Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Search

Page Path
HOME > Search
5 "Insulin infusion system"
Filter
Filter
Article category
Keywords
Publication year
Authors
Funded articles
Short Communication
Technology/Device
A 4-Week, Two-Center, Open-Label, Single-Arm Study to Evaluate the Safety and Efficacy of EOPatch in Well-Controlled Type 1 Diabetes Mellitus
Jiyun Park, Nammi Park, Sangjin Han, You-Bin Lee, Gyuri Kim, Sang-Man Jin, Woo Je Lee, Jae Hyeon Kim
Diabetes Metab J. 2022;46(6):941-947.   Published online March 8, 2022
DOI: https://doi.org/10.4093/dmj.2021.0299
  • 5,168 View
  • 269 Download
  • 2 Web of Science
  • 3 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
This study evaluated the safety and efficacy of tubeless patch pump called EOPatch in patients with well-controlled type 1 diabetes mellitus (T1DM). This 4-week, two-center, open-label, single-arm study enrolled 10 adult patients diagnosed with T1DM with glycosylated hemoglobin less than 7.5%. The co-primary end points were patch pump usage time for one attachment and number of serious adverse events related to the patch pump. The secondary end points were total amount of insulin injected per patch and changes in glycemic parameters including continuous glucose monitoring data compared to those at study entry. The median usage time per patch was 84.00 hours (interquartile range, 64.50 to 92.50). Serious adverse events did not occur during the trial. Four weeks later, time in range 70 to 180 mg/dL was significantly improved (70.71%±17.14 % vs. 82.96%±9.14%, P=0.01). The times spent below range (<54 mg/dL) and above range (>180 mg/dL) also improved (All P<0.05). Four-week treatment with a tubeless patch pump was safe and led to clinical improvement in glycemic control.

Citations

Citations to this article as recorded by  
  • Multilayer track‐etched membrane‐based electroosmotic pump for drug delivery
    Qian Yang, Zebo Zhang, Junshu Lin, Boyu Zhu, Rongying Yu, Xinru Li, Bin Su, Bo Zhao
    ELECTROPHORESIS.2024; 45(5-6): 433.     CrossRef
  • Comparison between a tubeless, on-body automated insulin delivery system and a tubeless, on-body sensor-augmented pump in type 1 diabetes: a multicentre randomised controlled trial
    Ji Yoon Kim, Sang-Man Jin, Eun Seok Kang, Soo Heon Kwak, Yeoree Yang, Jee Hee Yoo, Jae Hyun Bae, Jun Sung Moon, Chang Hee Jung, Ji Cheol Bae, Sunghwan Suh, Sun Joon Moon, Sun Ok Song, Suk Chon, Jae Hyeon Kim
    Diabetologia.2024;[Epub]     CrossRef
  • A true continuous healthcare system for type 1 diabetes
    Jiyong Kim, Salman Khan, Eun Kyu Kim, Hye-Jun Kil, Bo Min Kang, Hyo Geon Lee, Jin-Woo Park, Jun Young Yoon, Woochul Kim
    Nano Energy.2023; 113: 108553.     CrossRef
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
  • 5,285 View
  • 192 Download
  • 5 Web of Science
  • 5 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   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
Review
Technology/Device
Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence
Sun Joon Moon, Inha Jung, Cheol-Young Park
Diabetes Metab J. 2021;45(6):813-839.   Published online November 22, 2021
DOI: https://doi.org/10.4093/dmj.2021.0177
  • 14,420 View
  • 796 Download
  • 28 Web of Science
  • 28 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

Citations

Citations to this article as recorded by  
  • Integration of a Safety Module to Prevent Rebound Hypoglycemia in Closed-Loop Artificial Pancreas Systems
    María F. Villa-Tamayo, Patricio Colmegna, Marc D. Breton
    Journal of Diabetes Science and Technology.2024; 18(2): 318.     CrossRef
  • The effects of acute hyperglycaemia on sports and exercise performance in type 1 diabetes: A systematic review and meta-analysis
    Bonar McGuire, Hashim Dadah, Dominic Oliver
    Journal of Science and Medicine in Sport.2024; 27(2): 78.     CrossRef
  • A new approach to stabilize diabetes systems with time-varying delays and disturbance rejection
    S. Syafiie, Fahd Alharbi, Abdullah Ali Alshehri, Bassam Hasanain
    Journal of the Franklin Institute.2024; 361(1): 543.     CrossRef
  • Effects of Low-Dose Glucagon on Subcutaneous Insulin Absorption in Pigs
    Ingrid Anna Teigen, Marte Kierulf Åm, Misbah Riaz, Sverre Christian Christiansen, Sven Magnus Carlsen
    Current Therapeutic Research.2024; 100: 100736.     CrossRef
  • Robust Online Correlation Method for Identification of a Nonparametric Model of Type 1 Diabetes
    Martin Dodek, Eva Miklovičová
    IEEE Access.2024; 12: 35899.     CrossRef
  • 100 Years of insulin: A chemical engineering perspective
    B. Wayne Bequette
    Korean Journal of Chemical Engineering.2023; 40(1): 1.     CrossRef
  • Efficacy of intermittent short‐term use of a real‐time continuous glucose monitoring system in non‐insulin–treated patients with type 2 diabetes: A randomized controlled trial
    Sun Joon Moon, Kyung‐Soo Kim, Woo Je Lee, Mi Yeon Lee, Robert Vigersky, Cheol‐Young Park
    Diabetes, Obesity and Metabolism.2023; 25(1): 110.     CrossRef
  • Identifiable prediction animal model for the bi-hormonal intraperitoneal artificial pancreas
    Karim Davari Benam, Hasti Khoshamadi, Marte Kierulf Åm, Øyvind Stavdahl, Sebastien Gros, Anders Lyngvi Fougner
    Journal of Process Control.2023; 121: 13.     CrossRef
  • 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
  • CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review
    John S Pemberton, Emma G Wilmot, Katharine Barnard‐Kelly, Lalantha Leelarathna, Nick Oliver, Tabitha Randell, Craig E Taplin, Pratik Choudhary, Peter Adolfsson
    Diabetes, Obesity and Metabolism.2023; 25(4): 916.     CrossRef
  • Evaluation of awareness and attitude of paediatric nursing students, nurses, and adolescents regarding type one diabetes advanced devices and virtual nursing
    Howaida Moawad Ahmed Ali
    Kontakt.2023; 25(2): 100.     CrossRef
  • Predicting the output error of the suboptimal state estimator to improve the performance of the MPC-based artificial pancreas
    Martin Dodek, Eva Miklovičová
    Control Theory and Technology.2023; 21(4): 541.     CrossRef
  • A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials
    Martina Vettoretti, Martina Drecogna, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino
    Computer Methods and Programs in Biomedicine.2023; 240: 107700.     CrossRef
  • Drug delivery breakthrough technologies – A perspective on clinical and societal impact
    Beate Bittner, Manuel Sánchez-Félix, Dennis Lee, Athanas Koynov, Joshua Horvath, Felix Schumacher, Simon Matoori
    Journal of Controlled Release.2023; 360: 335.     CrossRef
  • Importance of continuous glucose monitoring in the treatment of diabetes mellitus
    Sun Joon Moon, Won-Young Lee
    Journal of the Korean Medical Association.2023; 66(7): 432.     CrossRef
  • Constrained Versus Unconstrained Model Predictive Control for Artificial Pancreas
    Chiara Toffanin, Lalo Magni
    IEEE Transactions on Control Systems Technology.2023; 31(5): 2288.     CrossRef
  • Intelligent Insulin vs. Artificial Intelligence for Type 1 Diabetes: Will the Real Winner Please Stand Up?
