Silva, Artur Quintiliano Bezerra da

Background. Living kidney donation (KD) evaluation particularly focuses on glomerular filtration rate (GFR). Assessing GFR in living kidney donors can be done by estimation (eGFR) or measurement (mGFR). This study aims to evaluate the impact of eGFR equations, focusing on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 equation for donor eligibility screening and the reclassification of donors excluded by eGFR criteria to mGFR assessments. Methods. Retrospective, single-center observational study of 2512 kidney donors evaluated between 2011 and 2023, at the Mayo Clinic. We performed analyses and comparisons of 4 eGFR formulae and 2 mGFR methods in terms of performance, eligibility criteria according to Kidney Disease: Improving Global Outcomes guidelines/age-adjusted criteria, eligibility reclassification, and subgroup analyses. Results. The CKD-EPI 2021 resulted in a higher percentage of patients being eligible for KD (81.4%) and achieved the highest P10 (32%–34%) and P30 (87%–88%) across all mGFR methods. When patients were deemed eligible for donation by any eGFR formula, 95% retained this status on reassessment with mGFR. Conversely, when an eGFR formula classified a patient as ineligible, this was revised to be eligible in about 90% of cases on reassessment with mGFR, with a higher reclassification rate observed when the IoCl was used instead of CrCl. Conclusions. The CKD-EPI 2021 performs best for screening potential KD. If a KD is deemed ineligible by CKD-EPI 2021, there is a high likelihood that they will be reclassified as eligible when assessed with mGFR. This study strongly supports using mGFR in donor evaluations, especially when the eGFR does not meet the criteria to ensure equity of access to being a living donor.

The increasing prevalence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD) has led to a growing demand for kidney transplantation (KTx). Identifying risk factors that enable improved allograft survival through novel therapeutic agents, advanced biomarkers, and artificial intelligence (AI)-driven data integration are critical to addressing this challenge. Drugs, such as SGLT2 inhibitors and finerenone, have demonstrated improved outcomes in patients but lack comprehensive long-term evidence in KTx patients. The use of biomarkers, including circulating cytokines and transcriptomics, coupled with AI, could enhance early detection and personalized treatment strategies. Addressing patient self-management and addressing health access disparities may be more achievable using technologies used at home rather than traditional models of healthcare and thus lead to increased transplant success, both in terms of transplantation rates and allograft longevity.