Relationship between CGM-derived nocturnal hypoglycemia and subjective sleep quality in people with type 1 diabetes.

This pilot study explores the relationship between nocturnal hypoglycemia (NH) and subjective sleep quality in people with type 1 diabetes (T1D). Twenty-seven adults with T1D wore a Freestyle Libre Pro CGM and recorded subjective sleep quality daily, as assessed by a single Likert scale question. Frequency, duration, area under the curve (AUC) of NH (00:00-06:00) defined as sensor glucose below threshold (< 3.9 mmol/L; < 3 mmol/L) for ≥ 15 min, nocturnal mean glucose, Time in Range (3.9-10 mmol/L), and coefficient of variation were calculated. Twenty-seven adults, 18 (66.7%) women, with median (IQR) age of 27 (26, 32) years and HbA1c of 7.6 (7.1, 8.1) participated. Nights with NH < 3.9 mmol/L resulted in a lower (worse) sleep score than nights without NH [Mean (SD): 3.3 (1.2) vs 3.5 (1.0), p = 0.03). A higher frequency and longer duration but not AUC [adjusted OR (95% CI) 0.52 (0.38, 0.72), 0.961 (0.932, 0.991), 0.999 (0.998, 1.001) respectively)], of NH < 3.9 mmol/L, were associated with a lower sleep score. NH < 3.0 mmol/L metrics were not associated with sleep quality. Recurrent NH < 3.9 mmol/L, rather than prolonged NH < 3.0 mmol/L, seems associated with subjective sleep quality, implying that those with the highest burden of NH are likely unaware of it.

Association of Smartphone-Based Activity Tracking and Nocturnal Hypoglycemia in People With Type 1 Diabetes.

BACKGROUND: Nocturnal hypoglycemia (NH) remains a major burden for people with type 1 diabetes (T1D). Daytime physical activity (PA) increases the risk of NH. This pilot study tested whether cumulative daytime PA measured using a smartphone-based step tracker was associated with NH. METHODS: Adults with T1D for ≥ 5 years (y) on multiple daily insulin or continuous insulin infusion, not using continuous glucose monitoring and HbA1c 6 to 10% wore blinded Freestyle Libre Pro sensors and recorded total daily carbohydrate (TDC) and total daily dose (TDD) of insulin. During this time, daily step count (DSC) was tracked using the smartphone-based Fitbit MobileTrack application. Mixed effects logistic regression was used to estimate the effect of DSC on NH (sensor glucose <70, <54 mg/dl for ≥15 minutes), while adjusting for TDC and TDD of insulin, and treating participants as a random effect. RESULTS: Twenty-six adults, with 65.4% females, median age 27 years (interquartile range: 26-32) mean body mass index 23.9 kg/m2, median HbA1c 7.6% (7.1-8.1) and mean Gold Score 2.1 (standard deviation 1.0) formed the study population. The median DSC for the whole group was 2867 (1820-4807). There was a significant effect of DSC on NH episodes <70 mg/dl. (odds ratio 1.11 [95% CI: 1.01-1.23, P = .04]. There was no significant effect on NH <54 mg/dl. CONCLUSION: Daily PA measured by a smartphone-based step tracker was associated with the risk of NH in people with type 1 diabetes.