    Valentina Maria Cambuli, Marco Giorgio Baroni
    International Journal of Molecular Sciences.2023; 24(17): 13139.     CrossRef
  • Artificial Intelligence in Efficient Diabetes Care
    Gopal Bhagwan Khodve, Sugato Banerjee
    Current Diabetes Reviews.2023;[Epub]     CrossRef
  • The artificial pancreas: two alternative approaches to achieve a fully closed-loop system with optimal glucose control
    M. K. Åm, I. A. Teigen, M. Riaz, A. L. Fougner, S. C. Christiansen, S. M. Carlsen
    Journal of Endocrinological Investigation.2023; 47(3): 513.     CrossRef
  • Multivariable Automated Insulin Delivery System for Handling Planned and Spontaneous Physical Activities
    Mohammad Reza Askari, Mohammad Ahmadasas, Andrew Shahidehpour, Mudassir Rashid, Laurie Quinn, Minsun Park, Ali Cinar
    Journal of Diabetes Science and Technology.2023; 17(6): 1456.     CrossRef
  • Advanced Technology (Continuous Glucose Monitoring and Advanced Hybrid Closed-Loop Systems) in Diabetes from the Perspective of Gender Differences
    Maria Grazia Nuzzo, Marciano Schettino
    Diabetology.2023; 4(4): 519.     CrossRef
  • Artificial Pancreas under a Zone Model Predictive Control based on Gaussian Process models: toward the personalization of the closed loop
    Marco Polver, Beatrice Sonzogni, Mirko Mazzoleni, Fabio Previdi, Antonio Ferramosca
    IFAC-PapersOnLine.2023; 56(2): 9642.     CrossRef
  • Personalized Constrained MPC for glucose regulation
    Chiara Toffanin, Lalo Magni
    IFAC-PapersOnLine.2023; 56(2): 9648.     CrossRef
  • Automated Insulin Delivery Systems in Children and Adolescents With Type 1 Diabetes: A Systematic Review and Meta-analysis of Outpatient Randomized Controlled Trials
    Baoqi Zeng, Le Gao, Qingqing Yang, Hao Jia, Feng Sun
    Diabetes Care.2023; 46(12): 2300.     CrossRef
  • Novel Glycemic Index Based on Continuous Glucose Monitoring to Predict Poor Clinical Outcomes in Critically Ill Patients: A Pilot Study
    Eun Yeong Ha, Seung Min Chung, Il Rae Park, Yin Young Lee, Eun Young Choi, Jun Sung Moon
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Dual‐hormone artificial pancreas for glucose control in type 1 diabetes: A meta‐analysis
    Baoqi Zeng, Hao Jia, Le Gao, Qingqing Yang, Kai Yu, Feng Sun
    Diabetes, Obesity and Metabolism.2022; 24(10): 1967.     CrossRef
  • Dual-Hormone Insulin-and-Pramlintide Artificial Pancreas for Type 1 Diabetes: A Systematic Review
    Alezandra Torres-Castaño, Amado Rivero-Santana, Lilisbeth Perestelo-Pérez, Andrea Duarte-Díaz, Analia Abt-Sacks, Vanesa Ramos-García, Yolanda Álvarez-Pérez, Ana M. Wäagner, Mercedes Rigla, Pedro Serrano-Aguilar
    Applied Sciences.2022; 12(20): 10262.     CrossRef
  • History of insulin treatment of pediatric patients with diabetes in Korea
    Jae Hyun Kim, Choong Ho Shin, Sei Won Yang
    Annals of Pediatric Endocrinology & Metabolism.2021; 26(4): 237.     CrossRef
Short Communication
Type 1 Diabetes
Real-World Analysis of Therapeutic Outcome in Type 1 Diabetes Mellitus at a Tertiary Care Center
Antonia Kietaibl, Michaela Riedl, Latife Bozkurt
Diabetes Metab J. 2022;46(1):149-153.   Published online July 6, 2021
DOI: https://doi.org/10.4093/dmj.2020.0267
  • 4,351 View
  • 144 Download
AbstractAbstract PDFPubReader   ePub   
Insulin replacement in type 1 diabetes mellitus (T1DM) needs intensified treatment, which can either be performed by multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII). This retrospective analysis of a real-world scenario aimed to evaluate whether glycaemic and cardiovascular risk factors could be controlled with CSII outclass MDI as suggested by recent evidence. Data from patients with either insulin pump (n=68) or injection (n=224) therapy at an Austrian tertiary care centre were analysed between January 2016 and December 2017. There were no significant differences with regard to the latest glycosylated hemoglobin, cardiovascular risk factor control or diabetes-associated late complications. Hypoglycaemia was less frequent (P<0.001), sensor-augmented therapy was more common (P=0.003) and mean body mass index (BMI) was higher (P=0.002) with CSII treatment. This retrospective analysis of real-world data in T1DM did not demonstrate the superiority of insulin pump treatment with regard to glycaemic control or cardiovascular risk factor control.
Review
Others
Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications
Giacomo Cappon, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti
Diabetes Metab J. 2019;43(4):383-397.   Published online July 25, 2019
DOI: https://doi.org/10.4093/dmj.2019.0121
  • 21,324 View
  • 984 Download
  • 178 Web of Science
  • 188 Crossref
AbstractAbstract PDFPubReader   

By providing blood glucose (BG) concentration measurements in an almost continuous-time fashion for several consecutive days, wearable minimally-invasive continuous glucose monitoring (CGM) sensors are revolutionizing diabetes management, and are becoming an increasingly adopted technology especially for diabetic individuals requiring insulin administrations. Indeed, by providing glucose real-time insights of BG dynamics and trend, and being equipped with visual and acoustic alarms for hypo- and hyperglycemia, CGM devices have been proved to improve safety and effectiveness of diabetes therapy, reduce hypoglycemia incidence and duration, and decrease glycemic variability. Furthermore, the real-time availability of BG values has been stimulating the realization of new tools to provide patients with decision support to improve insulin dosage tuning and infusion. The aim of this paper is to offer an overview of current literature and future possible developments regarding CGM technologies and applications. In particular, first, we outline the technological evolution of CGM devices through the last 20 years. Then, we discuss about the current use of CGM sensors from patients affected by diabetes, and, we report some works proving the beneficial impact provided by the adoption of CGM. Finally, we review some recent advanced applications for diabetes treatment based on CGM sensors.

