For the majority of the patients (85%), acute rejection occurred in the first-year post-transplant. Death censored graft failure occurred in 236 (16.4%) patients with first kidney transplant and 25 (23%) patients with a second graft, p=0.08. Survival analysis showed similar graft survival for both groups (log-rank p=0.392). We found no difference in patients’ mortality at follow up for both groups. Conclusion Although second graft patients presented more episodes of biopsy proven acute rejection, especially at the first-year post-transplant, we found no differences in death censored graft survival or patients’ mortality for patients with a second kidney transplant. Second transplants should be offered to patients whenever feasible.

173: Delayed Graft Function (DGF) in HIV+ Kidney Transplant Recipients Predicts Worse Long-Term Renal Function

2010 ◽  
Vol 55 (4) ◽  
pp. B75
Author(s):  
Lissa Levin ◽  
Gregory Malat ◽  
Mohit Gupta ◽  
Muhammad Saeed ◽  
Snehankita Kulkarni ◽  
...  
Keyword(s):  
Renal Function ◽  
Kidney Transplant ◽  
Graft Function ◽  
Delayed Graft Function ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients

scholarly journals SP757The Burden of Delayed Graft Function on Kidney Transplant Recipients and Impact on long-term outcomes

2019 ◽  
Vol 34 (Supplement_1) ◽  
Author(s):  
Mia Vasilj ◽  
Fabian Halleck ◽  
Dmytro Khadzhynov ◽  
Eva Schrezenmeier ◽  
Michael Dürr ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Graft Function ◽  
Delayed Graft Function ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Long Term Outcomes

scholarly journals Urological Complications in Kidney Transplant Recipients: Analysis of the Risk Factors and Impact on Transplant Outcomes in the Era of “Extended Criteria Donors”

2021 ◽  
Vol 2 (1) ◽  
pp. 22-36
Author(s):  
Roberta Angelico ◽  
Marco Pellicciaro ◽  
Francesca Venza ◽  
Tommaso Maria Manzia ◽  
Roberto Cacciola ◽  
...  
Keyword(s):  
Risk Factors ◽  
Graft Survival ◽  
Survival Rates ◽  
Graft Function ◽  
Significant Risk ◽  
Kidney Transplant Recipients ◽  
Post Transplant ◽  
Extended Criteria Donors ◽  
Urological Complications

Urological complications (UC) following kidney transplantation (KT) are associated with increased morbidity. The aim of this study is to evaluate the risk factors for UC in the era of “extended criteria donors” (ECD) and their impact on patient and graft survivals. A retrospective monocentric study of all patients undergoing KT from 2010 to 2019 with a follow-up ≥30 days was performed. Out of 459 patients (males: 296 (64.5%); age: 57 (19–77) years) enrolled, 228 (49.7%) received ECD organs, moreover, 166 (67.2%) grafts had a cold ischemia time ≥10 h. UCs were reported in 32 (7%) patients. In 21 (65.6%) cases UC occurred within 3 months post-KT and 24 (5.2%) were associated with early urinary tract infection (UTI). The overall 5 year patient and graft survival rates were 96.5% and 90.6%, respectively. UC decreased graft survival (UC-group: 75.0% vs. noUC-group: 91.8%, p < 0.001), especially if associated with early UTI (UC-group: 71.4% vs. noUC-group: 77.8%, p < 0.001). At multivariate analysis, early UTI after KT (OR: 9.975, 95%-IC: 2.934–33.909, p < 0.001) and delayed graft function (DGF) (OR: 3.844, 95%-IC: 1.328–11.131, p: 0.013) were significant risk factors for UC, while ECD graft did not increase the risk of post-transplant UC. ECD grafts are not associated with UC. DGF and early UTI post-KT increase the risks of UC and reduce graft survival in the long-term. Therefore, aggressive management of early post-transplant UTI and strategies to reduce DGF incidence, such as machine preservation, are essential to prevent UC after KT.

scholarly journals Indicators of monocyte-derived component of the immune system in patients with satisfactory renal graft function

2020 ◽  
Vol 22 (2) ◽  
pp. 53-62
Author(s):  
S. V. Zybleva ◽  
S. L. Zyblev
Keyword(s):  
Kidney Transplant ◽  
Negative Correlation ◽  
Graft Function ◽  
Control Group ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Post Transplant ◽  
Long Term Follow Up

