Evaluation of a Prediction-Based Bedtime Intervention in Reducing Nocturnal Low Glucose in Adults With Type 1 Diabetes: The DailyDose Bedtime Smart Snack Crossover Study.

Abstract

Nocturnal hypoglycemia is challenging for individuals with type 1 diabetes, particularly those who are physically active or using multiple daily injections (MDIs). We hypothesized that adding bedtime decision support to usual care with continuous glucose monitoring (CGM)-augmented MDI therapy could reduce nocturnal hypoglycemia. We developed the DailyDose Smart Snack (DDSS) app, which features CGM and physical activity logging and delivers personalized bedtime snack recommendations to help prevent nocturnal hypoglycemia. Recommendations are based on the probability and timing of low-glucose events forecasted by an evidential neural network. We conducted a randomized crossover trial comparing DDSS with CGM-augmented MDI for 4 weeks each under free-living conditions to evaluate the feasibility and effect of DDSS in reducing nocturnal hypoglycemia. Twenty participants completed the study (mean ± SD age 39 ± 15 years; 10 women; HbA1c 7.1% ± 1.0% [54 ± 11 mmol/mol]). There was no difference between arms in the proportion of nights with low-glucose events <70 mg/dL lasting ≥10 min (control 26.0% ± 14.1% vs. DDSS 23.6% ± 15.6%; odds ratio [OR] 0.83; P = 0.207) or in overnight CGM metrics. A post hoc analysis showed that the proportion of nights with low-glucose events <54 mg/dL lasting ≥10 min was significantly reduced in the DDSS arm by 3.5% (11.9% ± 12.9% vs. 8.3% ± 8.8%; OR 0.64; P = 0.040). DDSS did not significantly reduce the proportion of nights with low-glucose events <70 mg/dL lasting ≥10 min but reduced nocturnal low glucose <54 mg/dL without compromising other glycemic metrics.