852-P: Is Real-Time CGM Superior to Flash Glucose Monitoring? Results of the Type 1 Diabetes CORRIDA Randomized Control Trial
Abstract
Background: The trial aim was to compare the efficacy of real-time and intermittently-scanned continuous glucose monitoring (rtCGM and isCGM, respectively) in maintaining optimal glycemic control. Methods: In this randomized study, adults with T1D and normal hypoglycemia awareness (GOLD score <4) used rtCGM (Guardian Connect Mobile) or isCGM (Freestyle Libre) during 4 days of physical activity (sport period) and in the subsequent 4 weeks (home period). Main endpoints were time in hypoglycemia (<3.9 mmol/l [<70 mg/dl]) and time in range (3.9-10.0 mmol/l [70-180 mg/dl]). To check for bias between the different sensors used by the rtCGM and isCGM systems, the isCGM group wore an additional blinded Enlite sensor (iPro2) for 6 days. Results: Sixty adults with T1D (age 38±13 years, HbA1c 7.8±1.1% [62±12 mmol/mol]) were randomized to rtCGM (n=30) or isCGM (n=30). All participants completed the study. Time in hypoglycemia (<3.9 mmol/l) was lower among rtCGM participants in the sport period (6.8±5.5% vs. 11.4±8.6%, respectively; p=0.018) and the home period (5.3±2.5% vs. 7.3±4.4%, respectively; p=0.035). Hypoglycemia differences were significant and most notable during the night. rtCGM participants spent more time in range than isCGM participants throughout both the sport (78.5±10.2% vs. 69.7±16%, respectively; p=0.0149) and home (75.6±9.7% vs. 67.4±17.8%, respectively; p=0.0339) periods. The results were robust to the insignificant bias between rtCGM and isCGM sensors that blinded CG…
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The Guardian Connect System is an AI system based on CGM, has an accompanying smartphone application, and was certified by the FDA in 2018.
“The Guardian Connect System (manufactured by Medtronic) is an example of an AI system with this functionality. This system is based on CGM, has an accompanying smartphone application,144 and was certified by the FDA in 2018.”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [144]
Cited by
Sorted by citations
Artificial intelligence in diabetes management: Advancements, opportunities, and challenges
Guan, Z., Li, H., Liu, R., Cai, C., Liu, Y., Li, J., Wang, X., Huang, S., Wu, L., Liu, D., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101213 · Cited by 287 · see citing works
- Authors
- SOUPAL, J., HÁSKOVÁ, A., GRUNBERGER, G., PETRUZELKOVA, L., PARKIN, C., SKRHA, J., RADOVNICKÁ, L., HOROVA, E., & PRAZNY, M.
- Affiliations
- Prague, Czech Republic, Bloomfield Hills, MI, Boulder City, NV, Ústí nad Labem, Czech Republic, Praha, Czech Republic
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2020-06-01
- Volume
- 69
- Issue
- Supplement_1
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W3034238749
- Cited by
- 0
- References
- 0
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- type 1 diabetes, real-time continuous glucose monitoring, flash glucose monitoring, hypoglycemia prevention, time in range, glycemic control, physical activity, sensor bias, adults with type 1 diabetes, HbA1c, hypoglycemia awareness
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review