Analysis of The Factors of Blood-related Indicators, Body Composition, and Nutritional Status That Influence on The Accuracy of Flash Glucose Monitoring Equipment
1. Department of Gerontology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China; 2. Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Abstract:Objective This study aims to explore risk factors impacting the accuracy of flash glucose monitoring (FGM) by analyzing various parameters including blood routine, biochemical indicators, blood glucose, body composition, and nutritional status among patients. Methods Patients were selected with type 2 diabetes who were hospitalized in the department of Gerontology at the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital) from April 2021 to April 2023. Patients' general information was collected, such as blood-related indicators, Body composition, malnutrition, and other parameters. FGM glucose readings were compared with fasting and 2-hour postprandial venous blood glucose respectively. Based on the paired blood glucose mean relative error (MARD) with its value 15% as a threshold, those with MARD less than 15% are the accurate group (MARD<15%), and those with more than 15% are the inaccurate group (MARD>15%). Among them, the patients were divided into the fasting FGM accurate group (n=25) and inaccurate group (n=18), and 2-hour postprandial FGM accurate group (n=32) and inaccurate group (n=11). Clarke grid analysis was used to evaluate the accuracy of FGM. Binary logistic regression analysis was performed to identify the independent risk factors that influence the accuracy of FGM. Results Forty-three subjects were included, yielding 86 pairs of blood glucose values. Clarke grid error analysis was performed on the FGM glucose values with venous blood glucose as the reference value. The results showed that 90.7% falls in area A, 9.3% falls in area B, and 100 % falls in area A+B, with an average MARD of 11.7%. Our results showcase that malnutrition is an independent risk factor affecting fasting FGM with an OR value of 7.979(95%CI 1.540-41.335, P=0.013) and it is also an independent risk factor affecting the accuracy of postprandial FGM with an OR value of 7.769(95% CI 1.117-59.370, P=0.048). Conclusion The FGM sensor used in this study met international standards for accuracy. Although the venous blood glucose is very different for a few individual patients during testing process, the overall accuracy for all patients is relatively high. Malnutrition was identified as a independent risk factor impacting FGM accuracy for fasting and 2-hour postprandial glucose levels, while age, body composition, and other blood routine and biochemical indicators showed no significant association with FGM accuracy.
邵丽洁, 朱翔, 朱文静, 殷实, 陈焱焱, 汪兰兰. 血液相关指标、体成分、营养状态对扫描式葡萄糖监测设备准确性的影响因素分析[J]. 湖南师范大学学报(医学版), 2024, 21(2): 127-132.
SHAO Lijie, ZHU Xiang, ZHU Wenjing, YIN Shi, CHEN Yanyan, WANG Lanlan. Analysis of The Factors of Blood-related Indicators, Body Composition, and Nutritional Status That Influence on The Accuracy of Flash Glucose Monitoring Equipment. HuNan ShiFan DaXue XueBao(YiXueBan), 2024, 21(2): 127-132.
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