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What difference does sleep make? Continuous glucose monitoring metrics during fixed-overnight time versus sleep periods among older adults with type 1 diabetes.

Steven TrawleyErin KubilayPeter G ColmanMelissa H LeeDavid N O'NealVijaya SundararajanSara VogrinSybil A McAuley
Published in: Journal of sleep research (2023)
Hypoglycaemia during sleep is a common and clinically important issue for people living with insulin-treated diabetes. Continuous glucose monitoring devices can help to identify nocturnal hypoglycaemia and inform treatment strategies. However, sleep is generally inferred, with diabetes researchers and physicians using a fixed-overnight period as a proxy for sleep-wake status when analysing and interpretating continuous glucose monitoring data. No study to date has validated such an approach with established sleep measures. Continuous glucose monitoring and research-grade actigraphy devices were worn and sleep diaries completed for 2 weeks by 28 older adults (mean age 67 years [SD 5]; 17 (59%) women) with type 1 diabetes. Using continuous glucose monitoring data from a total of 356 nights, fixed-overnight (using the recommended period of 00:00 hours-06:00 hours) and objectively-measured sleep periods were compared. The fixed-overnight period approach missed a median 57 min per night (interquartile range: 49-64) of sleep for each participant, including five continuous glucose monitoring-detected hypoglycaemia episodes during objectively-measured sleep. Twenty-seven participants (96%) had at least 1 night with continuous glucose monitoring time-in-range and time-above-range discrepancies both ≥ 10 percentage points, a clinically significant discrepancy. The utility of fixed-overnight time continuous glucose monitoring as a proxy for sleep-awake continuous glucose monitoring is inadequate as it consistently excludes actual sleep time, obscures glycaemic patterns, and misses sensor hypoglycaemia episodes during sleep. The use of validated measures of sleep to aid interpretation of continuous glucose monitoring data is encouraged.
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