Diabetes mellitus (DM) and chronic kidney disease (CKD) are common in middle aged and elderly individuals. DM may accelerate the aging process, and the age-related declines in the estimated Glomerular Filtration Rate (eGFR), can pose a challenge to diagnose diabetic kidney disease (DKD) using standard diagnostic criteria especially with absence of severe albuminuria among the elderly. In the presence of CKD and DM, elderly patients may need multidisciplinary care due to susceptibility to various health issues e.g., cognitive decline, auditory or visual impairment, various comorbidities, complex medical regimens, and increased sensitivity to medication adverse effects. As a result, it can be challenging to apply recent therapeutic advancements for the general population to the elderly. We review the evidence that the benefits from these newer therapies apply equally to elderly and non-elderly patients and propose a framework for the management of DKD by discussing the nonpharmacological measures and pharmacological management with renin angiotensin system inhibitors (RASi), Sodium Glucose Co-Transporter two inhibitors (SGLT2i), non-steroidal mineralocorticoids receptor antagonists (MRAs), and Glucagon Like Peptide 1 Receptor Agonists (GLP1-RAs).

In this study, we introduce a novel framework for the estimation of residual renal function (RRF), based on the population compartmental kinetic behavior of Beta 2 Microglobulin (B2M) and its dialytic removal. Using this model, we simulated a large cohort of patients with various levels of RRF receiving either conventional high-flux hemodialysis or on-line hemodiafiltration. These simulations were used to estimate a novel population kinetic (PK) equation for RRF (PK-RRF) that was validated in an external public dataset of real patients. We assessed the performance of the resulting equation(s) against their ability to estimate urea clearance using cross-validation. Our equations derived entirely from computer simulations and advanced statistical modeling, and had extremely high discrimination (AUC 0.808 – 0.909) when applied to a human dataset of measurements of RRF. A clearance-based equation that utilized pre and post dialysis B2M measurements, patient weight, treatment duration and ultrafiltration had higher discrimination than an equation previously derived in humans. Furthermore, the derived equations appeared to have higher clinical usefulness as assessed by Decision Curve Analysis, potentially supporting decisions that for individualizing dialysis frequency in patients with preserved RRF.