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Diabetes PHGKB

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Last Posted: Sep 24, 2023
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Cost effectiveness review of text messaging, smartphone application, and website interventions targeting T2DM or hypertension.
Ruben Willems et al. NPJ Digit Med 2023 8 (1) 150 (Posted Aug 21, 2023 8AM)

Digital health interventions have been shown to be clinically-effective for type 2 diabetes mellitus (T2DM) and hypertension prevention and treatment. This study synthesizes and compares the cost-effectiveness of text-messaging, smartphone application, and websites. We found that digital interventions are cost-effective without substantial differences between the different delivery modes. Future health economic studies should increase transparency, conduct sufficient sensitivity analyses, and appraise the ICUR more critically in light of a reasoned willingness-to-pay threshold.

An AI-Enhanced Electronic Health Record Could Boost Primary Care Productivity.
Jeffrey E Harris et al. JAMA 2023 8 (Posted Aug 08, 2023 8PM)

More than a few commentators have seriously inquired whether artificial intelligence (AI) could ultimately replace many clinicians. The far likelier prospect, however, is that the newly emerging technology will enhance clinical productivity. To be sure, AI-based pattern recognition software can already scan retinal photos for complications of diabetes, detect tuberculosis on chest x-rays, and evaluate screening mammograms. And some AI applications have been found to be comparable if not superior to human clinical judgment.

Are You Up to Date on Your Preventive Care?
CDC, July 2023 (Posted Aug 01, 2023 9AM)

Family health history is a record of the diseases and health conditions in your family. You and your family members share genes. You may also have behaviors in common, like what you do for physical activity and what you like to eat. You may live in the same area and come into contact with similar harmful things in the environment. Family history includes all of these factors, any of which can affect your health. If you have a family history of a chronic disease, like cancer, heart disease, diabetes, or osteoporosis, you’re more likely to get that disease yourself.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records.
Megan M Shuey et al. EBioMedicine 2023 7 104674 (Posted Jul 05, 2023 7AM)

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug–gene pairs. These drug–gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).


news Latest News and Publications
Who is most at risk of dying if infected with SARS-CoV-2? A mortality risk factor analysis using machine learning of patients with COVID-19 over time: a large population-based cohort study in Mexico. External Web Site Icon
Liao Lauren D, et al. BMJ open 2023 0 0. (9) e072436
Cost-effectiveness of genetic-based screening strategies for maturity-onset diabetes of the young. External Web Site Icon
Gábor Kovács et al. Per Med 2023
Feasibility and accuracy of the screening for diabetic retinopathy using a fundus camera and an artificial intelligence pre-evaluation application. External Web Site Icon
A Piatti et al. Acta Diabetol 2023
Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study. External Web Site Icon
Mehdi Amini et al. Sci Rep 2023 13(1) 14920
Predictive models of long COVID. External Web Site Icon
Antony Blessy, et al. EBioMedicine 2023 0 0. 104777
Comparative study on risk prediction model of type 2 diabetes based on machine learning theory: a cross-sectional study. External Web Site Icon
Shu Wang et al. BMJ Open 2023 13(8) e069018
Machine Learning Applied to Cholesterol-Lowering Pharmacotherapy: Proof-of-Concept in High-Risk Patients Treated in Primary Care. External Web Site Icon
Andrew J Krentz et al. Metab Syndr Relat Disord 2023
Using machine learning to detect sarcopenia from electronic health records. External Web Site Icon
Xiao Luo et al. Digit Health 2023 920552076231197098
Prognostic factors for the outcomes of COVID-19 patients infected with SARS-CoV-2 Omicron and Delta variants. External Web Site Icon
Gunadi, et al. BMC medical genomics 2023 0 0. (1) 205
Molecular and Clinical Epidemiology of SARS-CoV-2 Infection among Vaccinated and Unvaccinated Individuals in a Large Healthcare Organization from New Jersey. External Web Site Icon
Mediavilla José R, et al. Viruses 2023 0 0. (8)

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About Diabetes PHGKB

Diabetes PHGKB is an online, continuously updated, searchable database of published scientific literature, CDC and NIH resources, and other materials that address the translation of genomic and other precision health discoveries into improved health care and prevention related to diabetes...more

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Common Diabetes Related Topics

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Disclaimer: Articles listed in the Public Health Knowledge Base are selected by the CDC Office of Public Health Genomics to provide current awareness of the literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the update, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.

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