Citations

Citations to this article as recorded by  
  • Continuous glucose monitoring metrics following sub-Tenon’s injection of triamcinolone acetonide for diabetic macular edema
    Rei Sotani-Ogawa, Sentaro Kusuhara, Yushi Hirota, Kyung Woo Kim, Wataru Matsumiya, Wataru Ogawa, Makoto Nakamura
    Graefe's Archive for Clinical and Experimental Ophthalmology.2024; 262(2): 449.     CrossRef
  • Identifying and mapping measures of medication safety during transfer of care in a digital era: a scoping literature review
    Catherine Leon, Helen Hogan, Yogini H Jani
    BMJ Quality & Safety.2024; 33(3): 173.     CrossRef
  • Highly sensitive and stable glucose sensing using N-type conducting polymer based organic electrochemical transistor
    Gang Zhou, Zhu Cao, Yangxuan Liu, Haoyu Zheng, Kai Xu
    Journal of Electroanalytical Chemistry.2024; 952: 117961.     CrossRef
  • Effectiveness and User Perception of an In-Vehicle Voice Warning for Hypoglycemia: Development and Feasibility Trial
    Caterina Bérubé, Vera Franziska Lehmann, Martin Maritsch, Mathias Kraus, Stefan Feuerriegel, Felix Wortmann, Thomas Züger, Christoph Stettler, Elgar Fleisch, A Baki Kocaballi, Tobias Kowatsch
    JMIR Human Factors.2024; 11: e42823.     CrossRef
  • Can Electrochemical Aptasensors Achieve the Commercial Success of Glucose Biosensors?
    Sina Ardalan, Anna Ignaszak
    Advanced Sensor Research.2024;[Epub]     CrossRef
  • Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes
    Huiqi Y. Lu, Xiaorong Ding, Jane E. Hirst, Yang Yang, Jenny Yang, Lucy Mackillop, David A. Clifton
    IEEE Reviews in Biomedical Engineering.2024; 17: 98.     CrossRef
  • Effects of Digitization of Self-Monitoring of Blood Glucose Records Using a Mobile App and the Cloud System on Outpatient Management of Diabetes: Single-Armed Prospective Study
    Tomoko Handa, Takeshi Onoue, Tomoko Kobayashi, Ryutaro Maeda, Keigo Mizutani, Ayana Yamagami, Tamaki Kinoshita, Yoshinori Yasuda, Shintaro Iwama, Takashi Miyata, Mariko Sugiyama, Hiroshi Takagi, Daisuke Hagiwara, Hidetaka Suga, Ryoichi Banno, Yoshinori Az
    JMIR Diabetes.2024; 9: e48019.     CrossRef
  • The Association of Macronutrient Consumption and BMI to Exhaled Carbon Dioxide in Lumen Users: Retrospective Real-World Study
    Shlomo Yeshurun, Tomer Cramer, Daniel Souroujon, Merav Mor
    JMIR mHealth and uHealth.2024; 12: e56083.     CrossRef
  • Generative adversarial network-based data augmentation for improving hypoglycemia prediction: A proof-of-concept study
    Wonju Seo, Namho Kim, Sung-Woon Park, Sang-Man Jin, Sung-Min Park
    Biomedical Signal Processing and Control.2024; 92: 106077.     CrossRef
  • Pre‐dinner walks may be superior to post‐dinner walks for glucose time in range in adults with type 1 diabetes on hybrid closed‐loop insulin delivery systems
    Lauren V. Turner, Michael C. Riddell
    Diabetes, Obesity and Metabolism.2024;[Epub]     CrossRef
  • Real-world effectiveness of GLP-1 receptor agonist-based treatment strategies on “time in range” in patients with type 2 diabetes
    Yongru Chen, Jingxian Chen, Shuo Zhang, Dan Zhu, Feiying Deng, Rui Zuo, Yufei Hu, Yue Zhao, Yale Duan, Benwei Lin, Fengwu Chen, Yun Liang, Jiaxiong Zheng, Barkat Ali Khan, Kaijian Hou
    Frontiers in Pharmacology.2024;[Epub]     CrossRef
  • Utility of Flash Glucose Monitoring to Determine Glucose Variation Induced by Different Doughs in Persons with Type 2 Diabetes
    Maria Antonietta Taras, Sara Cherchi, Ilaria Campesi, Valentina Margarita, Gavino Carboni, Paola Rappelli, Giancarlo Tonolo
    Diabetology.2024; 5(1): 129.     CrossRef
  • Facile chemiresistive biosensor functionalized with PANI/GOx and novel green synthesized silver nanoparticles for glucose sensing
    Jitendra B. Zalke, N.P. Narkhede, Dinesh R. Rotake, Shiv Govind Singh
    Microchemical Journal.2024; 200: 110339.     CrossRef
  • A novel questionnaire for evaluating digital tool use (DTUQ-D) among individuals with type 2 diabetes: exploring the digital landscape
    Ora Peleg, Efrat Hadar, Meyran Boniel-Nissim
    Frontiers in Public Health.2024;[Epub]     CrossRef
  • Continuous glucose monitoring with structured education in adults with type 2 diabetes managed by multiple daily insulin injections: a multicentre randomised controlled trial
    Ji Yoon Kim, Sang-Man Jin, Kang Hee Sim, Bo-Yeon Kim, Jae Hyoung Cho, Jun Sung Moon, Soo Lim, Eun Seok Kang, Cheol-Young Park, Sin Gon Kim, Jae Hyeon Kim
    Diabetologia.2024;[Epub]     CrossRef
  • Development of a Novel Insulin Sensor for Clinical Decision-Making
    Eva Vargas, Eleonora M. Aiello, Jordan E. Pinsker, Hazhir Teymourian, Farshad Tehrani, Mei Mei Church, Lori M. Laffel, Francis J. Doyle, Mary-Elizabeth Patti, Eyal Dassau, Joseph Wang
    Journal of Diabetes Science and Technology.2023; 17(4): 1029.     CrossRef
  • Diabetes technology and sexual health: which role?
