The Relationship Between the Percent Coefficient of Variation of Sensor Glucose Levels and the Risk of Severe Hypoglycemia or Non-Severe Hypoglycemia in Patients With Type 1 Diabetes: Post Hoc Analysis of the ISCHIA Study.

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM

Journal of Diabetes Science and Technology Pub Date : 2025-02-17 DOI:10.1177/19322968251318756

Takashi Murata, Munehide Matsuhisa, Akio Kuroda, Masao Toyoda, Yushi Hirota, Masahito Ogura, Shota Suzuki, Ken Kato, Atsuhito Tone, Yuka Matoba, Shu Meguro, Junnosuke Miura, Kunihiro Nishimura, Akira Shimada, Kiminori Hosoda, Naoki Sakane

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引用次数: 0

Abstract

Background: The relationship between the percent coefficient of variation (%CV) and the risk of severe hypoglycemia (SH) or non-severe hypoglycemia (NSH) in patients with type 1 diabetes (T1D) remains to be elucidated.

Materials and methods: The Effect of Intermittent-Scanning Continuous Glucose Monitoring to Glycemic Control Including Hypoglycemia and Quality of Life of Patients with Type 1 Diabetes Mellitus (ISCHIA) study was a crossover, randomized, controlled trial for hypoglycemia prevention in patients with T1D using multiple daily injections (MDIs). Blinded continuous glucose monitoring (CGM) data of 93 patients obtained during the Control period (84 days) were used for the post hoc analysis. The receiver operating characteristics (ROC) curves were analyzed to determine the discrimination thresholds of %CV corresponding to the low blood glucose index (LBGI) > 5 and LBGI ≥ 2.5, and the occurrence of SH.

Results: The %CV corresponding to LBGI > 5 and LBGI ≥ 2.5 was 42.2% and 37.0%, respectively. The episodes of SH were observed in three patients, and the %CV corresponding to the occurrence of SH was 40.7%.

Conclusions: The identification of the discrimination threshold of %CV associated with the risk of SH or NSH in patients with T1D is needed.

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来源期刊

Journal of Diabetes Science and Technology Medicine-Internal Medicine

CiteScore

7.50

自引率

12.00%

发文量

148

期刊介绍： The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.