Objective: to study the indicators of the monocyte-derived component of the immune system in kidney transplant recipients with satisfactory early and delayed renal transplant function. Materials and methods. The study involved 76 kidney transplant recipients. Concentrations of serum creatinine (sCr), serum urea (sUr) and serum cystatin C (sCysC) were measured. CD14+mid/high and CD14+low were isolated from CD14+ monocytes. CD64- and CD86-expressing cell counts were determined for each subpopulation. Immunological examination was performed before surgery, as well as at days 1, 3, 7, 30, 90, 180 and 360 after surgery. Results. There was significant imbalance between the two monocyte subpopulations before transplantation and in the early post-transplant period (first 3 months). By the end of a 6-month follow-up period, the percentage of CD14+ cells had normalized. The dynamics of the subclasses of CD86-expressing monocytes in the post-transplant period is somewhat different from the dynamics of the total count for these monocytes. However, by the end of a 6-month follow-up period, these biomarkers returned to normal for the group of healthy individuals (CD14+mid/highCD86+ p180 = 0.079; CD14+lowCD86+ p180 = 0.789). CD14+lowCD64+ level was significantly higher in the kidney transplant group than in the control group during the entire follow-up period (p0 = 0.0006, p1 = 0.0001, p7 = 0.005, p30 = 0.005, p90 = 0.007, p180 = 0.0002, p360 = 0.001). On the other hand, CD14+mid/highCD64+ count for up to 180 days was not significantly different from that of the control group (p0 = 0.561, p1 = 0.632, p7 = 0.874, p30 = 0.926, p90 = 0.912), with subsequent significant increase by day 360 of follow-up (p180 = 0.01, p360 = 0.003). We observed a negative correlation between CD14+lowCD86+ level at day 0 and sCr levels at day 7 (r = –0.4; p = 0.008) and day 360 (r = –0.34; p = 0.042) and sCysC level at day 7 (r = –0.57; p = 0.014). A negative correlation was also found between CD14+lowCD86+ at day 1 and sCr levels at day 7 (r = –0.4; p = 0.005) and day 360 (r = –0.39; p = 0.02). There was positive correlation between the CD14+lowCD64+ subpopulation index at day 0 and sCr (r = 0.54; p = 0.008) and sCysC (r = 0.6; p = 0.008) levels at day 7, and also between the CD14+lowCD64+ count at day 1 and sCr (r = 0.55; p < 0.0001) and sCysC (r = 0.58; p = 0.004) levels at day 7. CD14+mid/highCD64+ at day 0 negatively correlated with sCysC level at day 360 (r = –0.85; p = 0.015), while CD14+mid/highCD64+ at day 7 positively correlated with sCysC level at day 360 (r = 0.50; p = 0.016). Conclusion. Before transplant surgery, CD14+mid/high, CD14+mid/highCD86+ , and CD14+lowCD86+ counts were reduced, while those of CD14+low, CD14+mid/highCD64+ and CD14+lowCD64+ were increased. By the 6-month follow-up, all these subpopulations except CD14+mid/highCD64+ had reached values for healthy people. Positive correlation between CD14+mid/high, CD14+lowCD64+ , CD14+mid/highCD86+ , CD14+mid/highCD64+ counts in the early post-transplant period and sCr/sCysC levels in long-term follow-up, as well as negative correlation between CD14+low, CD14+lowCD86+ counts in the early post-transplant period and sCr/sCysC levels in long-term follow-up can serve as a predictor of renal graft function.

scholarly journals Changes in body mass index and outcomes after kidney transplantation: a single centre, retrospective, observational study

2019 ◽  
Author(s):  
Adam Arshad ◽  
James Hodson ◽  
Khalid Khalil ◽  
Adnan Sharif
Keyword(s):  
Body Mass Index ◽  
Kidney Transplantation ◽  
Body Mass ◽  
Geometric Mean ◽  
Graft Function ◽  
Estimating Equation ◽  
Kidney Transplant Recipients ◽  
Long Term Outcomes ◽  
Post Transplant

Abstract Background The aim of this study was to describe the changes in body mass index (BMI) after kidney transplantation and assess how this influences long-term outcomes. Methods Data were collected for all kidney transplant recipients between January 2007 and July 2016. Changes in BMI over the post-transplant period were modelled using a generalised estimating equation. The change in BMI from pre-transplantation to six months was then calculated for each patient. These were categorised into three groups: stable BMI (a change of ±1.5 kg/m2), BMI reduction and BMI increase (changes of >1.5 kg/m2), between which a range of outcomes were compared. Results Data was available for 1,344 patients, who had a geometric mean pre-transplant BMI of 27.3 kg/m2. This declined significantly (P<0.001), to a geometric mean of 25.6 kg/m2 one month after transplantation, before increasing and stabilising to pre-transplant levels by 36 months (geometric mean 27.2 kg/m2, P=0.522). The n=882 patients with BMI measurements at six months, were divided into groups of reduced (n=303), stable (n=388) and increased (n=131) BMI, relative to pre-transplantation levels. On multivariate analysis, 12-month creatinine levels were significantly higher in the BMI reduction cohort, with adjusted levels of 160.6 μmol/l, compared to 135.0 μmol/l in stable BMI. However, no significant associations were detected between six-month BMI change and patient survival, graft survival, incidence of post-transplant diabetes, cancer, or a range of clinical and histological outcomes (all P>0.05). Conclusions Our data demonstrates that BMI significantly reduces in the first month after kidney transplantation, before increasing to pre-transplant levels at 3-5 years. Furthermore, patients with decreasing BMI at six-months have impaired graft function in the long-term. These observations conflict with the existing literature and warrant further investigation.

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