    V. Zamponi, J. Haxhi, G. Pugliese, A. Faggiano, R. Mazzilli
    Journal of Endocrinological Investigation.2023;[Epub]     CrossRef
  • Discordance Between Glycated Hemoglobin A1c and the Glucose Management Indicator in People With Diabetes and Chronic Kidney Disease
    Philippe Oriot, Claire Viry, Antoine Vandelaer, Sébastien Grigioni, Malanie Roy, Jean Christophe Philips, Gaëtan Prévost
    Journal of Diabetes Science and Technology.2023; 17(6): 1553.     CrossRef
  • Expertenaustausch zum Einsatz von kontinuierlichem Glukosemonitoring (CGM) im Diabetesmanagement: Eine aktuelle Bestandsaufnahme und Blick in die Zukunft
    Andreas Thomas, Thomas Haak, Astrid Tombek, Bernhard Kulzer, Dominic Ehrmann, Olga Kordonouri, Jens Kroeger, Oliver Schubert-Olesen, Ralf Kolassa, Thorsten Siegmund, Nicola Haller, Lutz Heinemann
    Diabetologie und Stoffwechsel.2023; 18(01): 57.     CrossRef
  • Evaluation of the performance and usability of a novel continuous glucose monitoring system
    Li Yan, Qiang Li, Qingbo Guan, Mingsong Han, Yu Zhao, Junfei Fang, Jiajun Zhao
    International Journal of Diabetes in Developing Countries.2023; 43(4): 551.     CrossRef
  • Efficacy of intermittent short‐term use of a real‐time continuous glucose monitoring system in non‐insulin–treated patients with type 2 diabetes: A randomized controlled trial
    Sun Joon Moon, Kyung‐Soo Kim, Woo Je Lee, Mi Yeon Lee, Robert Vigersky, Cheol‐Young Park
    Diabetes, Obesity and Metabolism.2023; 25(1): 110.     CrossRef
  • Intermittent-scanned continuous glucose monitoring with low glucose alarms decreases hypoglycemia incidence in middle-aged adults with type 1 diabetes in real-life setting
    Philippe Oriot, Michel P. Hermans
    Journal of Diabetes and its Complications.2023; 37(2): 108385.     CrossRef
  • Applications of Microwaves in Medicine
    J.-C. Chiao, Changzhi Li, Jenshan Lin, Robert H. Caverly, James C. M. Hwang, Harel Rosen, Arye Rosen
    IEEE Journal of Microwaves.2023; 3(1): 134.     CrossRef
  • A Double-Needle Gold-Silver Electrodes Continuous Glucose Monitoring Device
    C. Ben Ali Hassine, A. Tekin
    IRBM.2023; 44(3): 100752.     CrossRef
  • Accuracy of Flash Glucose Monitoring in Hemodialysis Patients With and Without Diabetes Mellitus
    Michèle R. Weber, Matthias Diebold, Peter Wiesli, Andreas D. Kistler
    Experimental and Clinical Endocrinology & Diabetes.2023; 131(03): 132.     CrossRef
  • Minimally invasive electrochemical continuous glucose monitoring sensors: Recent progress and perspective
    Yuanyuan Zou, Zhengkang Chu, Jiuchuan Guo, Shan Liu, Xing Ma, Jinhong Guo
    Biosensors and Bioelectronics.2023; 225: 115103.     CrossRef
  • Continuous Glucose Monitoring in Enterally Fed Children with Severe Central Nervous System Impairment
    Marlena Górska, Joanna Kudzin, Anna Borkowska, Agnieszka Szlagatys-Sidorkiewicz, Agnieszka Szadkowska, Małgorzata Myśliwiec, Ewa Toporowska-Kowalska
    Nutrients.2023; 15(3): 513.     CrossRef
  • Prevalence of type 2 diabetes complications and its association with diet knowledge and skills and self‐care barriers in Tabriz, Iran: A cross‐sectional study
    Habib Jalilian, Elnaz Javanshir, Leila Torkzadeh, Saeedeh Fehresti, Nazanin Mir, Majid Heidari‐Jamebozorgi, Somayeh Heydari
    Health Science Reports.2023;[Epub]     CrossRef
  • Status of continuous glucose monitoring use and management in tertiary hospitals of China: a cross-sectional study
    Liping Chen, Xiaoqin Liu, Qin Lin, Hongmei Dai, Yong Zhao, Zumin Shi, Liping Wu
    BMJ Open.2023; 13(2): e066801.     CrossRef
  • Diboronic-Acid-Based Electrochemical Sensor for Enzyme-Free Selective and Sensitive Glucose Detection
    Joong-Hyun Kim, Hongsik Choi, Chul-Soon Park, Heung-Seop Yim, Dongguk Kim, Sungmin Lee, Yeonkeong Lee
    Biosensors.2023; 13(2): 248.     CrossRef
  • Artificial intelligence biosensors for continuous glucose monitoring
    Xiaofeng Jin, Andrew Cai, Tailin Xu, Xueji Zhang
    Interdisciplinary Materials.2023; 2(2): 290.     CrossRef
  • Continuous Glucose Monitoring in Dogs and Cats
    Francesca Del Baldo, Federico Fracassi
    Veterinary Clinics of North America: Small Animal Practice.2023; 53(3): 591.     CrossRef
  • Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy
    Anders Pors, Kaspar G. Rasmussen, Rune Inglev, Nina Jendrike, Amalie Philipps, Ajenthen G. Ranjan, Vibe Vestergaard, Jan E. Henriksen, Kirsten Nørgaard, Guido Freckmann, Karl D. Hepp, Michael C. Gerstenberg, Anders Weber
    ACS Sensors.2023; 8(3): 1272.     CrossRef
  • Diabetes mellitus in der Akut- und Notfallmedizin
    Leo Benning, Julian Krehl, Felix Patricius Hans
    Notfallmedizin up2date.2023; 18(01): 45.     CrossRef
  • Empowering People with Diabetes: Role of Continuous Glucose Monitor Systems
    Sneha B Srivastava
    American Journal of Lifestyle Medicine.2023; 17(3): 359.     CrossRef
  • Diabétologie connectée : quelles sont les attentes des médecins et des patients ?
    Nicolas Naïditch, Jean-Pierre Riveline
    Médecine des Maladies Métaboliques.2023; 17(2): 2S3.     CrossRef
  • Association of Vibrotactile Biofeedback With Reduced Ergonomic Risk for Surgeons During Tonsillectomy
    Natalie A. Kelly, Abdulrahman Althubaiti, Aashika D. Katapadi, Adam G. Smith, Sarah C. Nyirjesy, Jane H. Yu, Amanda J. Onwuka, Tendy Chiang
    JAMA Otolaryngology–Head & Neck Surgery.2023; 149(5): 397.     CrossRef
  • The Evolution of Diabetes Technology – Options Toward Personalized Care
    Maleeha Zahid, Samaneh Dowlatshahi, Abhishek H. Kansara, Archana R. Sadhu
    Endocrine Practice.2023; 29(8): 653.     CrossRef
  • A Personalized and Adaptive Insulin Bolus Calculator Based on Double Deep Q- Learning to Improve Type 1 Diabetes Management
    Giulia Noaro, Taiyu Zhu, Giacomo Cappon, Andrea Facchinetti, Pantelis Georgiou
    IEEE Journal of Biomedical and Health Informatics.2023; 27(5): 2536.     CrossRef
  • Celebrating a Century of Insulin Discovery: A Critical Appraisal of the Emerging Alternative Insulin Delivery Systems
    Ntethelelo Sibiya, Bonisiwe Mbatha, Phikelelani Ngubane, Andile Khathi
    Current Drug Delivery.2023; 20(6): 656.     CrossRef
