Elizabeth Hegedus1, Sarah-Jeanne Salvy2, Choo Phei Wee3, Monica Naguib1, Jennifer K Raymond1, D Steven Fox4, Alaina P Vidmar5. 1. Children's Hospital Los Angeles and Keck School of Medicine of USC, Center for Endocrinology, Diabetes and Metabolism, Los Angeles, CA, United States. 2. Cancer Research Center on Health Equity, Cedars-Sinai Medical Center, West Hollywood, CA, United States. 3. Southern California Clinical and Translational Science Institute, Department of Preventive Medicine, Keck School of Medicine, Los Angeles, CA, United States. 4. Department of Pharmaceutical and Health Economics, School of Pharmacy of the University of Southern California, Los Angeles, CA, United States. 5. Children's Hospital Los Angeles and Keck School of Medicine of USC, Center for Endocrinology, Diabetes and Metabolism, Los Angeles, CA, United States. Electronic address: avidmar@chla.usc.edu.
Abstract
BACKGROUND: This scoping review provides a timely synthesis of the use of continuous glucose monitoring in obesity research with considerations to adherence to continuous glucose monitor devices and metrics most frequently reported. METHODS: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Eligible studies (n = 31) evaluated continuous glucose monitor use in research on participants, of all ages, with overweight or obesity. RESULTS: Reviewed studies varied in duration from one to 84 days (mean: 8.74 d, SD 15.2, range 1-84 d) with 889 participants total (range: 11-118 participants). Across all studies, the mean percent continuous glucose monitor wear time (actual/intended wear time in days) was 92% (numerator - mean: 266.1 d, SD: 452, range: 9-1596 d/denominator - mean: 271.6 d, SD: 451.5, range: 9-1596 d). Continuous glucose monitoring was utilized to provide biofeedback (n = 2, 6%), monitor dietary adherence (n = 2, 6%), and assess glycemic variability (n = 29, 93%). The most common variability metrics reported were standard deviation (n = 19, 62%), area under the curve (n = 12, 39%), and glycemic range (n = 12, 39%). CONCLUSIONS: Available evidence suggests that continuous glucose monitoring is a well-tolerated and versatile tool for obesity research in pediatric and adult patients. Future investigation is needed to substantiate the feasibility and utility of continuous glucose monitors in obesity research and maximize comparability across studies.
BACKGROUND: This scoping review provides a timely synthesis of the use of continuous glucose monitoring in obesity research with considerations to adherence to continuous glucose monitor devices and metrics most frequently reported. METHODS: This scoping review was conducted adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist. Eligible studies (n = 31) evaluated continuous glucose monitor use in research on participants, of all ages, with overweight or obesity. RESULTS: Reviewed studies varied in duration from one to 84 days (mean: 8.74 d, SD 15.2, range 1-84 d) with 889 participants total (range: 11-118 participants). Across all studies, the mean percent continuous glucose monitor wear time (actual/intended wear time in days) was 92% (numerator - mean: 266.1 d, SD: 452, range: 9-1596 d/denominator - mean: 271.6 d, SD: 451.5, range: 9-1596 d). Continuous glucose monitoring was utilized to provide biofeedback (n = 2, 6%), monitor dietary adherence (n = 2, 6%), and assess glycemic variability (n = 29, 93%). The most common variability metrics reported were standard deviation (n = 19, 62%), area under the curve (n = 12, 39%), and glycemic range (n = 12, 39%). CONCLUSIONS: Available evidence suggests that continuous glucose monitoring is a well-tolerated and versatile tool for obesity research in pediatric and adult patients. Future investigation is needed to substantiate the feasibility and utility of continuous glucose monitors in obesity research and maximize comparability across studies.
Authors: Jason A Mendoza; K Scott Baker; Megan A Moreno; Kathryn Whitlock; Mark Abbey-Lambertz; Alan Waite; Trina Colburn; Eric J Chow Journal: Pediatr Blood Cancer Date: 2017-06-15 Impact factor: 3.167
Authors: R E Climie; M S Grace; R L Larsen; P C Dempsey; J Oberoi; N D Cohen; N Owen; B A Kingwell; D W Dunstan Journal: Nutr Metab Cardiovasc Dis Date: 2018-05-26 Impact factor: 4.222
Authors: Jonathan P Little; Mary E Jung; Amy E Wright; Wendi Wright; Ralph J F Manders Journal: Appl Physiol Nutr Metab Date: 2014-02-18 Impact factor: 2.665
Authors: Nathan C Winn; Ryan Pettit-Mee; Lauren K Walsh; Robert M Restaino; Sean T Ready; Jaume Padilla; Jill A Kanaley Journal: Med Sci Sports Exerc Date: 2019-05 Impact factor: 5.411
Authors: Christine L Chan; Laura Pyle; Lindsey Newnes; Kristen J Nadeau; Philip S Zeitler; Megan M Kelsey Journal: J Clin Endocrinol Metab Date: 2014-12-22 Impact factor: 5.958
Authors: Nejla Ghane; Miranda M Broadney; Elisabeth K Davis; Robert W Trenschel; Shavonne M Collins; Sheila M Brady; Jack A Yanovski Journal: Pediatr Diabetes Date: 2019-08-29 Impact factor: 4.866
Authors: D Spruijt-Metz; C K F Wen; G O'Reilly; M Li; S Lee; B A Emken; U Mitra; M Annavaram; G Ragusa; S Narayanan Journal: Curr Obes Rep Date: 2015-12
Authors: Evelyn B Parr; Brooke L Devlin; Karen H C Lim; Laura N Z Moresi; Claudia Geils; Leah Brennan; John A Hawley Journal: Nutrients Date: 2020-10-22 Impact factor: 5.717
Authors: Susan M Schembre; Michelle R Jospe; Erin D Giles; Dorothy D Sears; Yue Liao; Karen M Basen-Engquist; Cynthia A Thomson Journal: Nutrients Date: 2021-12-16 Impact factor: 5.717
Authors: Monica N Naguib; Elizabeth Hegedus; Jennifer K Raymond; Michael I Goran; Sarah-Jeanne Salvy; Choo Phei Wee; Ramon Durazo-Arvizu; Lilith Moss; Alaina P Vidmar Journal: Front Endocrinol (Lausanne) Date: 2022-02-25 Impact factor: 5.555