Aim: Long-term survival of renal allografts has improved over the last 20 years. However, less is known about current expectations for long-term allograft function as determined by estimated glomerular filtration rate (eGFR). The aim of this study was to investigate factors which affect graft function at 5 years' post-renal transplantation. The statistically significant factors were then used to construct a predictive model for expected eGFR at five years' post-transplant. Methods: We retrospectively reviewed all adult patients who received a renal transplant in the Republic of Ireland between 1990 and. Data collected included era of transplantation (1990-1994, 1995-1999, 2000-2004), donor and recipient age and gender, number of human leucocyte antigen mismatches, cold ischemia time (CIT), number of prior renal transplants, immunosuppressive regimen used and acute rejection episodes. Estimated GFR was calculated at 5 years after transplantation from patient data using the Modified Diet in Renal Disease (MDRD) equation. Consecutive sampling was used to divide the study population into two equal unbiased groups of 489 patients. The first group (derivation cohort) was used to construct a predictive model for eGFR five years' post-transplantation, the second (validation cohort) to test this model. Results: Nine hundred and seventy eight patients were analyzed. The median age at transplantation was 43 years (range 18-78) and 620 (63.4%) were male. One hundred and seventy five patients (17.9%) had received a prior renal transplant. Improved eGFR at five years' post-transplantation was associated with tacrolimus-based combination immunosuppression, younger donor age, male recipient, absence of cytomegalovirus disease and absence of acute rejection episodes as independently significant factors (p50.05). The predictive model developed using these factors showed good correlation between predicted and actual median eGFR at five years. The model explained 20% of eGFR variability. The validation model findings were consistent with the derivation model (21% variability of eGFR explained by model using same covariates on new data). Conclusion: The predictive model we have developed shows good correlation between predicted and actual median eGFR at five years' post-transplant. Applications of this model include comparison of current and future therapy options such as new immunosuppressive regimens.
Pre-implant kidney biopsy is used to determine suitability of marginal donor kidneys for transplantation. However, there is limited data examining the utility of pre-implant histology in predicting medium term graft outcome. This retrospective study examined kidney transplants over a 10-year period at a single center to determine if pre-implant histology can identify cases of eGFR ≤35 ml/min/1.73m at 5 year follow up beyond a clinical predictive logistic regression model. We also compared outcomes of dual kidney transplants with standard single kidney transplants. Of 1195 transplants, 171 received a pre-implant kidney biopsy and 15 were dual transplants. There was no significant difference in graft and patient survival rates. Median eGFR was lower in recipients of biopsied kidneys compared with standard kidney transplants (44 vs. 54 ml/min/1.73m, p < .001). Median eGFR of dual transplant and standard kidney transplants were similar (58 vs. 54 ml/min/1.73m, p = .64). Glomerular sclerosis (p = .05) and Karpinski Score (p = .03) were significant predictors of eGFR at 5-years in multivariate analysis but did not improve discrimination of eGFR ≤35 ml/min/1.73m at 5-years beyond a clinical prediction model comprising donor age, donor hypertension and terminal donor creatinine (C-statistic 0.67 vs. 0.66; p = .647). Pre-implant histology did not improve prediction of medium-term graft outcomes beyond clinical predictors alone. Allograft function of dual transplant kidneys was similar to standard transplants, suggesting that there is scope to increase utilization of kidneys considered marginal based on histology.
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