Association Between Preoperative Allograft Function (Effective Renal Plasma Flow) and the Change in Glomerular Filtration Rate Among Living-Donor Kidney Transplant Recipients

Chang, Sheng-Po; Hung, Chung-Jye; Chou, Tse‐Chuan; Chung, P. Y.; Lin, Yo‐Sheng; Lee, P. C.

doi:10.1016/j.transproceed.2011.11.045

Cited by 6 publications

(3 citation statements)

References 25 publications

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“…Other studies available at the time provided limited additional information [17,18]. A more recent single-centre study of 83 living kidney transplants found that poor pre-donation effective renal plasma flow was not associated with an increased rate of decline of allograft function [19].…”

Section: Discussionmentioning

confidence: 99%

Living kidney donor estimated glomerular filtration rate and recipient graft survival

Young

Kim

Garg

et al. 2013

Nephrology Dialysis Transplantation

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Section: Discussionmentioning

confidence: 99%

Living kidney donor estimated glomerular filtration rate and recipient graft survival

Young

Kim

Garg

et al. 2013

Nephrology Dialysis Transplantation

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“…Using recurrent neural network sequence-to-sequence modeling, we developed a tool to forecast patient-specific kidney transplant function. Rather than aiming at prognostication of graft failure The clinical assessment of trajectories of kidney function was previously modeled statistically and evaluated for prognostication, for example by using latent class mixed models 13,14 and ARIMA, [15][16][17] but prediction of future patient-specific expected ranges, to benchmark new measured values against, is specific to this study. This model incorporates previous eGFR trajectories in its prediction, with better accuracy than a more conventional ARIMA model.…”

Section: Discussionmentioning

confidence: 99%

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model

et al. 2021

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IMPORTANCELike other clinical biomarkers, trajectories of estimated glomerular filtration rate (eGFR) after kidney transplant are characterized by intra-individual variability. These fluctuations hamper the distinction between alarming graft functional deterioration or harmless fluctuation within the patient-specific expected reference range of eGFR. OBJECTIVE To determine whether a deep learning model could accurately predict the patientspecific expected reference range of eGFR after kidney transplant.

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“…Studies assessing the effect of donor's kidney function on recipient's graft function[24][25][26][52][53][54] …”

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confidence: 99%

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

Torreggiani

Esposito

Martinelli

et al. 2021

Kidney Blood Press Res

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Introduction: 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. Methods: 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. Results: 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 m2. Donor’s age and eGFR were significantly correlated (p < 0.0001, r2 0.023). Donor’s age and eGFR significantly correlated with recipient’s eGFR at 3, 12, and 24 months posttransplant (age: p < 0.001 at all intervals; eGFR p = 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 (p < 0.001). Conclusions: 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.

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Association Between Preoperative Allograft Function (Effective Renal Plasma Flow) and the Change in Glomerular Filtration Rate Among Living-Donor Kidney Transplant Recipients

Cited by 6 publications

References 25 publications

Living kidney donor estimated glomerular filtration rate and recipient graft survival

Living kidney donor estimated glomerular filtration rate and recipient graft survival

Forecasting of Patient-Specific Kidney Transplant Function With a Sequence-to-Sequence Deep Learning Model

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

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