ABSTRACT
OBJECTIVE: We investigated the efficacy of an integrated digital health care platform with artificial intelligence (AI)-based dietary management in adults with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: In this 48-week, open-label, randomized, multicenter clinical trial, overweight or obese adults with T2D were randomly assigned to one of three groups in a 1:1:1 ratio: group A received routine diabetes care; group B used the digital integrated health care platform by themselves; and group C used the platform with feedback from medical staff and intermittently applied personal continuous glucose monitoring. The primary end point was the difference of change in HbA1c from baseline to 24 weeks between groups A and B, while secondary end points included changes in HbA1c from baseline to 48 weeks and changes in body weight during follow-up. RESULTS: A total of 294 participants were randomly assigned to group A (n = 99), B (n = 97), or C (n = 98). The decreases in HbA1c from baseline to 24 and 48 weeks in group B (-0.32 ± 0.58% to 24 weeks and -0.28 ± 0.56% to 48 weeks) and group C (-0.49 ± 0.57% to 24 weeks and -0.44 ± 0.62% to 48 weeks) were significantly larger than those in group A (-0.06 ± 0.61% to 24 weeks and 0.07 ± 0.78% to 48 weeks). Groups B and C exhibited greater weight loss than group A from baseline to 24 weeks, and group C demonstrated more weight loss than group A from baseline to week 48. CONCLUSIONS: Among adults with T2D, use of an integrated digital health care platform with AI-driven dietary management resulted in better glycemia and more weight loss.
Subject(s)
Diabetes Mellitus, Type 2 , Adult , Humans , Diabetes Mellitus, Type 2/therapy , Glycated Hemoglobin , Blood Glucose Self-Monitoring , Artificial Intelligence , Blood Glucose , Weight Loss , Delivery of Health CareABSTRACT
BACKGROUND: Despite the numerous healthcare smartphone applications for self-management of diabetes, patients often fail to use these applications consistently due to various limitations, including difficulty in inputting dietary information by text search and inconvenient and non-persistent self-glucose measurement by home glucometer. We plan to apply a digital integrated healthcare platform using an artificial intelligence (AI)-based dietary management solution and a continuous glucose monitoring system (CGMS) to overcome those limitations. Furthermore, medical staff will be performing monitoring and intervention to encourage continuous use of the program. The aim of this trial is to examine the efficacy of the program in patients with type 2 diabetes mellitus (T2DM) who have HbA1c 53-69 mmol/mol (7.0-8.5%) and body mass index (BMI) ≥ 23 mg/m2. METHODS: This is a 48-week, open-label, randomized, multicenter trial consisting of patients with type 2 diabetes. The patients will be randomly assigned to three groups: control group A will receive routine diabetes care; experimental group B will use the digital integrated healthcare platform by themselves without feedback; and experimental group C will use the digital integrated healthcare platform with continuous glucose monitoring and feedback from medical staff. There are five follow-up measures: baseline and post-intervention at weeks 12, 24, 36, and 48. The primary end point is change in HbA1c from baseline to six months after the intervention. DISCUSSION: This trial will verify the effectiveness of a digital integrated healthcare platform with an AI-driven dietary solution and a real-time CGMS in patients with T2DM. TRIAL REGISTRATION: Clinicaltrials.gov NCT04161170, registered on 08 November 2019. https://clinicaltrials.gov/ct2/show/NCT04161170?term=NCT04161170&draw=2&rank=1.
Subject(s)
Delivery of Health Care, Integrated , Diabetes Mellitus, Type 2 , Artificial Intelligence , Blood Glucose , Blood Glucose Self-Monitoring , Humans , Solutions , TimeABSTRACT
Introduction The aim of this study was to improve the quality of diabetes control and evaluate the efficacy of an Internet-based integrated healthcare system for diabetes management and safety. Methods We conducted a large-scale, multi-centre, randomized clinical trial involving 484 patients. Patients in the intervention group ( n = 244) were treated with the Internet-based system for six months, while the control group ( n = 240) received the usual outpatient management over the same period. HbA1c, blood chemistries, anthropometric parameters, and adverse events were assessed at the beginning of the study, after three months, and the end of the study. Results There were no initial significant differences between the groups with respect to demographics and clinical parameters. Upon six-month follow-up, HbA1c levels were significantly decreased from 7.86 ± 0.69% to 7.55 ± 0.86% within the intervention group ( p < 0.001) compared to 7.81 ± 0.66% to 7.70 ± 0.88% within the control group. Postprandial glucose reduction was predominant. A subgroup with baseline HbA1c higher than 8% and good compliance achieved a reduction of HbA1c by 0.8 ± 1.05%. Glucose control and waist circumference reduction were more effective in females and subjects older than 40 years of age. There were no adverse events associated with the intervention. Discussion This e-healthcare system was effective for glucose control and body composition improvement without associated adverse events in a multi-centre trial. This system may be effective in improving diabetes control in the general population.