  • Machine Learning–Based Time in Patterns for Blood Glucose Fluctuation Pattern Recognition in Type 1 Diabetes Management: Development and Validation Study
    Nicholas Berin Chan, Weizi Li, Theingi Aung, Eghosa Bazuaye, Rosa M Montero
    JMIR AI.2023; 2: e45450.     CrossRef
  • Drug Delivery Systems for Personal Healthcare by Smart Wearable Patch System
    Bikram Khadka, Byeongmoon Lee, Ki-Taek Kim
    Biomolecules.2023; 13(6): 929.     CrossRef
  • Wearable Electrochemical Glucose Sensors in Diabetes Management: A Comprehensive Review
    Tamoghna Saha, Rafael Del Caño, Kuldeep Mahato, Ernesto De la Paz, Chuanrui Chen, Shichao Ding, Lu Yin, Joseph Wang
    Chemical Reviews.2023; 123(12): 7854.     CrossRef
  • Real-life 24-week changes in glycemic parameters among European users of flash glucose monitoring with type 1 and 2 diabetes and different levels of glycemic control
    Annel Lameijer, Julia J. Bakker, Kalvin Kao, Yongjin Xu, Rijk O.B. Gans, Henk J.G. Bilo, Timothy C. Dunn, Peter R. van Dijk
    Diabetes Research and Clinical Practice.2023; 201: 110735.     CrossRef
  • Les médicaments anti-diabétiques : ce que le médecin anesthésiste réanimateur doit savoir
    Michael Joubert
    Anesthésie & Réanimation.2023; 9(3): 251.     CrossRef
  • Glycemia control using remote technologies
    L. A. Suplotova, O. O. Alieva
    Meditsinskiy sovet = Medical Council.2023; 17(9): 81.     CrossRef
  • Data-enabled learning and control algorithms for intelligent glucose management: The state of the art
    Deheng Cai, Wenjing Wu, Marzia Cescon, Wei Liu, Linong Ji, Dawei Shi
    Annual Reviews in Control.2023; 56: 100897.     CrossRef
  • A Markov Model of Gap Occurrence in Continuous Glucose Monitoring Data for Realistic in Silico Clinical Trials
    Martina Vettoretti, Martina Drecogna, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino
    Computer Methods and Programs in Biomedicine.2023; 240: 107700.     CrossRef
  • Volumetric Electron Transfer from Metabolites to Chemically Doped Polymer Electrodes
    Siew Ting Melissa Tan, Gijun Lee, Kalee Rozylowicz, Adam Marks, Alberto Salleo
    Advanced Functional Materials.2023;[Epub]     CrossRef
  • Diabetes and hypertension MobileHealth systems: a review of general challenges and advancements
    Bliss Utibe-Abasi Stephen, Benedicta C. Uzoewulu, Phillip Michael Asuquo, Simeon Ozuomba
    Journal of Engineering and Applied Science.2023;[Epub]     CrossRef
  • THE ASSESSMENT OF COMPENSATION OF CARBOHYDRATE METABOLISM IN PATIENTS WITH TYPE 2 DIABETES MELLITUS WITH METABOLIC SYNDROME BEYOND THE LIMITS OF GLYCATED HEMOGLOBIN
    Taras V. Romaniv, Nadiya V. Skrypnyk, Ulyana V. Synko, Nataliia M. Voronych-Semchenko, Oleh V. Melnyk, Anna O. Hryb, Igor B. Boruchok
    Wiadomości Lekarskie.2023; 76(6): 1385.     CrossRef
  • Pros and cons of continous glucose monitoring
    Marcin Ciechański, Edyta Witkowska, Agnieszka Ostańska, Adrianna Szafran, Klaudia Wiśniewska, Laura Piasek, Grzegorz Godek, Kacper Więcław, Katarzyna Stańko, Wiktor Terelak
    Journal of Medical Science.2023;[Epub]     CrossRef
  • Continuous Glucose Monitoring by Insulin-Treated Pilots Flying Commercial Aircraft Within the ARA.MED.330 Diabetes Protocol: A Preliminary Feasibility Study
    Gillian L. Garden, Fariba Shojaee-Moradie, Ewan J. Hutchison, Brian M. Frier, Kenneth M. Shaw, Simon R. Heller, Gerd Koehler, Julia K. Mader, Declan Maher, Graham A. Roberts, David L. Russell-Jones
    Diabetes Technology & Therapeutics.2023; 25(8): 543.     CrossRef
  • Importance of continuous glucose monitoring in the treatment of diabetes mellitus
    Sun Joon Moon, Won-Young Lee
    Journal of the Korean Medical Association.2023; 66(7): 432.     CrossRef
  • DiaTrend: A dataset from advanced diabetes technology to enable development of novel analytic solutions
    Temiloluwa Prioleau, Abigail Bartolome, Richard Comi, Catherine Stanger
    Scientific Data.2023;[Epub]     CrossRef
  • Testing the Real-World Accuracy of the Dexcom G6 Pro CGM During the Insulin-Only Bionic Pancreas Pivotal Trial
    Martin Chase Marak, Peter Calhoun, Edward R. Damiano, Steven J. Russell, Katrina J. Ruedy, Roy W. Beck
    Diabetes Technology & Therapeutics.2023; 25(11): 817.     CrossRef
  • Use of continuous glucose monitoring in pediatric gastroenterology allows for personalized nutrition support care – Potential for collaboration between pediatric endocrinologists and gastroenterologists
    Kathryn Hitchcock, Stephanie Oliveira
    Journal of Pediatric Endocrinology and Diabetes.2023; 3: 34.     CrossRef
  • Anti-biofouling strategies for implantable biosensors of continuous glucose monitoring systems
    Yan Zheng, Dunyun Shi, Zheng Wang
    Frontiers of Chemical Science and Engineering.2023; 17(12): 1866.     CrossRef
  • A novel strategy for therapeutic drug monitoring: application of biosensors to quantify antimicrobials in biological matrices
    Quanfang Wang, Sihan Li, Jiaojiao Chen, Luting Yang, Yulan Qiu, Qian Du, Chuhui Wang, Mengmeng Teng, Taotao Wang, Yalin Dong
    Journal of Antimicrobial Chemotherapy.2023; 78(11): 2612.     CrossRef
  • Hypoglycemic Effect of an Herbal Decoction (Modified Gangsimtang) in a Patient with Severe Type 2 Diabetes Mellitus Refusing Oral Anti-Diabetic Medication: A Case Report
    Sungjun Joo, Hyonjun Chun, Jisu Lee, Seungmin Seo, Jungmin Lee, Jungtae Leem
    Medicina.2023; 59(11): 1919.     CrossRef
  • GluGAN: Generating Personalized Glucose Time Series Using Generative Adversarial Networks
    Taiyu Zhu, Kezhi Li, Pau Herrero, Pantelis Georgiou
    IEEE Journal of Biomedical and Health Informatics.2023; 27(10): 5122.     CrossRef
  • Millifluidic valves and pumps made of tape and plastic
    Josue U. Amador-Hernandez, Pablo E. Guevara-Pantoja, Diana F. Cedillo-Alcantar, Gabriel A. Caballero-Robledo, Jose L. Garcia-Cordero
    Lab on a Chip.2023; 23(20): 4579.     CrossRef
  • Offline Deep Reinforcement Learning and Off-Policy Evaluation for Personalized Basal Insulin Control in Type 1 Diabetes
    Taiyu Zhu, Kezhi Li, Pantelis Georgiou
    IEEE Journal of Biomedical and Health Informatics.2023; 27(10): 5087.     CrossRef
