New Methods to Monitor Kidney Function and Damage

Abstract

With the ongoing increase in both the prevalence and disease burden of chronic kidney disease (CKD), it remains crucial to develop precise monitoring tools for assessing kidney function and injury. Accurate monitoring may aid clinicians in diagnosing kidney disease, estimating prognosis, guiding the treatment of kidney disease, and dosing of renally excreted drugs. Despite advancements in monitoring kidney function and injury, the implementation of novel techniques in clinical practice remains limited. Currently, the primary diagnostic tools for detecting and monitoring acute and chronic kidney disease are creatinine-based equations for estimating glomerular filtration rate (eGFR), developed in 1999 with updates in 2009 and 2021, and basic urinalysis, dating back to the 19th century. While these methods are cost-effective and user-friendly, they lack the necessary sensitivity to timely diagnose kidney disease or accurately track its progression. Moreover, using the same diagnostic tests for all patients may not be suitable due to individual patient and disease-specific factors. With the development of new technologies and the increased integration of digital healthcare, the incorporation of innovative diagnostic methods could become feasible without confusing or adding additional burden to physicians. This thesis explored approaches for monitoring kidney function and injury as a complement to existing methods in patient care and in pre-clinical disease models.