Flash glucose monitoring system help reduce the frequency of hypoglycemia and hypoglycemic fear behavior in type 1 diabetes patients

Lining Dong; Junxian Li; Yanyun Hu; Ruoting Chai; Ye Zhu; Liying Zhu; Nengguang Fan; Zhijian Zhang; Jiemin Pan; Jinhua Yan; Fang Liu

doi:10.3389/fendo.2024.1464755

Flash glucose monitoring system help reduce the frequency of hypoglycemia and hypoglycemic fear behavior in type 1 diabetes patients

Front Endocrinol (Lausanne). 2024 Nov 12:15:1464755. doi: 10.3389/fendo.2024.1464755. eCollection 2024.

Authors

Lining Dong^#¹, Junxian Li^#¹, Yanyun Hu¹, Ruoting Chai¹, Ye Zhu¹, Liying Zhu¹, Nengguang Fan¹, Zhijian Zhang¹, Jiemin Pan², Jinhua Yan³, Fang Liu^{1

2}

Affiliations

¹ Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
² Shanghai Key Laboratory of Diabetes, Department of Endocrinology & Metabolism, Shanghai Jiao-Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Medical Center of Diabetes, Shanghai Key Clinical Center of Metabolic Diseases, Shanghai Institute for Diabetes, Shanghai, China.
³ Department of Endocrinology & Metabolism, The Third Affiliated Hospital of Sun Yat-Sen University, Guangdong, China.

^# Contributed equally.

Abstract

Objective: Hypoglycemia represents a serious acute complication in individuals with type 1 diabetes mellitus (T1DM). In order to more effectively identify and discriminate the occurrence of hypoglycemic events in patients with T1DM, this study aims to evaluate the impact of two distinct glucose monitoring systems-Flash Glucose Monitoring (FGM) and Continuous Glucose Monitoring (CGM)-on the management of blood glucose levels and the emotional responses associated with hypoglycemic episodes in individuals with T1DM.

Method: In this study, a total of 113 patients with type 1 diabetes mellitus were enrolled and allocated to two groups for the implementation of Glucose Monitoring Systems (GMS). The groups consisted of the FreeStyle Libre group (FGM, n=56) and the ipro2 group (CGM, n=57). Participants in both groups utilized GMS at least biannually and completed a set of three questionnaires: the Diabetes Monitoring and Treatment Satisfaction Questionnaire (DMTSQ), the Diabetes Specific Quality of Life (DQOL), and the Chinese Version of the Hypoglycemia Fear Survey II (CFHSII). Clinical data, CGM metrics, and questionnaire scores were collected at the initial visit and after a one-year follow-up period.

Results: The glucose coefficient of variation (GCV) and the standard deviation of blood glucose (SDBG) were independently associated with Time Below Range (TBR). Specifically, GCV could predict TBR ≥12%, with a cut-off point of 40.55. This yielded a specificity of 88.10% and a sensitivity of 68.18% in the overall patient population. For the FreeStyle Libre group and the iPro2 group, the cut-off points were 38.69 and 40.55, respectively, with specificities of 0.74 and 0.92, and sensitivities of 0.73 and 0.86, respectively. In the FreeStyle Libre group, where the frequency of use was greater than or equal to five times per year, the hypoglycemic episodes (time/month) and CHFSII-B scores were significantly reduced at follow-up compared to baseline (7.80 ± 10.25 vs 13.95 ± 14.87; 27.37 ± 11.05 vs 38.90 ± 21.61, respectively, all P <0.05).

Conclusion: The utilization of multiple Flash Glucose Monitoring (FGM) implementations proved to be valuable in discriminating the occurrence of hypoglycemia and mitigating the fear of hypoglycemic episodes in patients with type 1 diabetes. Within the parameters of Glucose Monitoring Systems (GMS), the glucose glycemic variability (GCV) was identified as a predictive factor for the risk of severe hypoglycemia (TBR > 12%). The optimal cut-off point for GCV was determined to be 40.55.

Keywords: continuous glucose monitoring system; flash glucose monitoring system; glucose coefficient of variation; hypoglycemia; type 1 diabetes.