  • Flash Glucose Monitoring in Croatia: The Optimal Number of Scans per Day to Achieve Good Glycemic Control in Type 1 Diabetes
    Silvija Canecki-Varzic, Ivana Prpic-Krizevac, Maja Cigrovski Berkovic, Dario Rahelic, Ema Schonberger, Marina Gradiser, Ines Bilic-Curcic
    Medicina.2023; 59(11): 1893.     CrossRef
  • The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP
    Francesco Prendin, Jacopo Pavan, Giacomo Cappon, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti
    Scientific Reports.2023;[Epub]     CrossRef
  • SHMAD: A Smart Health Care System to Monitor Alzheimer’s Disease Patients
    Shabana R. Ziyad, May Altulyan, Meshal Alharbi
    Journal of Alzheimer's Disease.2023; 95(4): 1545.     CrossRef
  • Séquelles fonctionnelles après résection pancréatique carcinologique. Un sujet d’actualité pour les patients et les praticiens
    Andrea Mulliri, Michael Joubert, Marie-Astrid Piquet, Arnaud Alves, Benoît Dupont
    Journal de Chirurgie Viscérale.2023; 160(6): 470.     CrossRef
  • Functional sequelae after pancreatic resection for cancer
    Andrea Mulliri, Michael Joubert, Marie-Astrid Piquet, Arnaud Alves, Benoît Dupont
    Journal of Visceral Surgery.2023; 160(6): 427.     CrossRef
  • Characteristics of glucose change in diabetes mellitus generalized through continuous wavelet transform processing: A preliminary study
    Yoichi Nakamura, Shinya Furukawa
    World Journal of Diabetes.2023; 14(10): 1562.     CrossRef
  • Evaluating passive physiological data collection during Spravato treatment
    Todd M. Solomon, Matus Hajduk, Martin Majernik, Jamileh Jemison, Alexander Deschamps, Jenna Scoggins, Adam Kolar, Miguel Amável Pinheiro, Peter Dubec, Ondrej Skala, Owen Muir, Amanda Tinkelman, Daniel R. Karlin, Robert Barrow
    Frontiers in Digital Health.2023;[Epub]     CrossRef
  • Fabrication of conductive Ag/AgCl/Ag nanorods ink on Laser-induced graphene electrodes on flexible substrates for non-enzymatic glucose detection
    Rana Bagheri, Saeid Alikhani, Ebrahim Miri-Moghaddam
    Scientific Reports.2023;[Epub]     CrossRef
  • Co-design of Human-centered, Explainable AI for Clinical Decision Support
    Cecilia Panigutti, Andrea Beretta, Daniele Fadda, Fosca Giannotti, Dino Pedreschi, Alan Perotti, Salvatore Rinzivillo
    ACM Transactions on Interactive Intelligent Systems.2023; 13(4): 1.     CrossRef
  • Analysis of blood glucose monitoring – a review on recent advancements and future prospects
    Gayathri Priyadarshini R, Sathiya Narayanan
    Multimedia Tools and Applications.2023;[Epub]     CrossRef
  • Nafion based biosensors: a review of recent advances and applications
    Roya Mohammadzadeh Kakhki
    International Journal of Polymeric Materials and Polymeric Biomaterials.2023; : 1.     CrossRef
  • Overview of modern sensors for continuous glucose monitoring
    K. T. Momynaliev, M. V. Prokopiev, I. V. Ivanov
    Diabetes mellitus.2023; 26(6): 575.     CrossRef
  • A Prospective Multicenter Clinical Performance Evaluation of the C-CGM System
    Mihailo Rebec, Kevin Cai, Ralph Dutt-Ballerstadt, Ellen Anderson
    Journal of Diabetes Science and Technology.2022; 16(2): 390.     CrossRef
  • Perceived Burdens and Benefits Associated With Continuous Glucose Monitor Use in Type 1 Diabetes Across the Lifespan
    Vidita Divan, Margaret Greenfield, Christopher P. Morley, Ruth S. Weinstock
    Journal of Diabetes Science and Technology.2022; 16(1): 88.     CrossRef
  • Technologies for Diabetes Self-Monitoring: A Scoping Review and Assessment Using the REASSURED Criteria
    Jessica Hanae Zafra-Tanaka, David Beran, Beatrice Vetter, Rangarajan Sampath, Antonio Bernabe-Ortiz
    Journal of Diabetes Science and Technology.2022; 16(4): 962.     CrossRef
  • Temporal Trends for Diabetes Management and Glycemic Control Between 2010 and 2019 in Korean Children and Adolescents with Type 1 Diabetes
    Jaewon Choe, Seung Hyun Won, Yunsoo Choe, Sang Hee Park, Yun Jeong Lee, Jieun Lee, Young Ah Lee, Han Hyuk Lim, Jae-Ho Yoo, Seong Yong Lee, Eun Young Kim, Choong Ho Shin, Jae Hyun Kim
    Diabetes Technology & Therapeutics.2022; 24(3): 201.     CrossRef
  • International comparison of glycaemic control in people with type 1 diabetes: an update and extension
    Regina Prigge, John A. McKnight, Sarah H. Wild, Aveni Haynes, Timothy W. Jones, Elizabeth A. Davis, Birgit Rami‐Merhar, Maria Fritsch, Christine Prchla, Astrid Lavens, Kris Doggen, Suchsia Chao, Ronnie Aronson, Ruth Brown, Else H. Ibfelt, Jannet Svensson,
    Diabetic Medicine.2022;[Epub]     CrossRef
  • Artificial intelligence perspective in the future of endocrine diseases
    Mandana Hasanzad, Hamid Reza Aghaei Meybodi, Negar Sarhangi, Bagher Larijani
    Journal of Diabetes & Metabolic Disorders.2022; 21(1): 971.     CrossRef
  • Telehealth Technologies and Their Benefits to People With Diabetes
    Chinenye O. Usoh, Kristine Kilen, Carolyn Keyes, Crystal Paige Johnson, Joseph A. Aloi
    Diabetes Spectrum.2022; 35(1): 8.     CrossRef
  • Acetylated Trifluoromethyl Diboronic Acid Anthracene with a Large Stokes Shift and Long Excitation Wavelength as a Glucose-Selective Probe
    Hongsik Choi, Inhyeok Song, Chul Soon Park, Heung-seop Yim, Joong Hyun Kim
    Applied Sciences.2022; 12(6): 2782.     CrossRef
  • Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study
    Patrik Schretzlmaier, Achim Hecker, Elske Ammenwerth
    JMIR Human Factors.2022; 9(1): e34918.     CrossRef
  • Continuous Glucose Monitoring System Based on Percutaneous Microneedle Array
    Ming-Nan Chien, Yu-Jen Chen, Chin-Han Bai, Jung-Tung Huang
    Micromachines.2022; 13(3): 478.     CrossRef
  • Impact of COVID-19 Lockdown on the Metabolic Control Parameters in Patients with Diabetes Mellitus: A Systematic Review and Meta-Analysis
    Ifan Ali Wafa, Nando Reza Pratama, Nurizzah Farahiyah Sofia, Elsha Stephanie Anastasia, Tiffany Konstantin, Maharani Ayuputeri Wijaya, M. Rifqi Wiyono, Lilik Djuari, Hermina Novida
    Diabetes & Metabolism Journal.2022; 46(2): 260.     CrossRef
  • Expert Roundtable on Continuous Glucose Monitoring
    Cheryl Rosenfeld, Thomas Blevins, Grazia Aleppo, Gregory Forlenza, Diana Isaacs, Javier Morales, Jane Seley, Jeffrey Unger
