Influencing Factors of Glycemic Variability in Type 1 Diabetes Patients

Abstract

BackgroundThe prevalence of T1DM (type 1 diabetes) is increasing year by year, and its autoimmunity can easily lead to the destruction of pancreaticβcells and insulin deficiency, making blood glucose difficult to reach the target.ObjectiveTo investigate the influencing factors of glucose variability in patients with T1DM by using flash glucose monitoring system (FGMS) , and to provide basis for future clinical use of targeted hypoglycemic treatment.MethodsUsing convenience sampling method, 85 patients with T1DM admitted to the Affiliated Huaian No.1 People's Hospital of Nanjing Medical University from May 2019 to April 2020 were selected as the research objects. The gender, age, diabetesduration, marital status, education level, smoking history, drinking history and other general data to determine body mass index (BMI) , waist hip ratio (WHR) , blood pressure (BP) , glycosylated hemoglobin (HbA1c) , total cholesterol (TC) , total triglycerides (TG) , high-density lipoprotein cholesterol (HDL-C) , low-density lipoprotein cholesterol (HDL-C) , estimated glomerular filtration rate (eGFR) , and urinary albumin creatinine ratio (UACR) of patients were collected. According to whether the mean amplitude of glycemic excursions (MAGE) of patient is higher than the overall average value of 0.82 mmol/L, patients were divided into high blood glucose fluctuation group and low blood glucose fluctuation group. The scores of the Summary of Diabetes Self Care Activities (SDSCA) and the Diabetes Empowerment Scale-Short Form (DES-SF) were calculated. Multiple linear regression was used to analyze the influencing factors of blood glucose fluctuation.ResultsThere were statistically significant difference between two groups in age, diabetes duration, HbA1c, TG, UACR, MEAN, SD, TIR, DES-SF scores and SDSCA scores (P<0.05) . Multiple linear regression analysis showed that age was the influencing factor of MEAN (β=-0.272, P=0.019) , SD (β=-0.300, P=0.009) , and MAGE (β=-0.254, P=0.007) , diabetes durationwas the influencing factor of MEAN (β=0.466, P=0.029) , HbA1cwas the influencing factor of MEAN (β=0.416, P<0.001) , SD (β=0.330, P=0.004) , TIR (β=-0.287, P=0.014) , MAGE (β=0.182, P<0.001) , UACR was the influencing factor of SD (β=0.264, P=0.040) , TIR (β=-0.350, P=0.006) , MAGE (β=0.236, P=0.009) , the total score of SDSCA was the influencing factor of MEAN (β=0.416, P<0.001) , SD (β=0.330, P=0.004) and TIR (β=-0.287, P=0.014) , the total score of DES-SF was the influencing factor of MEAN (β=-0.271, P=0.045) and TIR (β=0.865, P=0.016) .ConclusionAge, diabete duration, HbA1c, UACR, self-management behavior and self management potential were the influencing factors of glucose variability in patients with T1DM, individual hypoglycemic strategies should be formulated for patients according to these factors, so as to reduce patients' blood glucose fluctuations and delay the occurrence and development of the complications.

Keywords

• |diabetes mellitus, type 1|blood glucose excursions|flash glucose monitoring system|analysis of risk factors