- Clinical Care/Education
- Comparison of Glucose Area Under the Curve Measured Using Minimally Invasive Interstitial Fluid Extraction Technology with Continuous Glucose Monitoring System in Diabetic Patients
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Mei Uemura, Yutaka Yano, Toshinari Suzuki, Taro Yasuma, Toshiyuki Sato, Aya Morimoto, Samiko Hosoya, Chihiro Suminaka, Hiromu Nakajima, Esteban C. Gabazza, Yoshiyuki Takei
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Diabetes Metab J. 2017;41(4):265-274. Published online July 31, 2017
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DOI: https://doi.org/10.4093/dmj.2017.41.4.265
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Abstract
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- Background
Continuous glucose monitoring (CGM) is reported to be a useful technique, but difficult or inconvenient for some patients and institutions. We are developing a glucose area under the curve (AUC) monitoring system without blood sampling using a minimally invasive interstitial fluid extraction technology (MIET). Here we evaluated the accuracy of interstitial fluid glucose (IG) AUC measured by MIET in patients with diabetes for an extended time interval and the potency of detecting hyperglycemia using CGM data as a reference. MethodsThirty-eight inpatients with diabetes undergoing CGM were enrolled. MIET comprised a pretreatment step using a plastic microneedle array and glucose accumulation step with a hydrogel patch, which was placed on two sites from 9:00 AM to 5:00 PM or from 10:00 PM to 6:00 AM. IG AUC was calculated by accumulated glucose extracted by hydrogel patches using sodium ion as standard. ResultsA significant correlation was observed between the predicted AUC by MIET and CGM in daytime (r=0.76) and nighttime (r=0.82). The optimal cutoff for the IG AUC value of MIET to predict hyperglycemia over 200 mg/dL measured by CGM for 8 hours was 1,067.3 mg·hr/dL with 88.2% sensitivity and 81.5% specificity. ConclusionWe showed that 8-hour IG AUC levels using MIET were valuable in estimating the blood glucose AUC without blood sampling. The results also supported the concept of using this technique for evaluating glucose excursion and for screening hyperglycemia during 8 hours in patients with diabetes at any time of day.
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Citations
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- Efficacy of Postprandial Exercise in Mitigating Glycemic Responses in Overweight Individuals and Individuals with Obesity and Type 2 Diabetes—A Systematic Review and Meta-Analysis
Jie Kang, Brian M. Fardman, Nicholas A. Ratamess, Avery D. Faigenbaum, Jill A. Bush Nutrients.2023; 15(20): 4489. CrossRef - Multifunctional Wearable System that Integrates Sweat‐Based Sensing and Vital‐Sign Monitoring to Estimate Pre‐/Post‐Exercise Glucose Levels
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- Evaluation of a Novel Glucose Area Under the Curve (AUC) Monitoring System: Comparison with the AUC by Continuous Glucose Monitoring
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Satoshi Ugi, Hiroshi Maegawa, Katsutaro Morino, Yoshihiko Nishio, Toshiyuki Sato, Seiki Okada, Yasuo Kikkawa, Toshihiro Watanabe, Hiromu Nakajima, Atsunori Kashiwagi
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Diabetes Metab J. 2016;40(4):326-333. Published online July 26, 2016
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DOI: https://doi.org/10.4093/dmj.2016.40.4.326
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7,000
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84
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4
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5
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Abstract
PDFPubReader
- Background
Management of postprandial hyperglycemia is a key aspect in diabetes treatment. We developed a novel system to measure glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET) for simple monitoring of postprandial glucose excursions. In this study, we evaluated the relationship between our system and continuous glucose monitoring (CGM) by comparing glucose AUC obtained using MIET with that obtained using CGM for a long duration. MethodsTwenty diabetic inpatients wearing a CGM system were enrolled. For MIET measurement, a plastic microneedle array was applied to the skin as pretreatment, and hydrogels were placed on the pretreated area to collect interstitial fluid. Hydrogels were replaced every 2 or 4 hours and AUC was predicted on the basis of glucose and sodium ion levels. ResultsAUC predicted by MIET correlated well with that measured by CGM (r=0.93). Good performances of both consecutive 2- and 4-hour measurements were observed (measurement error: 11.7%±10.2% for 2 hours and 11.1%±7.9% for 4 hours), indicating the possibility of repetitive measurements up to 8 hours. The influence of neither glucose fluctuation nor average glucose level over the measurement accuracy was observed through 8 hours. ConclusionOur system showed good relationship with AUC values from CGM up to 8 hours, indicating that single pretreatment can cover a large portion of glucose excursion in a day. These results indicated possibility of our system to contribute to convenient monitoring of glucose excursions for a long duration.
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Citations
Citations to this article as recorded by
- Effects of insulin glargine U300 versus insulin degludec U100 on glycemic variability, hypoglycemia, and diet evaluated by continuous glucose monitoring in type 1 diabetes: a retrospective cross‐sectional study
Pin‐Lun Tsai, Chia‐Hung Lin, Yu‐Yao Huang, Hsin‐Yun Chen, Yi‐Hsuan Lin The Kaohsiung Journal of Medical Sciences.2024;[Epub] CrossRef - Continuous glucose monitoring metrics and pregnancy outcomes in insulin‐treated diabetes: A post‐hoc analysis of the GlucoMOMS trial
Doortje Rademaker, Anne W. T. van der Wel, Rik van Eekelen, Daphne N. Voormolen, Harold W. de Valk, Inge M. Evers, Ben Willem Mol, Arie Franx, Sarah E. Siegelaar, Bas B. van Rijn, J. Hans DeVries, Rebecca C. Painter Diabetes, Obesity and Metabolism.2023; 25(12): 3798. CrossRef - Regimen comprising GLP-1 receptor agonist and basal insulin can decrease the effect of food on glycemic variability compared to a pre-mixed insulin regimen
Yi-Hsuan Lin, Chia-Hung Lin, Yu-Yao Huang, Hsin-Yun Chen, An-Shun Tai, Shih-Chen Fu, Sheng-Hwu Hsieh, Jui-Hung Sun, Szu-Tah Chen, Sheng-Hsuan Lin European Journal of Medical Research.2022;[Epub] CrossRef - Advantages of Applying Artificial Intelligent System to Medical Neurology (Preprint)
Zhenqiang Fu, Jingtao Wang, Jingtao Wang JMIR Medical Informatics.2020;[Epub] CrossRef - Comparison of Glucose Area Under the Curve Measured Using Minimally Invasive Interstitial Fluid Extraction Technology with Continuous Glucose Monitoring System in Diabetic Patients
Mei Uemura, Yutaka Yano, Toshinari Suzuki, Taro Yasuma, Toshiyuki Sato, Aya Morimoto, Samiko Hosoya, Chihiro Suminaka, Hiromu Nakajima, Esteban C. Gabazza, Yoshiyuki Takei Diabetes & Metabolism Journal.2017; 41(4): 265. CrossRef
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