Your browser doesn't support javascript.
loading
Internet of things-based approach for glycemic control in people with type 2 diabetes: A randomized controlled trial.
Bouchi, Ryotaro; Izumi, Kazuo; Ishizuka, Naoki; Uemura, Yukari; Ohtsu, Hiroshi; Miyo, Kengo; Tanaka, Shigeho; Satoh-Asahara, Noriko; Hara, Kazuo; Odawara, Masato; Kusunoki, Yoshiki; Koyama, Hidenori; Onoue, Takeshi; Arima, Hiroshi; Tsushita, Kazuyo; Watada, Hirotaka; Kadowaki, Takashi; Ueki, Kohjiro.
Afiliación
  • Bouchi R; Diabetes and Metabolism Information Center, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan.
  • Izumi K; Department of Diabetes and Endocrinology and Metabolism, Center Hospital, National Center for Global Health and Medicine, Tokyo, Japan.
  • Ishizuka N; Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan.
  • Uemura Y; Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan.
  • Ohtsu H; Center for Digital Transformation of Healthcare, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Miyo K; Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan.
  • Tanaka S; Clinical Research and Trial Center, Juntendo University, Tokyo, Japan.
  • Satoh-Asahara N; Center for Medical Informatics Intelligence, National Center for Global Health and Medicine, Tokyo, Japan.
  • Hara K; Faculty of Nutrition, Kagawa Nutrition University, Saitama, Japan.
  • Odawara M; Department of Nutrition and Metabolism, National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan.
  • Kusunoki Y; Department of Endocrinology, Metabolism and Hypertension Research, Clinical Research Institute, National Hospital Organization Kyoto Medical Center, Kyoto, Japan.
  • Koyama H; Department of Endocrinology and Metabolism, Saitama Medical Center, Jichi Medical University, Saitama, Japan.
  • Onoue T; Department of Diabetology, Metabolism and Endocrinology, Tokyo Medical University Hospital, Tokyo, Japan.
  • Arima H; Department of Diabetes, Endocrinology and Clinical Immunology, School of Medicine, Hyogo Medical University, Hyogo, Japan.
  • Tsushita K; Department of Diabetes, Endocrinology and Clinical Immunology, School of Medicine, Hyogo Medical University, Hyogo, Japan.
  • Watada H; Departments of Endocrinology and Diabetes, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Kadowaki T; Departments of Endocrinology and Diabetes, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Ueki K; Faculty of Nutrition, Kagawa Nutrition University, Saitama, Japan.
J Diabetes Investig ; 2024 May 07.
Article en En | MEDLINE | ID: mdl-38712947
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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Diabetes Investig Año: 2024 Tipo del documento: Article País de afiliación: Japón

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: J Diabetes Investig Año: 2024 Tipo del documento: Article País de afiliación: Japón
...