Continuous Glucose Monitoring Predicts Progression to Diabetes in Autoantibody Positive Children.


Journal

The Journal of clinical endocrinology and metabolism
ISSN: 1945-7197
Titre abrégé: J Clin Endocrinol Metab
Pays: United States
ID NLM: 0375362

Informations de publication

Date de publication:
01 08 2019
Historique:
received: 10 10 2018
accepted: 01 03 2019
pmc-release: 07 03 2020
pubmed: 8 3 2019
medline: 26 5 2020
entrez: 8 3 2019
Statut: ppublish

Résumé

Accurate measures are needed for the prediction and diagnosis of type 1 diabetes (T1D) in at-risk persons. The purpose of this study was to explore the value of continuous glucose monitoring (CGM) in predicting T1D onset. The Diabetes Autoimmunity Study in the Young (DAISY) prospectively follows children at increased risk for development of islet autoantibodies (islet autoantibody positive; Ab+) and T1D. We analyzed 23 Ab+ participants with available longitudinal CGM data. CGM metrics as glycemic predictors of progression to T1D. Of 23 Ab+ participants with a baseline CGM, 8 progressed to diabetes at a median age of 13.8 years during a median follow-up of 17.7 years (interquartile range, 14.6 to 22.0 years). Compared with nonprogressors, participants who progressed to diabetes had significantly increased baseline glycemic variability (SD, 29 vs 21 mg/dL; P = 0.047), daytime sensor average (122 vs 106 mg/dL; P = 0.02), and daytime sensor area under the curve (AUC, 470,370 vs 415,465; P = 0.047). They spent 24% of time at >140 mg/dL and 12% at >160 mg/dL compared with, respectively, 8% and 3% for nonprogressors (both P = 0.005). A receiver-operating characteristic curve analysis showed an AUC of 0.85 for percentage of time spent at >140 or 160 mg/dL. The cutoff of 18% time spent at >140 mg/dL had 75% sensitivity, 100% specificity, and a 100% positive predictive value for diabetes prediction, although these values could change because some nonprogressors may develop diabetes with longer follow-up. Eighteen percent or greater CGM time spent at >140 mg/dL predicts progression to diabetes in Ab+ children.

Identifiants

pubmed: 30844073
pii: 5370167
doi: 10.1210/jc.2018-02196
pmc: PMC6589073
doi:

Substances chimiques

Autoantibodies 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3337-3344

Subventions

Organisme : NIDDK NIH HHS
ID : P30 DK048520
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK032083
Pays : United States
Organisme : NIDDK NIH HHS
ID : R37 DK032493
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK032493
Pays : United States
Organisme : NIDDK NIH HHS
ID : K12 DK094712
Pays : United States
Organisme : NIDDK NIH HHS
ID : R37 DK032083
Pays : United States

Informations de copyright

Copyright © 2019 Endocrine Society.

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Auteurs

Andrea K Steck (AK)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Fran Dong (F)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Iman Taki (I)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Michelle Hoffman (M)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Kimber Simmons (K)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Brigitte I Frohnert (BI)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

Marian J Rewers (MJ)

Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, Colorado.

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Classifications MeSH