Early Detection and Monitoring of Nephrolithiasis: The Potential of Electrochemical Sensors

Abstract

Nephrolithiasis (kidney stone disease) continues to pose a significant global health challenge, affecting millions of individuals and placing substantial economic pressures on healthcare systems. Traditional diagnostic methods-such as computed tomography (CT), ultrasound, and basic urinalysis-are often limited by issues including radiation exposure, lower sensitivity in detecting small stones, operator dependency, and the inability to provide real-time analysis. In response, electrochemical sensors have emerged as innovative and powerful tools capable of the rapid, sensitive, and specific detection of key biomarkers associated with nephrolithiasis. This review highlights the advances in electrochemical approaches for monitoring oxalate and uric acid, the two primary metabolites implicated in kidney stone formation. We discuss the principles of electrode design and fabrication, including nanomaterial integration, 3D printing, and molecular imprinting, which have markedly improved detection limits and selectivity. Furthermore, we critically evaluate the practical challenges-such as sensor fouling, reproducibility, and stability in complex biological matrices-that currently impede widespread clinical implementation. The potentials for miniaturization and point-of-care integration are emphasized, with an eye toward continuous or home-based monitoring systems that can offer personalized insights into risk of stone formation and progression. By consolidating recent findings and exploring future trends in multi-analyte detection and wearable diagnostics, this review provides a roadmap for translating electrochemical sensors from research laboratories to routine clinical practice, ultimately aiming to enhance early intervention and improve patient outcomes in nephrolithiasis.

Keywords: electrochemical sensors; nephrolithiasis; oxalate; point-of-care testing; uric acid.

Figure 2

The chemical structures of the three types of stones, as well as their images from top to bottom are calcium oxalate [72], uric acid [72], and cystine stones [73]. Reproduced with permission.

Figure 1

Common techniques for detecting kidney stones.

Figure 3

(A) Schematic diagram of the metabolism of ascorbic acid to oxalate in humans [76]. (B) Schematic diagram of the mechanism of oxalate stone formation [53].

Figure 4

(A) Purine metabolism and oxidative stress [85]. Copyright 2021, from Elsevier. (B) The formation of uric acid stones.

Figure 5

(A) The corresponding schematic representation of PtNPs loaded on the surface of WC NTs [100]. (B) The HR-TEM images of Gr with Ag NPs [101]. (C) Images of the lollipop AMEs printed from the bespoke graphite/CB and the CB/only filament [102]. (D) DPV measurements for Pd-nc/rGO-modified GCE and Pd-nico/rGO-modified GCE [106]. (E) Comparison of measurements performed using DPV with respect to expected HPLC results. Inset: the statistical error, mean, and standard deviation for each technique [107]. (F) Schematic diagram of a wireless-USB-like electrochemical platform for individual electrochemical sensing in microdroplets [108].

Figure 6

(A) Schematic diagram of the growth of PolyPPD and the incorporation of nanoparticles within the polymer matrix [132]. (B) A schematic diagram showcasing the development of an iron (Fe)-nanostructured (FeNS) sensor for the electrochemical detection of UA and the mechanism of the electrooxidation process of uric acid [133]. (C) SEM images of synthetic BMZIF and its resultant CNCo [134]. (D) Photographs of FECTs integrated into the fabric and the UA sensor during testing [135]. (E) Portable-device fabrication [136].