Diabetes & Metabolism Journal

Brief Report

Technology/Device
Effectiveness of Predicted Low-Glucose Suspend Pump Technology in the Prevention of Hypoglycemia in People with Type 1 Diabetes Mellitus: Real-World Data Using DIA:CONN G8: Jee Hee Yoo, Ji Yoon Kim, Jae Hyeon Kim; Diabetes Metab J. 2025;49(1):144-149. Published online August 28, 2024; DOI: https://doi.org/10.4093/dmj.2024.0039

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Abstract PDF Supplementary Material PubReader ePub: We evaluated the effectiveness of the predictive low-glucose suspend (PLGS) algorithm in the DIA:CONN G8. Forty people with type 1 diabetes mellitus (T1DM) who used a DIA:CONN G8 for at least 2 months with prior experience using pumps without and with PLGS were retrospectively analyzed. The objective was to assess the changes in time spent in hypoglycemia (percent of time below range [%TBR]) before and after using PLGS. The mean age, sensor glucose levels, glucose threshold for suspension, and suspension time were 31.1±22.8 years, 159.7±23.2 mg/dL, 81.1±9.1 mg/dL, and 111.9±79.8 min/day, respectively. Overnight %TBR <70 mg/dL was significantly reduced after using the algorithm (differences=0.3%, from 1.4%±1.5% to 1.1%±1.2%, P=0.045). The glycemia risk index (GRI) improved significantly by 4.2 (from 38.8±20.9 to 34.6±19.0, P=0.002). Using the PLGS did not result in a change in the hyperglycemia metric (all P>0.05). Our findings support the PLGS in DIA:CONN G8 as an effective algorithm to improve night-time hypoglycemia and GRI in people with T1DM.

Review

Clinical Diabetes & Therapeutics
Recent Updates on Type 1 Diabetes Mellitus Management for Clinicians: Ahmed Iqbal, Peter Novodvorsky, Simon R. Heller; Diabetes Metab J. 2018;42(1):3-18. Published online February 23, 2018; DOI: https://doi.org/10.4093/dmj.2018.42.1.3

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Type 1 diabetes mellitus (T1DM) is a chronic autoimmune condition that requires life-long administration of insulin. Optimal management of T1DM entails a good knowledge and understanding of this condition both by the physician and the patient. Recent introduction of novel insulin preparations, technological advances in insulin delivery and glucose monitoring, such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring and improved understanding of the detrimental effects of hypoglycaemia and hyperglycaemia offer new opportunities and perspectives in T1DM management. Evidence from clinical trials suggests an important role of structured patient education. Our efforts should be aimed at improved metabolic control with concomitant reduction of hypoglycaemia. Despite recent advances, these goals are not easy to achieve and can put significant pressure on people with T1DM. The approach of physicians should therefore be maximally supportive. In this review, we provide an overview of the recent advances in T1DM management focusing on novel insulin preparations, ways of insulin administration and glucose monitoring and the role of metformin or sodium-glucose co-transporter 2 inhibitors in T1DM management. We then discuss our current understanding of the effects of hypoglycaemia on human body and strategies aimed at mitigating the risks associated with hypoglycaemia.

Citations

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Health-Related Quality of Life of Adolescents and Children With Type 1 Diabetes in the Jazan Region of Saudi Arabia
Gassem A Gohal, Aqilah Majhali, Esaam Moafa, Sarah H Talebi, Bushra I Maashi, Amani Mutaen, Walaa J Alhamdan, Ibrahim M Dighriri
Cureus.2024;[Epub] CrossRef
An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems
Sayyar Ahmad, Aleix Beneyto, Taiyu Zhu, Ivan Contreras, Pantelis Georgiou, Josep Vehi
Scientific Reports.2024;[Epub] CrossRef
Nose-to-brain delivery of insulin nanoparticles for diabetes management: A review
Manoj Kumbhare, Ajaykumar Surana, Pravin Morankar
Baghdad Journal of Biochemistry and Applied Biological Sciences.2023; 4(02): 39. CrossRef
Clinical Effects of a Home Care Pilot Program for Patients with Type 1 Diabetes Mellitus: A Retrospective Cohort Study
Sejeong Lee, KyungYi Kim, Ji Eun Kim, Yura Hyun, Minyoung Lee, Myung-Il Hahm, Sang Gyu Lee, Eun Seok Kang
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Jong Ha Baek, Woo Je Lee, Byung-Wan Lee, Soo Kyoung Kim, Gyuri Kim, Sang-Man Jin, Jae Hyeon Kim
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Dapagliflozin: an effective adjunctive treatment in type 1 diabetes
Ghasem Yadegarfar, Mark Livingston, Gabriela Cortes, Ramadan Alshames, Kate Leivesley, Ann Metters, Linda Horne, Tom Steele, Adrian H. Heald
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Original Articles

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: Mei Uemura, Yutaka Yano, Toshinari Suzuki, Taro Yasuma, Toshiyuki Sato, Aya Morimoto, Samiko Hosoya, Chihiro Suminaka, Hiromu Nakajima, Esteban C. Gabazza, Yoshiyuki Takei; Diabetes Metab J. 2017;41(4):265-274. Published online July 31, 2017; DOI: https://doi.org/10.4093/dmj.2017.41.4.265

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Abstract PDF PubReader

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.