Subject(s)
Diabetes Mellitus, Type 2/therapy , Internet , Self-Management/methods , Telemedicine/organization & administration , Aged , Blood Chemical Analysis , Body Weights and Measures , Efficiency, Organizational , Female , Glycated Hemoglobin , Humans , Male , Middle Aged , Patient Compliance/statistics & numerical data , Patient Safety , Treatment OutcomeABSTRACT
Obesity is rapidly increasing and is of great public health concern worldwide. Although there have been remarkable developments in obesity research over the past 10 years, the molecular mechanism of obesity is still not completely understood. Body weight results from the balance between food intake and energy expenditure. Recent studies have found that hypothalamic AMP-activated protein kinase plays a key role in regulating these processes. Leptin, insulin, glucose and alpha-lipoic acid have been shown to reduce food intake by lowering hypothalamic AMP-activated protein kinase activity, whereas ghrelin and glucose depletion increase food intake by increasing hypothalamic AMP-activated protein kinase activity. In addition, this enzyme plays a role in the central regulation of energy expenditure. These findings indicate that hypothalamic AMP-activated protein kinase is an important signal molecule, which integrates nutritional and hormonal signals and modulates feeding behavior and energy expenditure.
Subject(s)
Body Weight , Hypothalamus/metabolism , Multienzyme Complexes/metabolism , Obesity/metabolism , Protein Serine-Threonine Kinases/metabolism , AMP-Activated Protein Kinases , Adipose Tissue/metabolism , Eating , Energy Metabolism , Homeostasis , Obesity/genetics , Obesity/physiopathology , Signal Transduction/physiologyABSTRACT
AMP-activated protein kinase (AMPK) acts as a cellular energy sensor, being activated during states of low energy charge. Hypothalamic AMPK activity is altered by hormonal and metabolic signals and mediates the feeding response. To determine the effect of diabetes on hypothalamic AMPK activity, we assayed this activity in streptozotocin (STZ)-induced diabetic rats. Compared with control rats, STZ-induced diabetic rats had significant hyperphagia and weight loss. Hypothalamic AMPK phosphorylation and alpha2-AMPK activity were higher and acetyl-CoA carboxylase activity was lower in diabetic rats than in control rats. Chronic insulin treatment or suppression of hypothalamic AMPK activity completely prevented diabetes-induced changes in food intake as well as in hypothalamic AMPK activity and mRNA expression of neuropeptide Y and proopiomelanocortin. Plasma leptin and insulin levels were profoundly decreased in diabetic rats. Intracerebroventricular administration of leptin and insulin reduced hyperphagia and the enhanced hypothalamic AMPK activity in diabetic rats. These data suggest that leptin and insulin deficiencies in diabetes lead to increased hypothalamic AMPK activity, which contributes to the development of diabetic hyperphagia.
Subject(s)
Diabetes Mellitus, Experimental/enzymology , Hyperphagia/enzymology , Hypothalamus/enzymology , Hypothalamus/physiopathology , Multienzyme Complexes/metabolism , Protein Serine-Threonine Kinases/metabolism , AMP-Activated Protein Kinases , Adipose Tissue/anatomy & histology , Animals , Energy Intake , Gene Transfer Techniques , Genes, myc/genetics , Insulin/blood , Leptin/blood , Male , Organ Size , Phosphorylation , Rats , Rats, Sprague-Dawley , Weight LossABSTRACT
Hyperinsulinism-hyperammonemia syndrome is due either to hyperactivity of GDH or impaired inhibition of GDH by GTP. We have investigated the effect of Cimicifuga heracleifolia extract on the activities of glutamate dehydrogenase (GDH) in cultured rat islets. When the extract was present in the culture medium for 24 h prior to cell harvest, the Vmax of GDH was decreased by 45% with no significant change in Km. In addition, the concentration of alpha-ketoglutarate increased by approximately 39%, and glutamate decreased by 48%. Perfusion of islets with C. heracleifolia extract reduced insulin release by up to 47%. Although the relation between GDH activity and insulin release remains to be clarified, our results suggest that C. heracleifolia extract regulates insulin release by altering GDH activity in primary cultured islets and that this natural compound may be used to modulate GDH activity in patients with hyperinsulinism-hyperammonemia syndrome.