Christine A March, Michelle Nanni, James Lutz, Madison Kavanaugh, Kwonho Jeong, Linda M Siminerio, Scott Rothenberger, Elizabeth Miller, Ingrid M Libman
{"title":"Comparisons of school-day glycemia in different settings for children with type 1 diabetes using continuous glucose monitoring.","authors":"Christine A March, Michelle Nanni, James Lutz, Madison Kavanaugh, Kwonho Jeong, Linda M Siminerio, Scott Rothenberger, Elizabeth Miller, Ingrid M Libman","doi":"10.1155/2023/8176606","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and non-school time.</p><p><strong>Methods: </strong>We conducted a retrospective analysis of CGM metrics in children 7-12 years (n=217, diabetes duration 3.5±2.5 years, hemoglobin A1c 7.5±0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school.</p><p><strong>Results: </strong>Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school.</p><p><strong>Conclusion: </strong>Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623999/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/2023/8176606","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/3/9 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Using continuous glucose monitoring (CGM), we examined patterns in glycemia during school hours for children with type 1 diabetes, exploring differences between school and non-school time.
Methods: We conducted a retrospective analysis of CGM metrics in children 7-12 years (n=217, diabetes duration 3.5±2.5 years, hemoglobin A1c 7.5±0.8%). Metrics were obtained for weekday school hours (8 AM to 3 PM) during four weeks in fall 2019. Two comparison settings included weekend (fall 2019) and weekday (spring 2020) data when children had transitioned to virtual school due to COVID-19. We used multilevel mixed models to examine factors associated with time in range (TIR) and compare glycemia between in-school, weekends, and virtual school.
Results: Though CGM metrics were clinically similar across settings, TIR was statistically higher, and time above range (TAR), mean glucose, and standard deviation (SD) lower, for weekends and virtual school (p<0.001). Hour and setting exhibited a significant interaction for several metrics (p<0.001). TIR in-school improved from a mean of 40.9% at the start of the school day to 58.0% later in school, with a corresponding decrease in TAR. TIR decreased on weekends (60.8 to 50.7%) and virtual school (62.2 to 47.8%) during the same interval. Mean glucose exhibited a similar pattern, though there was little change in SD. Younger age (p=0.006), lower hemoglobin A1c (p<0.001), and insulin pump use (p=0.02) were associated with higher TIR in-school.
Conclusion: Although TIR was higher for weekends and virtual school, glycemic metrics improve while in-school, possibly related to beneficial school day routines.