Methods

Thirty-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.

Results

A 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.

Conclusion

We 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.

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
Yongseok Joseph Hong, Hyunjae Lee, Jaemin Kim, Minha Lee, Hyung Jin Choi, Taeghwan Hyeon, Dae‐Hyeong Kim
Advanced Functional Materials.2018;[Epub] CrossRef

Others
Evaluation of a Novel Glucose Area Under the Curve (AUC) Monitoring System: Comparison with the AUC by Continuous Glucose Monitoring: Satoshi Ugi, Hiroshi Maegawa, Katsutaro Morino, Yoshihiko Nishio, Toshiyuki Sato, Seiki Okada, Yasuo Kikkawa, Toshihiro Watanabe, Hiromu Nakajima, Atsunori Kashiwagi; Diabetes Metab J. 2016;40(4):326-333. Published online July 26, 2016; DOI: https://doi.org/10.4093/dmj.2016.40.4.326

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Abstract PDF PubReader

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.

Methods

Twenty 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.

Results

AUC 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.

Conclusion

Our 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.

Citations

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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; 40(12): 1086. 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

1,5-Anhydroglucitol as a Useful Marker for Assessing Short-Term Glycemic Excursions in Type 1 Diabetes: Hannah Seok, Ji Hye Huh, Hyun Min Kim, Byung-Wan Lee, Eun Seok Kang, Hyun Chul Lee, Bong Soo Cha; Diabetes Metab J. 2015;39(2):164-170. Published online March 9, 2015; DOI: https://doi.org/10.4093/dmj.2015.39.2.164

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Abstract PDF PubReader

Background

Type 1 diabetes is associated with more severe glycemic variability and more frequent hypoglycemia than type 2 diabetes. Glycemic variability is associated with poor glycemic control and diabetic complications. In this study, we demonstrate the clinical usefulness of serum 1,5-anhydroglucitol (1,5-AG) for assessing changes in glycemic excursion in type 1 diabetes.

Methods

Seventeen patients with type 1 diabetes were enrolled in this study. A continuous glucose monitoring system (CGMS) was applied twice at a 2-week interval to evaluate changes in glycemic variability. The changes in serum glycemic assays, including 1,5-AG, glycated albumin and hemoglobin A1c (HbA1c), were also evaluated.

Results

Most subjects showed severe glycemic excursions, including hypoglycemia and hyperglycemia. The change in 1,5-AG level was significantly correlated with changes in the glycemic excursion indices of the standard deviation (SD), mean amplitude of glucose excursion (MAGE), lability index, mean postmeal maximum glucose, and area under the curve for glucose above 180 mg/dL (r=-0.576, -0.613, -0.600, -0.630, and -0.500, respectively; all P<0.05). Changes in glycated albumin were correlated with changes in SD and MAGE (r=0.495 and 0.517, respectively; all P<0.05). However, changes in HbA1c were not correlated with any changes in the CGMS variables.

Conclusion

1,5-AG may be a useful marker for the assessment of short-term changes in glycemic variability. Furthermore, 1,5-AG may have clinical implications for the evaluation and treatment of glycemic excursions in type 1 diabetes.

