Objective:To explore the effect of programmatic follow-up of joint nutrition team on the follow-up management of type 2 diabetes mellitus patients and to provide a basis for clinical practice.Methods:Using the convenient sampling method, a total of 144 patients with type 2 diabetes mellitus who were treated at the Diabetes Specialist Follow-up Clinic of the First Affiliated Hospital of Xinjiang Medical University from March 2016 to December 2017 were selected, and the programmatic follow-up of joint nutrition team was used for prospective observation. After the completion of 2-year follow-up, the changes in obesity, blood glucose, blood lipids and self-care activities of patients at baseline, 12th month and 24th month were compared using repeated measurements analysis of variance.Results:In the end, 141 patients completed the 2-year follow-up. Of the 141 patients, body mass index (BMI) was (21.73±1.89) kg/m 2, waistline was (77.57±1.68) cm, waist-to-hip ratio was (0.87±0.04) , fasting blood glucose was (5.14±0.92) mmol/L, glycosylated hemoglobin was (5.27±0.73) %, total cholesterol was (3.92±1.67) mmol/L, triglycerides was (1.94±0.68) mmol/L and low density lipoprotein was (1.04±0.31) mmol/L at the 24th month. The differences were statistically significant ( F=32.629, 5.556, 5.640, 89.734, 122.451, 43.373, 74.888, 35.887; P<0.05) among the 24th month, the 12th month and the baseline of the above indicators. At the 24 months, scores of diet, exercise, blood glucose monitoring and foot care in diabetic self-management behavior scale were respectively (20.33±3.09) , (11.13±1.54) , (11.78±1.99) and (10.42±1.91) . Compared with baseline and the 12th month, scores increased, and the differences were statistically significant ( F=25.276, 72.250, 74.503, 37.928; P<0.01) . Conclusions:The programmatic follow-up of joint nutrition team can improve indexes related to obesity, blood glucose and blood lipids in patients with type 2 diabetes mellitus and improve self-management ability of patients.

Objective:To explore the effect of precision nutrition therapy on the dietary pattern and appetite of patients with type 2 diabetes mellitus (T2DM) .Methods:From September 2018 to September 2019, convenience sampling method was used to select 155 patients with T2DM discharged from the Endocrinology Department of the First Affiliated Hospital of Xinjiang Medical University. All patients were randomly divided into control group (73 cases) and experimental group (82 cases) . Control group received routine nutritional intervention. Based on routine follow-up intervention, experimental group established a patient's personalized data model according to the medical artificial intelligence system for precise nutritional treatment, including the establishment of diabetes diet management prescriptions and intelligent diet intervention. The Dietary Pattern Questionnaire and the Simplified Nutritional Appetite Questionnaire (SNAQ) were used to compare the changes in dietary patterns and appetite before and after intervention between two groups.Results:After three months of intervention, the proportion of patients with reasonable protein, fat, and carbohydrate intake in two groups was higher than that before intervention, and that of experimental group was higher than that of control group, and the difference was statistically significant ( P<0.05) . After three months of intervention, the score of SNAQ of experimental group and control group was (13.20±1.54) and (10.32±1.25) respectively, and the difference was statistically significant ( t=-12.838, P<0.05) . Conclusions:The establishment of a big data model based on a medical artificial intelligence system for precise nutritional therapy can regulate the dietary behavior of patients with T2DM and increase their appetite.