    Endocrine Practice.2022; 28(6): 622.     CrossRef
  • Glucose variability and predicted cardiovascular risk after gastrectomy
    Jun Shibamoto, Takeshi Kubota, Takuma Ohashi, Hirotaka Konishi, Atsushi Shiozaki, Hitoshi Fujiwara, Kazuma Okamoto, Eigo Otsuji
    Surgery Today.2022; 52(11): 1634.     CrossRef
  • Efficacy of once-weekly tirzepatide versus once-daily insulin degludec on glycaemic control measured by continuous glucose monitoring in adults with type 2 diabetes (SURPASS-3 CGM): a substudy of the randomised, open-label, parallel-group, phase 3 SURPASS
    Tadej Battelino, Richard M Bergenstal, Angel Rodríguez, Laura Fernández Landó, Ross Bray, Zhentao Tong, Katelyn Brown
    The Lancet Diabetes & Endocrinology.2022; 10(6): 407.     CrossRef
  • Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes
    Loïc Olçomendy, Louis Cassany, Antoine Pirog, Roberto Franco, Emilie Puginier, Manon Jaffredo, David Gucik-Derigny, Héctor Ríos, Alejandra Ferreira de Loza, Julien Gaitan, Matthieu Raoux, Yannick Bornat, Bogdan Catargi, Jochen Lang, David Henry, Sylvie Re
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Effect of divergent continuous glucose monitoring technologies on glycaemic control in type 1 diabetes mellitus: A systematic review and meta‐analysis of randomised controlled trials
    Mona Elbalshy, Jillian Haszard, Hazel Smith, Sarahmarie Kuroko, Barbara Galland, Nick Oliver, Viral Shah, Martin I. de Bock, Benjamin J. Wheeler
    Diabetic Medicine.2022;[Epub]     CrossRef
  • Novel Glycemic Index Based on Continuous Glucose Monitoring to Predict Poor Clinical Outcomes in Critically Ill Patients: A Pilot Study
    Eun Yeong Ha, Seung Min Chung, Il Rae Park, Yin Young Lee, Eun Young Choi, Jun Sung Moon
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms
    Brian Bogue-Jimenez, Xiaolei Huang, Douglas Powell, Ana Doblas
    Sensors.2022; 22(9): 3534.     CrossRef
  • Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach
    N. Camerlingo, M. Vettoretti, S. Del Favero, A. Facchinetti, P. Choudhary, G. Sparacino
    Computer Methods and Programs in Biomedicine.2022; 221: 106862.     CrossRef
  • A Miniaturized Optofluidic Glucose Monitoring System Based on Enzyme Colorimetry
    Qingmei Xu, Chongwei Zou, Chengtao Sun, Xingguo Zhang, Haixia Yu, Dachao Li
    IEEE Sensors Journal.2022; 22(10): 9246.     CrossRef
  • Use and Trends of Diabetes Self-Management Technologies: A Correlation-Based Study
    Jesús Fontecha, Iván González, Alfonso Barragán, Theodore Lim, Dario Pitocco
    Journal of Diabetes Research.2022; 2022: 1.     CrossRef
  • Nanotechnology in Diabetes Mellitus: Overview for Nurses
    R Priya, Baba Vajrala
    Pondicherry Journal of Nursing.2022; 15(1): 22.     CrossRef
  • Effect of Different Glucose Monitoring Methods on Bold Glucose Control: A Systematic Review and Meta-Analysis
    Yeling Wang, Congcong Zou, Han Na, Weixin Zeng, Xiaoyan Li, Xi Lou
    Computational and Mathematical Methods in Medicine.2022; 2022: 1.     CrossRef
  • Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology—A Review
    Aminah Hina, Wala Saadeh
    Sensors.2022; 22(13): 4855.     CrossRef
  • Performance of islets of Langerhans conformally coated via an emulsion cross-linking method in diabetic rodents and nonhuman primates
    Aaron A. Stock, Grisell C. Gonzalez, Sophia I. Pete, Teresa De Toni, Dora M. Berman, Alexander Rabassa, Waldo Diaz, James C. Geary, Melissa Willman, Joy M. Jackson, Noa H. DeHaseth, Noel M. Ziebarth, Anthony R. Hogan, Camillo Ricordi, Norma S. Kenyon, Ali
    Science Advances.2022;[Epub]     CrossRef
  • Review—Electrochemistry and Other Emerging Technologies for Continuous Glucose Monitoring Devices
    Saroj Kumar Das, Kavya K. Nayak, P. R. Krishnaswamy, Vinay Kumar, Navakanta Bhat
    ECS Sensors Plus.2022; 1(3): 031601.     CrossRef
  • Design Strategies and Prospects in Developing Wearable Glucose Monitoring System Using Printable Organic Transistor and Microneedle: A Review
    Fazliyatul Azwa Md Rezali, Norhayati Soin, Sharifah Fatmadiana Wan Muhamad Hatta, Mohamad Hazwan Mohd Daut, Muhammad Hafizuddin Al-Helmy Nouxman, Hanim Hussin
    IEEE Sensors Journal.2022; 22(14): 13785.     CrossRef
  • Review of Automated Insulin Delivery Systems for Type 1 Diabetes and Associated Time in Range Outcomes
    Armaan Nallicheri, Katherine M Mahoney, Hanna A Gutow, Natalie Bellini, Diana Isaacs
    Endocrinology.2022; 18(1): 27.     CrossRef
  • Evaluation of Mesoporous TiO2 Layers as Glucose Optical Sensors
    David Ortiz de Zárate, Sara Serna, Salvador Ponce-Alcántara, Jaime García-Rupérez
    Sensors.2022; 22(14): 5398.     CrossRef
  • A Prospective Study on Continuous Glucose Monitoring in Glycogen Storage Disease Type Ia: Toward Glycemic Targets
    Alessandro Rossi, Annieke Venema, Petra Haarsma, Lude Feldbrugge, Rob Burghard, David Rodriguez-Buritica, Giancarlo Parenti, Maaike H Oosterveer, Terry G J Derks
    The Journal of Clinical Endocrinology & Metabolism.2022; 107(9): e3612.     CrossRef
  • Continuous glucose monitoring as a close to real life alternative to meal studies – a pilot study with a functional drink containing amino acids and chromium
    Azat Samigullin, Per M. Humpert, Elin Östman
    Frontiers in Medical Technology.2022;[Epub]     CrossRef
  • An overview of recent advances in insulin delivery and wearable technology for effective management of diabetes
    Sujeet Kumar Raj, M. Ravindra Babu, Sukriti Vishwas, M.V.N.L. Chaitanya, Vancha Harish, Gaurav Gupta, Dinesh Kumar Chellappan, Kamal Dua, Sachin Kumar Singh
    Journal of Drug Delivery Science and Technology.2022; 75: 103728.     CrossRef
  • Medical Certification of Pilots Through the Insulin-Treated Diabetes Mellitus Protocol at the FAA
    Lynn K. Stanwyck, James R. DeVoll, Joyce Pastore, Zykevise Gamble, Anna Poe, Gabrielle V. Gui
    Aerospace Medicine and Human Performance.2022; 93(8): 627.     CrossRef
  • Rate of glycaemic control and associated factors in patients with type 2 diabetes mellitus treated with insulin-based therapy at selected hospitals in Northwest Ethiopia: a multicentre cross-sectional study
