Arvind Veluvali, Ashkan Dehghani Zahedani, Amir Hosseinian, Nima Aghaeepour, Tracey McLaughlin, Mark Woodward, Alex DiTullio, Noosheen Hashemi, Michael P. Snyder
{"title":"Impact of digital health interventions on glycemic control and weight management","authors":"Arvind Veluvali, Ashkan Dehghani Zahedani, Amir Hosseinian, Nima Aghaeepour, Tracey McLaughlin, Mark Woodward, Alex DiTullio, Noosheen Hashemi, Michael P. Snyder","doi":"10.1038/s41746-025-01430-7","DOIUrl":null,"url":null,"abstract":"<p>This retrospective cohort study evaluates the impact of an AI-supported continuous glucose monitoring (CGM) mobile app (“January V2”) on glycemic control and weight management in 944 users, including healthy individuals and those with prediabetes or type 2 diabetes (T2D). The app, leveraging AI to personalize feedback, tracked users’ food intake, activity, and glucose responses over 14 days. Significant improvements in time in range (TIR) were observed, particularly in users with lower baseline TIR. Healthy users’ TIR increased from 74.7% to 85.5% (<i>p</i> < 0.0001), while T2D users’ TIR improved from 49.7% to 57.4% (<i>p</i> < 0.0004). Higher app engagement correlated with greater TIR improvements. Users also experienced an average weight reduction of 3.3 lbs over 33 days. These findings suggest that AI-enhanced digital health interventions can improve glycemic control and promote weight loss, particularly when users are actively engaged.</p>","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":"30 1","pages":""},"PeriodicalIF":12.4000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Digital Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41746-025-01430-7","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
This retrospective cohort study evaluates the impact of an AI-supported continuous glucose monitoring (CGM) mobile app (“January V2”) on glycemic control and weight management in 944 users, including healthy individuals and those with prediabetes or type 2 diabetes (T2D). The app, leveraging AI to personalize feedback, tracked users’ food intake, activity, and glucose responses over 14 days. Significant improvements in time in range (TIR) were observed, particularly in users with lower baseline TIR. Healthy users’ TIR increased from 74.7% to 85.5% (p < 0.0001), while T2D users’ TIR improved from 49.7% to 57.4% (p < 0.0004). Higher app engagement correlated with greater TIR improvements. Users also experienced an average weight reduction of 3.3 lbs over 33 days. These findings suggest that AI-enhanced digital health interventions can improve glycemic control and promote weight loss, particularly when users are actively engaged.
期刊介绍:
npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics.
The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.