The proportion of patients undergoing liver transplantation (LT) with renal insufficiency has significantly increased in the Model for End-Stage Liver Disease (MELD) era. This study was designed to determine the incidence and predictors of post-LT chronic renal failure (CRF) and its effect on patient survival in the MELD era. Outcomes of 221 adult LT recipients who had LT between February 2002 and February 2007 were reviewed retrospectively. Patients who were listed as status 1, were granted a MELD exception, or had living-donor, multiorgan LT were excluded. Renal insufficiency at LT was defined as none to mild [estimated glomerular filtration rate (GFR) Ն 60 mL/minute], moderate (30-59 mL/minute), or severe (Ͻ30 mL/minute). Post-LT CRF was defined as an estimated GFR Ͻ 30 mL/minute persisting for 3 months, initiation of renal replacement therapy, or listing for renal transplantation. The median age was 54 years, 66% were male, 89% were Caucasian, and 43% had hepatitis C. At LT, the median MELD score was 20, and 6.3% were on renal replacement therapy. After a median follow-up of 2.6 years (range, 0.01-5.99), 31 patients developed CRF with a 5-year cumulative incidence of 22%. GFR at LT was the only independent predictor of post-LT CRF (hazard ratio ϭ 1.33, P Ͻ 0.001). The overall post-LT patient survival was 74% at 5 years. Patients with MELD Ն 20 at LT had a higher cumulative incidence of post-LT CRF in comparison with patients with MELD Ͻ 20 (P ϭ 0.03). A decrease in post-LT GFR over time was the only independent predictor of survival. In conclusion, post-LT CRF is common in the MELD era with a 5-year cumulative incidence of 22%. Low GFR at LT was predictive of post-LT CRF, and a decrease in post-LT GFR over time was associated with decreased post-LT survival. Further studies of modifiable preoperative, perioperative, and postoperative factors influencing renal function are needed to improve outcomes following LT. Liver Transpl 15:1142-1148 Liver transplantation (LT) has altered the natural history of end-stage liver disease and is now considered the preferred therapy for a wide range of previously fatal chronic liver diseases. Optimal timing of LT is important to avoid harm from intervening too early and futility from transplanting too late.Serum creatinine, bilirubin, and the international normalized ratio of the prothrombin time are the components of the Model for End-Stage Liver Disease (MELD), which has served as the basis for liver allocation since February 2002.1 An analysis of data from the Scientific Registry of Transplant Recipients showed that the proportion of candidates with creatinine Ն 2.0 mg/dL or on renal replacement therapy (RRT) at the time of LT has increased significantly in the MELD era. Pre-LT renal insufficiency is also an important predictor of post-LT morbidity and mortality.3,4 Many studies have shown that patients with renal insufficiency at the time of LT have increased sepsis, number

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A kidney paired donation (KPD) pool consists of transplant candidates and their incompatible donors along with non-directed donors (NDDs). In a match run, exchanges are arranged among pairs in the pool via cycles, as well as chains created from NDDs. A problem of importance is how to arrange cycles and chains to optimize the number of transplants. We outline and examine, through example and by simulation, four schemes for selecting potential matches in a realistic model of a KPD system; our proposed schemes take account of probabilities that chosen transplants may not be completed as well as allowing for contingency plans when the optimal solution fails. Using data on candidate/donor pairs and NDDs from the Alliance for Paired Donation, the simulations extend over 8 match runs, with 30 pairs and 1 NDD added between each run. Schemes that incorporate uncertainties and fallbacks into the selection process yield substantially more transplants on average, increasing the number of transplants by as much as 40% compared to a standard selection scheme. The gain depends on the degree of uncertainty in the system. The proposed approaches can be easily implemented and provide substantial advantages over current KPD matching algorithms.

IntroductionNephCure Accelerating Cures Institute (NACI) is a collaborative organization sponsored by NephCure Kidney International and the University of Michigan. The Institute is composed of 7 cores designed to improve treatment options and outcomes for patients with glomerular disease: Clinical Trials Network, Data Warehouse, Patient-Reported Outcomes (PRO) and Endpoints Consortium, Clinical Trials Consulting Team, Quality Initiatives, Education and Engagement, and Data Coordinating Center.MethodsThe Trials Network includes 22 community- and hospital-based nephrology practices, 14 of which are trial-only sites. Eight sites participate in the NACI Registry, and as of October 2017, 1054 patients are enrolled with diagnoses including but not limited to focal segmental glomerulosclerosis, minimal change disease, membranous nephropathy, IgA nephropathy, and childhood-onset nephrotic syndrome. By using electronic health record data extraction, robust and efficient clinical data are captured while minimizing the burden to site-based network staff.ResultsThe Data Warehouse includes her-extracted data from registry patients, PRO development data, and data from completed observational studies and clinical trials. The Clinical Trial Consulting Team provides support for trial design in rare diseases leveraging these data. The PRO and Endpoints Consortium develops shorter-term endpoints while capturing the patient-reported significance of interventions under study. The Quality Initiatives and Education/Engagement cores elevate the level of care for patients. The Data Coordinating Center manages the analysis and operations of the Institute.ConclusionBy engaging with patients, academia, industry, and patient advocate community representatives, including our Patient Advisory Board, NACI strives for better outcomes and treatments using evidence-based support for clinical trial design.