Effect of automated bio-behavioral feedback on the control of type 1 diabetes

Abstract

OBJECTIVE - To test the effect of an automated system providing real-time estimates of HbA 1c, glucose variability, and risk for hypoglycemia. RESEARCH DESIGNANDMETHODS - For 1 year, 120 adults with type 1 diabetes (69 female/51 male, age = 39.1 [14.3] years, duration of diabetes 20.3 [12.9] years, HbA 1c = 8.0 [1.5]), performed self-monitoring of blood glucose (SMBG) and received feedback at three increasingly complex levels, each continuing for 3 months: level 1 - routine SMBG; level 2 - adding estimated HbA 1c, hypoglycemia risk, and glucose variability; and level 3 - adding estimates of symptoms potentially related to hypoglycemia. The subjects were randomized to feedback sequences of either levels 1-2-3 or levels 2-3-1. HbA 1c, symptomatic hypoglycemia, and blood glucose awareness were evaluated at baseline and at the end of each level. RESULTS - For all subjects, HbA 1c was reduced from 8.0 to 7.6 from baseline to the end of study (P = 0.001). This effect was confined to subjects with baseline HbA 1c>8.0 (from9.3 to 8.5, P<0.001). Incidence of symptomatic moderate/severe hypoglycemia was reduced from 5.72 to 3.74 episodes/person/month (P = 0.019), more prominently for subjects with a history of severe hypoglycemia (from 7.20 to 4.00 episodes, P = 0.008) and for those who were hypoglycemia unaware (from 6.44 to 3.71 episodes, P = 0.045). The subjects' ratings of the feedback were positive, with up to 89% approval of the provided features. CONCLUSIONS - Feedback of SMBG data and summary SMBG-based measures resulted in improvement in average glycemic control and reduction in moderate/severe hypoglycemia. These effects were most prominent in subjects who were at highest risk at the baseline. © 2011 by the American Diabetes Association.