Biopsy‐proven calciphylaxis in the Irish National Kidney Transplant Center 2010–2019

2021 ◽  
Author(s):  
Ciara O'Keeffe ◽  
Elsa Barbosa ◽  
Marina O'Kane
Keyword(s):  
Kidney Transplant ◽  
Transplant Center

scholarly journals Outcomes in Living Donor Kidney Transplantation: The Role of Donor’s Kidney Function

2021 ◽  
pp. 1-11
Author(s):  
Massimo Torreggiani ◽  
Ciro Esposito ◽  
Elena Martinelli ◽  
Thomas Jouve ◽  
Antoine Chatrenet ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Kidney Function ◽  
Living Donor ◽  
Graft Function ◽  
Kidney Graft ◽  
Donor Kidney ◽  
Transplant Center ◽  
Function Correlation ◽  
End Stage ◽  
Living Donor Kidney

<b><i>Introduction:</i></b> Living donor kidney transplant (LDKT) is one of the best therapeutic options for end-stage kidney disease (ESKD). Guidelines identify different estimated glomerular filtration rate (eGFR) thresholds to determine the eligibility of donors. The aim of our study was to evaluate whether pretransplant donor eGFR was associated with kidney function in the recipient. <b><i>Methods:</i></b> We retrospectively studied LDKT recipients who received a kidney graft between September 1, 2005, and June 30, 2016 in the same transplant center in France and that had eGFR data available at 3, 12, 24, and 36 months posttransplant. <b><i>Results:</i></b> We studied 90 donor-recipient pairs. The average age at time of transplant was 51.47 ± 10.95 for donors and 43.04 ± 13.52 years for recipients. Donors’ average eGFR was 91.99 ± 15.37 mL/min/1.73 m<sup>2</sup>. Donor’s age and eGFR were significantly correlated (<i>p</i> &#x3c; 0.0001, <i>r</i><sup>2</sup> 0.023). Donor’s age and eGFR significantly correlated with recipient’s eGFR at 3, 12, and 24 months posttransplant (age: <i>p</i> &#x3c; 0.001 at all intervals; eGFR <i>p</i> = 0.001, 0.003, and 0.016, respectively); at 36 months, only donor’s age significantly correlated with recipient’s eGFR. BMI, gender match, and year of kidney transplant did not correlate with graft function. In the multivariable analyses, donor’s eGFR and donor’s age were found to be associated with graft function; correlation with eGFR was lost at 36 months; and donor’s age retained a strong correlation with graft function at all intervals (<i>p</i> &#x3c; 0.001). <b><i>Conclusions:</i></b> Donor’s eGFR and age are strong predictors of recipient’s kidney function at 3 years. We suggest that donor’s eGFR should be clinically balanced with other determinants of kidney function and in particular with age.

Local Variation in Inclusion on Kidney Transplant Waiting Lists: Analysis in the Reference Area of a Kidney Transplant Center

2018 ◽  
Vol 50 (2) ◽  
pp. 550-552 ◽  
Author(s):  
N.G. Toapanta Gaibor ◽  
G. Bernal Blanco ◽  
M. Cintra Cabrera ◽  
A. Suarez Benjumea ◽  
M.A. Pérez Valdivia ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Local Variation ◽  
Waiting Lists ◽  
Reference Area ◽  
Transplant Center

scholarly journals Antibiotic Sensitivity and Resistance Among the Most Common Uropathogens in Kidney Transplant Recipients

2015 ◽  
Vol 12 (1) ◽  
pp. 27-32
Author(s):  
Borelli Zlatkov ◽  
Jean Filipov ◽  
Emil Paskalev ◽  
Boyka Markova ◽  
Yuliya Marteva-Proevska ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Kidney Transplant ◽  
Antibiotic Sensitivity ◽  
High Sensitivity ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Bacterial Strains ◽  
Gram Positive ◽  
Transplant Center ◽  
Enterococcus Spp