Citations

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Digital Behavior Change Interventions to Reduce Sedentary Behavior and Promote Physical Activity in Adults with Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Xiaoyan Zhang, Xue Qiao, Ke Peng, Shan Gao, Yufang Hao
International Journal of Behavioral Medicine.2024; 31(6): 959. CrossRef
The correlation between serum 1, 5-anhydroglucitol and β-cell function in Chinese adults with different glucose metabolism statuses
Yuexing Yuan, Yuanyuan Tan, Yao Wang, Shanhu Qiu, Jiao Yang, Cheng Chen
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The progress of clinical research on the detection of 1,5-anhydroglucitol in diabetes and its complications
Huijuan Xu, Junhua Pan, Qiu Chen
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Glycation and Glucose Variability in Subjects with Type 1 Diabetes
V. V. Klimontov, D. M. Bulumbaeva, J. F. Semenova
Biochemistry (Moscow), Supplement Series B: Biomedical Chemistry.2024; 18(1): 59. CrossRef
The clinical potential of 1,5-anhydroglucitol as biomarker in diabetes mellitus
Haiying Xu, Renyin Chen, Xiaoli Hou, Na Li, Yanwei Han, Shaoping Ji
Frontiers in Endocrinology.2024;[Epub] CrossRef
Glycemic dispersion: a new index for screening high glycemic variability
Rui Shi, Lei Feng, Yan-Mei Liu, Wen-Bo Xu, Bei-Bei Luo, Ling-Tong Tang, Qian-Ye Bi, Hui-Ying Cao
Diabetology & Metabolic Syndrome.2023;[Epub] CrossRef
DBS are suitable for 1,5-anhydroglucitol monitoring in GSD1b and G6PC3-deficient patients taking SGLT2 inhibitors to treat neutropenia
Joseph P. Dewulf, Nathalie Chevalier, Sandrine Marie, Maria Veiga-da-Cunha
Molecular Genetics and Metabolism.2023; 140(3): 107712. CrossRef
HbA1c combined with glycated albumin or 1,5‐anhydroglucitol improves the efficiency of diabetes screening in a Chinese population
Junyi Qian, Cheng Chen, Xiaohang Wang, Yuanyuan Tan, Jiao Yang, Yuexing Yuan, Juan Chen, Haijian Guo, Bei Wang, Zilin Sun, Yao Wang
Diabetic Medicine.2022;[Epub] CrossRef
Assessment of glycemia in chronic kidney disease
Mohamed Hassanein, Tariq Shafi
BMC Medicine.2022;[Epub] CrossRef
Continuous subcutaneous insulin infusion alters microRNA expression and glycaemic variability in children with type 1 diabetes
Emma S. Scott, Andrzej S. Januszewski, Luke M. Carroll, Gregory R. Fulcher, Mugdha V. Joglekar, Anandwardhan A. Hardikar, Timothy W. Jones, Elizabeth A. Davis, Alicia J. Jenkins
Scientific Reports.2021;[Epub] CrossRef
Red rice koji extract alleviates hyperglycemia by increasing glucose uptake and glucose transporter type 4 levels in skeletal muscle in two diabetic mouse models
Takakazu Yagi, Koji Ataka, Kai-Chun Cheng, Hajime Suzuki, Keizaburo Ogata, Yumiko Yoshizaki, Kazunori Takamine, Ikuo Kato, Shouichi Miyawaki, Akio Inui, Akihiro Asakawa
Food & Nutrition Research.2020;[Epub] CrossRef
How tightly controlled do fluctuations in blood glucose levels need to be to reduce the risk of developing complications in people with Type 1 diabetes?
R. Livingstone, J. G. Boyle, J. R. Petrie
Diabetic Medicine.2020; 37(4): 513. CrossRef
Resolution on the results of the first working meeting of the scientific advisory board «Actual problems of glycemic variability as a new criterion of glycemic control and safety of diabetes therapy»
Mikhail B. Antsiferov, Gagik R. Galstyan, Alexey V. Zilov, Alexander Y. Mayorov, Tatyana N. Markova, Nikolay A. Demidov, Olga M. Koteshkova, Dmitry N. Laptev, Alisa V. Vitebskaya
Diabetes mellitus.2019; 22(3): 281. CrossRef
Hyperglycemia and Carotenoid Intake Are Associated with Serum Carotenoids in Youth with Type 1 Diabetes
Namrata Sanjeevi, Leah M. Lipsky, Tonja R. Nansel
Journal of the Academy of Nutrition and Dietetics.2019; 119(8): 1340. CrossRef
Correlation of Serum 1,5-AG with Uric Acid in Type 2 Diabetes Mellitus with Different Renal Functions
Kai Zhang, Bizhen Xue, Yuexing Yuan, Yao Wang
International Journal of Endocrinology.2019; 2019: 1. CrossRef
Glycaemic control and glycaemic variability in older people with diabetes
Hermes J Florez
The Lancet Diabetes & Endocrinology.2018; 6(6): 433. CrossRef
Alternate glycemic markers reflect glycemic variability in continuous glucose monitoring in youth with prediabetes and type 2 diabetes
Christine L. Chan, Laura Pyle, Megan M. Kelsey, Lindsey Newnes, Amy Baumgartner, Philip S. Zeitler, Kristen J. Nadeau
Pediatric Diabetes.2017; 18(7): 629. CrossRef
1,5-anidroglucitolo: un marcatore non tradizionale di iperglicemia
Gabriella Lavalle, Roberto Testa, Maria Elisabetta Onori, Raffaella Vero, Anna Vero
La Rivista Italiana della Medicina di Laboratorio - Italian Journal of Laboratory Medicine.2017; 13(3-4): 139. CrossRef
Glycemic control and variability in association with body mass index and body composition over 18months in youth with type 1 diabetes
Leah M. Lipsky, Benjamin Gee, Aiyi Liu, Tonja R. Nansel
Diabetes Research and Clinical Practice.2016; 120: 97. CrossRef
How Can We Easily Measure Glycemic Variability in Diabetes Mellitus?
Suk Chon
Diabetes & Metabolism Journal.2015; 39(2): 114. CrossRef
Alternative biomarkers for assessing glycemic control in diabetes: fructosamine, glycated albumin, and 1,5-anhydroglucitol
Ji-Eun Lee
Annals of Pediatric Endocrinology & Metabolism.2015; 20(2): 74. CrossRef
Glycemic Variability: How Do We Measure It and Why Is It Important?
Sunghwan Suh, Jae Hyeon Kim
Diabetes & Metabolism Journal.2015; 39(4): 273. CrossRef

