Diabetes & Metabolism Journal

Brief Report

Technology/Device
Do-It-Yourself Open Artificial Pancreas System in Children and Adolescents with Type 1 Diabetes Mellitus: Real-World Data: Min Sun Choi, Seunghyun Lee, Jiwon Kim, Gyuri Kim, Sung Min Park, Jae Hyeon Kim; Diabetes Metab J. 2022;46(1):154-159. Published online November 23, 2021; DOI: https://doi.org/10.4093/dmj.2021.0011

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Abstract PDF Supplementary Material PubReader ePub

Few studies have been conducted among Asian children and adolescents with type 1 diabetes mellitus (T1DM) using do-it-yourself artificial pancreas system (DIY-APS). We evaluated real-world data of pediatric T1DM patients using DIY-APS. Data were obtained for 10 patients using a DIY-APS with algorithms. We collected sensor glucose and insulin delivery data from each participant for a period of 4 weeks. Average glycosylated hemoglobin was 6.2%±0.3%. The mean percentage of time that glucose level remained in the target range of 70 to 180 mg/dL was 82.4%±7.8%. Other parameters including time above range, time below range and mean glucose were also within the recommended level, similar to previous commercial and DIY-APS studies. However, despite meeting the target range, unadjusted gaps were still observed between the median basal setting and temporary basal insulin, which should be handled by healthcare providers.

Citations

Citations to this article as recorded by

Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control
Jee Hee Yoo, Jae Hyeon Kim
Diabetes & Metabolism Journal.2023; 47(1): 27. CrossRef
Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience
Judith Nir, Marianna Rachmiel, Abigail Fraser, Yael Lebenthal, Avivit Brener, Orit Pinhas-Hamiel, Alon Haim, Eve Stern, Noa Levek, Tal Ben-Ari, Zohar Landau
Endocrine.2023; 81(2): 262. CrossRef
Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial
Mengyun Lei, Beisi Lin, Ping Ling, Zhigu Liu, Daizhi Yang, Hongrong Deng, Xubin Yang, Jing Lv, Wen Xu, Jinhua Yan
BMJ Open.2023; 13(8): e073263. CrossRef
Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey
Antonia Huhndt, Yanbing Chen, Shane O’Donnell, Drew Cooper, Hanne Ballhausen, Katarzyna A. Gajewska, Timothée Froment, Mandy Wäldchen, Dana M. Lewis, Klemens Raile, Timothy C. Skinner, Katarina Braune
Frontiers in Clinical Diabetes and Healthcare.2022;[Epub] CrossRef
Toward Personalized Hemoglobin A1c Estimation for Type 2 Diabetes
Namho Kim, Da Young Lee, Wonju Seo, Nan Hee Kim, Sung-Min Park
IEEE Sensors Journal.2022; 22(23): 23023. CrossRef

Response

Response: An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment (Diabetes Metab J 2020;44:56–66): Sung Woon Park, Seunghyun Lee, Won Chul Cha, Kyu Yeon Hur, Jae Hyeon Kim, Moon-Kyu Lee, Sung-Min Park, Sang-Man Jin; Diabetes Metab J. 2020;44(2):358-359. Published online April 23, 2020; DOI: https://doi.org/10.4093/dmj.2020.0080; [Original]

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Original Article

Drug/Regimen
An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment: Sung Woon Park, Seunghyun Lee, Won Chul Cha, Kyu Yeon Hur, Jae Hyeon Kim, Moon-Kyu Lee, Sung-Min Park, Sang-Man Jin; Diabetes Metab J. 2020;44(1):56-66. Published online October 21, 2019; DOI: https://doi.org/10.4093/dmj.2018.0227

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Abstract PDF Supplementary Material PubReader

Background

We aimed to describe the outcome of a computerized intravenous insulin infusion (CII) protocol integrated to the electronic health record (EHR) system and to improve the CII protocol in silico using the EHR-based predictors of the outcome.

Methods

Clinical outcomes of the patients who underwent the CII protocol between July 2016 and February 2017 and their matched controls were evaluated. In the CII protocol group (n=91), multivariable binary logistic regression analysis models were used to determine the independent associates with a delayed response (taking ≥6.0 hours for entering a glucose range of 70 to 180 mg/dL). The CII protocol was adjusted in silico according to the EHR-based parameters obtained in the first 3 hours of CII.

Results

Use of the CII protocol was associated with fewer subjects with hypoglycemia alert values (P=0.003), earlier (P=0.002), and more stable (P=0.017) achievement of a glucose range of 70 to 180 mg/dL. Initial glucose level (P=0.001), change in glucose during the first 2 hours (P=0.026), and change in insulin infusion rate during the first 3 hours (P=0.029) were independently associated with delayed responses. Increasing the insulin infusion rate temporarily according to these parameters in silico significantly reduced delayed responses (P<0.0001) without hypoglycemia, especially in refractory patients.

Conclusion

Our CII protocol enabled faster and more stable glycemic control than conventional care with minimized risk of hypoglycemia. An EHR-based adjustment was simulated to reduce delayed responses without increased incidence of hypoglycemia.

Citations

Citations to this article as recorded by

Response: An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment (Diabetes Metab J 2020;44:56–66)
Sung Woon Park, Seunghyun Lee, Won Chul Cha, Kyu Yeon Hur, Jae Hyeon Kim, Moon-Kyu Lee, Sung-Min Park, Sang-Man Jin
Diabetes & Metabolism Journal.2020; 44(2): 358. CrossRef
Letter: An Electronic Health Record-Integrated Computerized Intravenous Insulin Infusion Protocol: Clinical Outcomes and in Silico Adjustment (Diabetes Metab J 2020;44:56–66)
Dongwon Yi
Diabetes & Metabolism Journal.2020; 44(2): 354. CrossRef

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