Diabetes: a review of its pathophysiology, and advanced methods of mitigation

Abstract

Diabetes mellitus (DM) is a long-lasting metabolic non-communicable disease often characterized by an increase in the level of glucose in the blood or hyperglycemia. Approximately, 415 million people between the ages of 20 and 79 years had DM in 2015 and this figure will rise by 200 million by 2040. In a study conducted by CARRS, it’s been found that in Delhi the prevalence of diabetes is around 27% and for prediabetic cases, it is more than 46%. The disease DM can be both short-term and long-term and is often associated with one or more diseases like cardiovascular disease, liver disorder, or kidney malfunction. Early identification of diabetes may help avoid catastrophic repercussions because untreated DM can result in serious complications. Diabetes’ primary symptoms are persistently high blood glucose levels, frequent urination, increased thirst, and increased hunger. Therefore, DM is classified into four major categories, namely, Type 1, Type 2, Gestational diabetes, and secondary diabetes. There are various oral and injectable formulations available in the market like insulin, biguanides, sulphonylureas, etc. for the treatment of DM. Recent attention can be given to the various nano approaches undertaken for the treatment, diagnosis, and management of diabetes mellitus. Various nanoparticles like Gold Nanoparticles, carbon nanomaterials, and metallic nanoparticles are some of the approaches mentioned in this review. Besides nanotechnology, artificial intelligence (AI) has also found its application in diabetes care. AI can be used for screening the disease, helping in decision-making, predictive population-level risk stratification, and patient self-management tools. Early detection and diagnosis of diabetes also help the patient avoid expensive treatments later in their life with the help of IoT (internet of medical things) and machine learning models. These tools will help healthcare physicians to predict the disease early. Therefore, the Nano drug delivery system along with AI tools holds a very bright future in diabetes care.

Keywords:

• Diabetes
• artificial intelligence
• hyperglycemia
• nanoparticles

Transparency

Declaration of funding

This review is not funded.

Declaration of financial/other relationships

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgements

The author would like to acknowledge the important contributions of NS, SA, and SV to this manuscript. The authors acknowledge to the Director, Amity Institute of Pharmacy, Amity University, Noida for his constant encouragement, and support.