Effectiveness of 3-Day Continuous Glucose Monitoring for Improving Glucose Control in Type 2 Diabetic Patients in Clinical Practice: Soo Kyoung Kim, Hye Jeong Kim, Taehun Kim, Kyu Yeon Hur, Sun Wook Kim, Moon-Kyu Lee, Yong-Ki Min, Kwang-Won Kim, Jae Hoon Chung, Jae Hyeon Kim; Diabetes Metab J. 2014;38(6):449-455. Published online December 15, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.6.449

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Abstract PDF PubReader

Background

The aim of this study was to investigate whether adjusting diabetic treatment regimens according to the information obtained from a continuous glucose monitoring system (CGMS) might lead to improved glycemic control in patients with type 2 diabetes.

Methods

We reviewed the medical charts of 172 patients who used the CGMS for 1 year starting in December 2008 and the records of 1,500 patients who visited their regular outpatient clinics during December 2008. Of these patients, a total of 65 CGMS patients and 301 regular outpatients (control group) were enrolled in the study after propensity score matching. There were no differences in baseline glycated hemoglobin (HbA1c), age, and duration of diabetes between the CGMS and the control groups after propensity score matching. The changes in the HbA1c levels from baseline to 6 months were calculated.

Results

The CGMS group showed a significant improvement in the HbA1c level compared to the control group at 3 months (7.9%±1.6% vs. 7.4%±1.2%, P=0.001) and at 6 months (7.4%±1.2% vs. 7.9%±1.6%, P=0.010). There were significant differences in the treatment modality changes between the CGMS group and the control group.

Conclusion

Using a 3-day CGMS was advantageous for improving glucose control in patients with type 2 diabetes and may help these patients to optimize glycemic control in clinical practice.

Citations

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Joseph A. Sierra, Mona Shah, Max S. Gill, Zachery Flores, Hiten Chawla, Francine R. Kaufman, Robert Vigersky
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Sunghwan Suh, Jae Hyeon Kim
Diabetes & Metabolism Journal.2015; 39(4): 273. CrossRef

The Correlation and Accuracy of Glucose Levels between Interstitial Fluid and Venous Plasma by Continuous Glucose Monitoring System: Young Ha Baek, Heung Yong Jin, Kyung Ae Lee, Seon Mee Kang, Woong Ji Kim, Min Gul Kim, Ji Hyun Park, Soo Wan Chae, Hong Sun Baek, Tae Sun Park; Korean Diabetes J. 2010;34(6):350-358. Published online December 31, 2010; DOI: https://doi.org/10.4093/kdj.2010.34.6.350

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Background

Clinical experience with the continuous glucose monitoring systems (CGMS) is limited in Korea. The objective of this study is to evaluate the accuracy of the CGMS and the correlation between interstitial fluid and venous plasma glucose level in Korean healthy male subjects.

Methods

Thirty-two subjects were served with glucose solution contained same amount of test food's carbohydrate and test foods after separate overnight fasts. CGMS was performed over 3 days during hopitalization for each subjects. Venous plasma glucose measurements were carried out during 4 hours (0, 0.25, 0.5, 0.75, 1, 2, 4 hours) just before and after glucose solution and test food load. The performance of the CGMS was evaluated by comparing its readings to those obtained at the same time by the hexokinase method using the auto biochemistry machine (Hitachi 7600-110). Also, correlations between glucose recorded with CGMS and venous plasma glucose value were examined.

Results

CGMS slightly underestimated the glucose value as compared with the venous plasma glucose level (16.3 ± 22.2 mg/dL). Correlation between CGMS and venous plasma glucose values throughout sensor lifetime is 0.73 (regression analysis: slope = 1.08, intercept = 8.38 mg/dL). Sensor sensitivity can deteriorate over time, with correlations between venous blood glucose and CGMS values dropping from 0.77 during 1st day to 0.65 during 2nd and 3rd day.

Conclusion

The accuracy of data provided by CGMS may be less than expected. CGMS sensor sensitivity is decreased with the passage of time. But, from this study, CGMS can be used for glucose variability tendency monitoring conveniently to the Korean.

Citations

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