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Analytical Challenges in Diabetes Management: Towards Glycated Albumin Point-of-Care Detection. | LitMetric

Analytical Challenges in Diabetes Management: Towards Glycated Albumin Point-of-Care Detection.

Biosensors (Basel)

Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy.

Published: August 2022

AI Article Synopsis

Article Abstract

Diabetes mellitus is a worldwide-spread chronic metabolic disease that occurs when the pancreas fails to produce enough insulin levels or when the body fails to effectively use the secreted pancreatic insulin, eventually resulting in hyperglycemia. Systematic glycemic control is the only procedure at our disposal to prevent diabetes long-term complications such as cardiovascular disorders, kidney diseases, nephropathy, neuropathy, and retinopathy. Glycated albumin (GA) has recently gained more and more attention as a control biomarker thanks to its shorter lifespan and wider reliability compared to glycated hemoglobin (HbA1c), currently the "gold standard" for diabetes screening and monitoring in clinics. Various techniques such as ion exchange, liquid or affinity-based chromatography and immunoassay can be employed to accurately measure GA levels in serum samples; nevertheless, due to the cost of the lab equipment and complexity of the procedures, these methods are not commonly available at clinical sites and are not suitable to home monitoring. The present review describes the most up-to-date advances in the field of glycemic control biomarkers, exploring in particular the GA with a special focus on the recent experimental analysis techniques, using enzymatic and affinity methods. Finally, analysis steps and fundamental reading technologies are integrated into a processing pipeline, paving the way for future point-of-care testing (POCT). In this view, we highlight how this setup might be employed outside a laboratory environment to reduce the time from measurement to clinical decision, and to provide diabetic patients with a brand-new set of tools for glycemic self-monitoring.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9496022PMC
http://dx.doi.org/10.3390/bios12090687DOI Listing

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