Internet of things-based approach for glycemic control in people with type 2 diabetes: A randomized controlled trial

Abstract

Aims

The utilization of long-term effect of internet of things (IoT) on glycemic control is controversial. This trial aimed to examine the effect of an IoT-based approach for type 2 diabetes.

Materials and Methods

This randomized controlled trial enrolled 1,159 adults aged 20–74 years with type 2 diabetes with a HbA1c of 6.0–8.9% (42–74 mmol/mol), who were using a smartphone on a daily basis were randomly assigned to either the IoT-based approach group (ITG) or the control group (CTG). The ITG were supervised to utilize an IoT automated system that demonstrates a summary of lifelogging data (weight, blood pressure, and physical activities) and provides feedback messages that promote behavioral changes in both diet and exercise. The primary end point was a HbA1c change over 52 weeks.

Results

Among the patients, 581 were assigned to the ITG and 578 were in the CTG. The changes in HbA1c from baseline to the final measurement at 52 weeks [mean (standard deviation)] were −0.000 (0.6225)% in ITG and − 0.006 (0.6449)% in CTG, respectively (P = 0.8766). In the per protocol set, including ITG using the IoT system almost daily and CTG, excluding those using the application almost daily, the difference in HbA1c from baseline to 52 weeks were −0.098 (0.579)% and 0.027 (0.571)%, respectively (P = 0.0201). We observed no significant difference in the adverse event profile between the groups.

Conclusions

The IoT-based approach did not reduce HbA1c in patients with type 2 diabetes. IoT-based intervention using data on the daily glycemic control and HbA1c level may be required to improve glycemic control.