Abstract Introduction. Urinary tract infection (UTI) among kidney transplant recipients (KTRs) is one of the most common complications after transplantation. The aim of our study was to analyze the antibiotic sensitivity and resistance of the most common agents causing UTI in Bulgarian KTRs followed up in our Transplant Center. Methods. We analyzed the antibiotic resistance and sensitivity of the most common strains of bacteria causing UTI in the Bulgarian KTRs, namely class Enterobac-teriaceae and Enterococcus spp. We used conventional biochemical methods to identify different strains of uro-pathogens-miniApi (bioMerieux, France) and BBL Crystal (BD). The antibiotic sensitivity was determined via disc-diffusing method, according to the accepted Bulgarian CLSI standard. We used WHONET, version 5.6 to analyze the antibiotic resistance data. Results. The total number of tested patients was 366 [males 228, females 138]. The total number of tested urine samples was 829 [positive ones-203), negative samples 606, contaminated 20]. The most commonly detected uropathogens in Bulgarian KTRs were Gram /-/ negative bacteria (63.80%). Of these, 93.28% belonged to the Enterobacteriaceae group, with E. coli, K. pneumoniae and the PPM /Proteus, Providentia, Mor-ganela/subgroup being the most common (54.5%, 19.20% and 16%, respectively). Gram /+/ positive bacteria were detected in 28.09% of the patients, Enterococcus spp being the most commonly isola-ted-67.79%. In the Enterococcus group, the strains of E. faecalis and E. faecium were the most commonly detected. The bacteria belonging to Enterobacteriaceae group were most sensitive to carbapenems and aminoglycosides, with sensitivity peaking to almost 100%, whereas they were least sensitive to aminopenicillines [sensitivity below 20%]. The PPM subgroup revealed very high sensitivity to beta-lactamase protected broad spectrum penicillins (Piperacillin/Tazobactam, sensitivity - 90%). Gram /+/ positive uropathogens were mostly sensitive to Linezolid, Vancomycin, Teicoplanin (100%). These strains were least sensitive to Erythromycin and Tetracicline (17.50%). Conclusions. Our results were similar to previous studies. The differences detected can be explained with the characteristics of the bacterial strains and the specific practice of each transplant center. Having in mind the possible complications of UTIs, further studies are needed to clarify the problem with antimicrobial resistance in uropathogens and the use of antibiotics after KT.

Highly HLA Sensitized Kidney Transplant Patients in a Transplant Center

2018 ◽  
Vol 50 (2) ◽  
pp. 436-440 ◽  
Author(s):  
P.K. Garcia ◽  
J. Toro ◽  
C. Borda ◽  
C. Gonzalez ◽  
M.P. Rodriguez ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Transplant Patients ◽  
Transplant Center ◽  
Kidney Transplant Patients

Impact of Kidney Transplant Center Performance On the Survival Advantage of Transplantation Versus Dialysis.

2014 ◽  
Vol 98 ◽  
pp. 201-202
Author(s):  
J. Schold ◽  
L. Buccini ◽  
D. Goldfarb ◽  
S. Flechner ◽  
E. Poggio ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Survival Advantage ◽  
Transplant Center

Readmission Rates Are a Poor Proxy for Transplant Center Quality of Care among US Kidney Transplant Recipients

2012 ◽  
Vol 94 (10S) ◽  
pp. 185 ◽  
Author(s):  
T. R. Srinivas ◽  
R. Woodward ◽  
A. Tang ◽  
D. Goldfarb ◽  
S. Flechner ◽  
...  
Keyword(s):  
Quality Of Care ◽  
Kidney Transplant ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Readmission Rates ◽  
Transplant Center

Low Activity Kidney Transplant Center - What Are The Results?

2014 ◽  
Vol 98 ◽  
pp. 257
Author(s):  
H. Sanders-Pinheiro ◽  
L. Braga ◽  
L. Moratelli ◽  
M. Carminatti ◽  
F. Colugnati ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Transplant Center ◽  
Low Activity

scholarly journals Effect of Comorbidity Adjustment on CMS Criteria for Kidney Transplant Center Performance

2009 ◽  
Vol 9 (3) ◽  
pp. 506-516 ◽  
Author(s):  
E. D. Weinhandl ◽  
J. J. Snyder ◽  
A. K. Israni ◽  
B. L. Kasiske
Keyword(s):  
Kidney Transplant ◽  
Transplant Center

scholarly journals Failure of the New Kidney Allocation System in a Specific Ethnic Group

2020 ◽  
Author(s):  
Texell Longoria-Dubocq ◽  
Yaritza Pizarro-Gonzalez ◽  
Isabel Mayorga-Perez ◽  
Mariel Javier-Gonzalez ◽  
Pedro Hernandez-Rivera
Keyword(s):  
Kidney Transplant ◽  
Graft Failure ◽  
Wait Time ◽  
Mortality Rates ◽  
Kidney Allocation ◽  
Allocation System ◽  
Transplant Center ◽  
Kidney Allocation System ◽  
Before And After ◽  
Moderate Volume

ABSTRACTIntroductionThe Kidney Allocation System (KAS) implemented on December 4, 2014, was expected to improve kidney transplant list wait-time and allocate more kidney to high cPRA patients. This study aims to demonstrate outcomes after the implementation of the KAS in a Hispanic transplant center.MethodsRetrospective study from a prospectively maintained database from a single-transplant center. Included all DDKT from July 2013 to June 2016. Compare and analyze DDKT selection and outcomes before and after KAS implementation.ResultsThe overall number of kidney transplants performed during this period was 220. All of the patients were Hispanic. Included 50.5% Pre-KAS and 49.5% Post-KAS. Pre-KAS group had a significantly shorter waiting-time list than the post-KAS group, 900.05 vs 1126.75 respectively. EPTS less than 20% significantly improved in the Post-KAS group compared to the Pre-KAS group, 41.3% vs 20.9% respectively. No differences observed in KDPI, 1-year graft failure, or 1-year mortality rates.ConclusionThis might be the first Hispanic only cohort evaluating the effects of KAS on a moderate volume kidney transplant center. The new system increased the wait-time list by approximately 25%, and it did not improve graft quality, graft failure, or mortality rates.

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