The Effect Of Using Modern Technology In Examining And Detecting Accumulated Sugar In The Blood
DOI:
https://doi.org/10.70082/ypn4kx09Keywords:
Diabetes mellitus, blood glucose monitoring, continuous glucose monitoring (CGM), non-invasive technology, biosensors, artificial intelligence, digital health.Abstract
Having been in a state of great prevalence, diabetes mellitus is ranked very high among chronic diseases in many parts of the world. Diabetic hyperglycemia has numerous dangers of cardiovascular, renal, and neurological complications. Of course, conventional means of glucose monitoring that include finger-prick tests and laboratory-based assays are invasive, inconvenient, and do not permit continuous monitoring, even though they remain accurate. In the wake of rapid technological development that occurred in recent history, we find a few methods like continuous glucose monitor (CGM), non-invasive biosensors, and digital health applications that ensure efficiency, precision, and compliance by patients in conducting examinations and detecting accumulated blood sugar. The present study offers a systematic review of recent literature and clinical trials centered on modern technological interventions in blood glucose monitoring, with data being collected from PubMed, Scopus, and Web of Science. The research papers studied were conducted in the last decade, comparing the use of traditional methods of diagnosis with more technologically advanced approaches: CGM, near-infrared spectroscopy, optical sensors, and the use of smartphones in diagnostic devices. Issues involved were accuracy, patient compliance, cost-effectiveness, and early detection of glycemic fluctuations.nThe findings suggested the CGM system could compensate for conventional techniques, capturing real-time fluctuations in blood sugar levels and preventing undetected hyperglycemia and hypoglycemia periods. Although further work is still needed to optimize methods, these non-invasive technologies have proven fairly accurate while generating minimal discomfort. Additionally, merging with AI and m-health platforms would strengthen the predictive ability of such systems that facilitate the early identification of abnormal glucose trends and eventually improve systems to better cater to the management of diabetes.nSuch technological developments herald a paradigm shift in glucose detection; patients now have continuous and non-invasive tracking, which encourages patient compliance, reduces complications, and skin-side-interventions. Cost constitutes a barrier, with these devices often underfunded or unavailable preemptively in low-resource settings. Lastly, the validation of any new device remains a challenge. Sometimes, old technology is better at glycated blood detection rather than a new one with forthcoming accuracy, convenience, and clinical utility. Further improvements in method design might bring a revolution in diabetes care while CGM and other digital health integrations provide huge benefits in the present. Subsequent steps should include large-scale validations, cost-reduction strategies, and integration into public health systems globally. into global public health frameworks.
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