Emerging Technology and its Use in the Management of Adults with Diabetes: Continuous Glucose Monitoring Technology (Research Proposal Sample)

Emerging Technology and its Use in the Management of Adults with Diabetes: Continuous Glucose Monitoring Technology Author's Name Institutional Affiliation Course Number Course Name Instructor's Name Due Date Introduction An endocrinologist's aptitude to obtain blood glucose measurements to adjust the management therapies forms the backbone of diabetes treatment (Almarshad, 2017). It is crucial to attain standard glucose targets to prevent hypoglycemia amongst patients (Ergin & Zaybak, 2021). Similarly, the Diabetes Control and Complication Trial (DCCT) endorsed that glycosylated hemoglobin (HbA1c) of not more than 7% in diabetes therapeutics was suitable for decreasing the patient's risk of microvascular and macrovascular complications (Deng et al., 2021). Thus, stable glucagon formulations might be essential in developing a dual-hormone closed-loop system to enhance glycaemic regulation in the continuous glucose monitoring process. Problem Statement Over the last two decades, diabetes care and research units have witnessed tremendous advancements and the development of new therapies and technologies for managing type 1 and 2 diabetes (Reddy & Oliver, 2021). However, to achieve the recommended glycemic targets, the endocrinologist must monitor the patient's blood glucose level multiple times daily due to several physiologic factors, including stress, illness, or physical activity. The main challenge facing diabetes management is how to optimize the available management therapies to guarantee stable blood pressure and adequate lipid and glycemic control to decrease the prevailing complications (Joseph, 2020). Computing the patient's carbohydrate intake manually to estimate their appropriate meal coverage could be challenging because it might include administering several insulin doses which could have varying effects on their health outcomes. Therefore, improving the accuracy of continuous glucose monitoring and self-monitoring for diabetes through innovations would enhance automated insulin delivery systems to help adjust diabetes management therapies based on glucose input. Purpose of the study This review aims to establish how emerging technologies in continuous glucose monitoring can be used to achieve the recommended glycemic targets by decreasing the disease burden. It explores how the development of stable glucagon formulations and new drugs promise improved postprandial glycemia outcomes among patients. Methods Search and Retrieval Strategy Concurring with Burns and Grove (2010), data analysis for this study includes systematic reviews. Underpinned by the PICO framework, the study's weighted problem comprised establishing how emerging technologies in continuous glucose monitoring could be used to achieve the recommended glycemic targets to decrease the disease burden of diabetes. Importantly, PubMed, discover, and Medline was considered credible search engines for data search and retrieval. The search process carried out on 2nd September 2022 employed the following key terms in PubMed, Medline, and Discover to find relevant information: Artificial pancreas, Automated insulin delivery, Continuous glucose monitoring technology, Ultrarapid-acting insulin, Dual-hormone closed-loop system, and glucagon formulation. Inclusion and exclusion Using the Prisma-P flowchart, as shown in the figure below, duplicates were eliminated grounded on abstract and full-text screening for inclusion and exclusion. Thus, guided by the CASP tool criteria of 2019, only peer-reviewed articles on emerging technologies in continuous glucose monitoring and stable glucagon formulations were included in this research for analysis. Importantly, the PICO principle enabled the researcher to filter the most credible articles to guarantee that only studies promising valuable outcomes for the study were filtered from 72 records to 9 credible articles. 31813509525Discover (n = 11)0Discover (n = 11)right12700Scopus (n = 9)00Scopus (n = 9)183832513334Medline (n = 26)00Medline (n = 26)70485013334PubMed (n =27)00PubMed (n =27)2495550213741041243252499360Excluded articles (excluded records after screening = 48)00Excluded articles (excluded records after screening = 48)11906262527935Inclusion and exclusion criteria applied 00Inclusion and exclusion criteria applied left4404042Eligibility 00Eligibility left2651442Screening 00Screening left802321Identification 00Identification 26003252114553743325230505 4229100628651447800110490 1838325247650Screened articles (Non-duplicate records =72)00Screened articles (Non-duplicate records =72) 298132593345 187642581915 120015072390Articles retrieved after screening(n= 24)00Articles retrieved after screening(n= 24) 4655185208280data extraction (Excluded records= 3)00data extra...