Literature review of Diabetes noninvasive screening tools for previously undiagnosed. Scoping review

Author:

Haile TesfayeORCID

Abstract

AbstractBackgroundDiabetes is a severe chronic disease that needs due attention. Worldwide distribution of the disease is increasing in alarming trend marked by its pandemic nature. Numerous people are disabled and dead due to the complexity of the disease and its management. A recent CDC report revealed that in the USA, 37.3 million people have Diabetes (11.3% of the US population). Ninety-six million people aged 18 years and older have prediabetes (38.0% of the adult US population). Worldwide, the number of people with Diabetes rose from 108 million in 1980 to 422 million in 2014. WHO on its sustainable development goal (SDG) report made clear the existing diabetic patient evaluation, intervention, and monitoring method does not adequately address the problem. Paradoxically, the ambitious goal of the American Diabetes Association is: “A Future Without Diabetes.”The current Diabetes screening method is invasive, provided that scarcity of resources and high cost of test kit makes it nonpractical to frequently checkup. We must proactively engage in its prevention by making screening cheap and easily accessible. So, this review is designed to answer the question: What is an available Diabetes noninvasive screening tool for undiagnosed?MethodThe relevant Article was searched from PubMed, MEDLINE, Embase, Web of Science, SCOPUS, and the CINHAL using a combination of the following key constructs: Diabetes screening, Diabetes noninvasive screening, Diabetes AND screening, Diabetes and (“noninvasive” or “non-invasive” or “non invasive”) and “screening tool,” Diabetes AND noninvasive AND screening AND Tool, “Diabetes noninvasive Screening Tool.” The selection process was conducted based on the PRISMA framework statement. Exclusion and inclusion criteria were applied to select the final relevant literature, after which 22 relevant studies were selected.ResultThe review included studies conducted from 2013 to 2023, 36% in 2019 and 2022. The included articles are from 13 countries. The data sources for the articles are surveys, databanks, random sampling, and opportunity sampling. A total of 24 key predictors were used to develop 22 types of tools. The researchers used the logistic regression (LR) method while developing most studies, and ML in a couple of them. The Authors described the Tool’s performance using the ROC curve, and the AUC is 0.65-0.93. The developed tool predictive power of the screening Prediabetes used Sensitivity, Specificity, PPV, NPV metrics and the result is encouraging.ConclusionDiabetes noninvasive Screening tests have the potential to identify prediabetes at an early stage and, thus, a more treatable disease that, as a result, saves lives. The developed tools had promising designate ability in pre-DM case findings, as shown by their ROC curve, AUC, sensitivity/specificity, and PPV/NPV. The Tool developed by these researchers looks promising for our goal of screening Diabetes by noninvasive method to answer this review research question using non-laboratory methods, which can be applied by common people regardless of the involvement of health professional skill. This review’s limitations are that the included article’s bias assessment was not performed, and non-English language articles were not included, so this could miss some pertinent tools. Finally, a systematic review, meta-analysis, and RCT on the Tool are recommended to identify any bias during the development of the Tool and possible generalizability of the best Tool for worldwide applicability.

Publisher

Cold Spring Harbor Laboratory

Reference28 articles.

1. Centers for Disease Control and Prevention. CDC National Diabetes Statistics Report 2020: Estimates of Diabetes and its Burden in the United States. https://www.cdc.gov/diabetes/data/statistics-report/index.html. Accessed 5/01/2023

2. World health Organization. World health statistics 2016: monitoring health for the SDGs sustainable development goals. World Health Organization; 2016 Jun 8. https://www.who.int/news-room/fact-sheets/detail/diabetes2World Health Organization. Accessed 11/12/2023.

3. Translation and performance of the Finnish Diabetes Risk Score for detecting undiagnosed diabetes and dysglycaemia in the Indonesian population

4. A Chinese risk score model for identifying postprandial hyperglycemia without oral glucose tolerance test

5. Screening for Type 2 Diabetes and Dysglycemia in Saudi Arabia: Development and Validation of Risk Scores

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