{"title":"Long-Term Patterns in Automated Insulin Delivery and Carbohydrate Announcement: A 24-Month Follow-Up.","authors":"Estelle Godard, Alfred Penfornis, Coralie Amadou","doi":"10.1177/15209156251362499","DOIUrl":null,"url":null,"abstract":"<p><p>We evaluated long-term (24 months) consistency in carbohydrate counting and meal announcements among Control-IQ users using two parameters: auto-bolus percentage (i.e., automatic correction boluses divided by total boluses) and daily carbohydrate announcement (DCA). In this single-center retrospective cohort study (October 2021-October 2024), we analyzed trends in auto-bolus percentage-alongside DCA and metabolic control-and its associations with age, sex, DCA, and time in range (TIR) using mixed-effects linear models. Among 2751 person-quarters (57% women, mean age 37 years), the mean auto-bolus percentage was 61% and increased by 0.4% per quarter (<i>P</i> < 0.001). DCA declined from 132 to 100 g/day, while TIR slightly decreased from 61% to 58%. Auto-bolus percentage was inversely associated with age, TIR, and DCA, with the latter association strengthening over time. The modest change in TIR suggests sustained effectiveness of automated insulin delivery despite decreasing carbohydrate reporting-likely reflecting adaptive user behavior.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes technology & therapeutics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15209156251362499","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
We evaluated long-term (24 months) consistency in carbohydrate counting and meal announcements among Control-IQ users using two parameters: auto-bolus percentage (i.e., automatic correction boluses divided by total boluses) and daily carbohydrate announcement (DCA). In this single-center retrospective cohort study (October 2021-October 2024), we analyzed trends in auto-bolus percentage-alongside DCA and metabolic control-and its associations with age, sex, DCA, and time in range (TIR) using mixed-effects linear models. Among 2751 person-quarters (57% women, mean age 37 years), the mean auto-bolus percentage was 61% and increased by 0.4% per quarter (P < 0.001). DCA declined from 132 to 100 g/day, while TIR slightly decreased from 61% to 58%. Auto-bolus percentage was inversely associated with age, TIR, and DCA, with the latter association strengthening over time. The modest change in TIR suggests sustained effectiveness of automated insulin delivery despite decreasing carbohydrate reporting-likely reflecting adaptive user behavior.
期刊介绍：
Diabetes Technology & Therapeutics is the only peer-reviewed journal providing healthcare professionals with information on new devices, drugs, drug delivery systems, and software for managing patients with diabetes. This leading international journal delivers practical information and comprehensive coverage of cutting-edge technologies and therapeutics in the field, and each issue highlights new pharmacological and device developments to optimize patient care.
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