    Ashenafi Kibret Sendekie, Eyayaw Ashete Belachew, Ephrem Mebratu Dagnew, Adeladlew Kassie Netere
    BMJ Open.2022; 12(9): e065250.     CrossRef
  • Glucose Profiles Assessed by Intermittently Scanned Continuous Glucose Monitoring System during the Perioperative Period of Metabolic Surgery
    Kyuho Kim, Sung Hee Choi, Hak Chul Jang, Young Suk Park, Tae Jung Oh
    Diabetes & Metabolism Journal.2022; 46(5): 713.     CrossRef
  • Hypoglycemic events and glycemic control effects between NPH and premixed insulin in patients with type 2 diabetes mellitus: A real-world experience at a comprehensive specialized hospital in Ethiopia
    Ashenafi Kibret Sendekie, Adeladlew Kassie Netere, Eyayaw Ashete Belachew, Rekha Samuel
    PLOS ONE.2022; 17(9): e0275032.     CrossRef
  • Continuous Glucose Monitoring for the Diagnosis of Gestational Diabetes Mellitus: A Pilot Study
    Daria Di Filippo, Marrwah Ahmadzai, Melissa Han Yiin Chang, Ksana Horgan, Ru Min Ong, Justine Darling, Mahmood Akhtar, Amanda Henry, Alec Welsh, Daniela Foti
    Journal of Diabetes Research.2022; 2022: 1.     CrossRef
  • Caring for people with diabetes
    Martha M. Funnell, Katherine A. Kloss, Robin B. Nwankwo
    Nursing.2022; 52(11): 26.     CrossRef
  • Tackling the challenges of developing microneedle-based electrochemical sensors
    Hilmee Abdullah, Tonghathai Phairatana, Itthipon Jeerapan
    Microchimica Acta.2022;[Epub]     CrossRef
  • A Concise and Systematic Review on Non-Invasive Glucose Monitoring for Potential Diabetes Management
    Soumyasanta Laha, Aditi Rajput, Suvra S. Laha, Rohan Jadhav
    Biosensors.2022; 12(11): 965.     CrossRef
  • Assessment of Seasonal Stochastic Local Models for Glucose Prediction without Meal Size Information under Free-Living Conditions
    Francesco Prendin, José-Luis Díez, Simone Del Favero, Giovanni Sparacino, Andrea Facchinetti, Jorge Bondia
    Sensors.2022; 22(22): 8682.     CrossRef
  • Wearable Sensor-Based Monitoring of Environmental Exposures and the Associated Health Effects: A Review
    Xueer Lin, Jiaying Luo, Minyan Liao, Yalan Su, Mo Lv, Qing Li, Shenglan Xiao, Jianbang Xiang
    Biosensors.2022; 12(12): 1131.     CrossRef
  • Acceptability and feasibility of continuous glucose monitoring in people with diabetes: protocol for a mixed-methods systematic review of quantitative and qualitative evidence
    Jennifer V. E. Brown, Ramzi Ajjan, Najma Siddiqi, Peter A. Coventry
    Systematic Reviews.2022;[Epub]     CrossRef
  • Utilization of Personalized Machine-Learning to Screen for Dysglycemia from Ambulatory ECG, toward Noninvasive Blood Glucose Monitoring
    I-Min Chiu, Chi-Yung Cheng, Po-Kai Chang, Chao-Jui Li, Fu-Jen Cheng, Chun-Hung Richard Lin
    Biosensors.2022; 13(1): 23.     CrossRef
  • Effect of hydroxychloroquine on glycemic variability in type 2 diabetes patients uncontrolled on glimepiride and metformin therapy
    Rajesh Rajput, Suyasha Saini, Siddhant Rajput, Parankush Upadhyay
    Indian Journal of Endocrinology and Metabolism.2022; 26(6): 537.     CrossRef
  • GESTATIONAL DIABETES MELLITUS: MODERN GLYCEMIA MONITORING SYSTEMS
    YU.A. DUDAREVA, V.A. GURYEVA, G.V. NEMTSEVA
    AVICENNA BULLETIN.2022; 24(1): 97.     CrossRef
  • Extraction With Sweat-Sebum Emulsion as a New Test Method for Leachables in Patch-Based Medical Devices, Illustrated by Assessment of Isobornylacrylate (IBOA) in Diabetes Products
    Herbert Fink, Nuno M. de Barros Fernandes, Jörg Weissmann, Manfred Frey
    Journal of Diabetes Science and Technology.2021; 15(4): 792.     CrossRef
  • Mathematical Models of Meal Amount and Timing Variability With Implementation in the Type-1 Diabetes Patient Decision Simulator
    Nunzio Camerlingo, Martina Vettoretti, Simone Del Favero, Andrea Facchinetti, Giovanni Sparacino
    Journal of Diabetes Science and Technology.2021; 15(2): 346.     CrossRef
  • Fit‐for‐Purpose Biometric Monitoring Technologies: Leveraging the Laboratory Biomarker Experience
    Alan Godfrey, Benjamin Vandendriessche, Jessie P. Bakker, Cheryl Fitzer‐Attas, Ninad Gujar, Matthew Hobbs, Qi Liu, Carrie A. Northcott, Virginia Parks, William A. Wood, Vadim Zipunnikov, John A. Wagner, Elena S. Izmailova
    Clinical and Translational Science.2021; 14(1): 62.     CrossRef
  • Self-charging wearables for continuous health monitoring
    Jiyong Kim, Salman Khan, Peng Wu, Sungjin Park, Hwanjoo Park, Choongho Yu, Woochul Kim
    Nano Energy.2021; 79: 105419.     CrossRef
  • Impact of Switching from Intermittently Scanned to Real-Time Continuous Glucose Monitoring Systems in a Type 1 Diabetes Patient French Cohort: An Observational Study of Clinical Practices
    Yannis Préau, Martine Armand, Sébastien Galie, Pauline Schaepelynck, Denis Raccah
    Diabetes Technology & Therapeutics.2021; 23(4): 259.     CrossRef
  • Individualizing Time-in-Range Goals in Management of Diabetes Mellitus and Role of Insulin: Clinical Insights From a Multinational Panel
    Sanjay Kalra, Shehla Shaikh, Gagan Priya, Manas P. Baruah, Abhyudaya Verma, Ashok K. Das, Mona Shah, Sambit Das, Deepak Khandelwal, Debmalya Sanyal, Sujoy Ghosh, Banshi Saboo, Ganapathi Bantwal, Usha Ayyagari, Daphne Gardner, Cecilia Jimeno, Nancy E. Barb
    Diabetes Therapy.2021; 12(2): 465.     CrossRef
  • Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy
    Giulia Noaro, Giacomo Cappon, Martina Vettoretti, Giovanni Sparacino, Simone Del Favero, Andrea Facchinetti
    IEEE Transactions on Biomedical Engineering.2021; 68(1): 247.     CrossRef
  • Efficacy of telemedicine for persons with type 1 diabetes during Covid19 lockdown
    Federico Boscari, Sara Ferretto, Ambra Uliana, Angelo Avogaro, Daniela Bruttomesso
    Nutrition & Diabetes.2021;[Epub]     CrossRef
  • Technological innovation of Continuous Glucose Monitoring (CGM) as a tool for commercial aviation pilots with insulin-treated diabetes and stakeholders/regulators: A new chance to improve the directives?
    F. Strollo, A. Furia, P. Verde, A. Bellia, M. Grussu, A. Mambro, M.D. Petrelli, S. Gentile
    Diabetes Research and Clinical Practice.2021; 172: 108638.     CrossRef
  • Machine Learning Techniques for Hypoglycemia Prediction: Trends and Challenges
    Omer Mujahid, Ivan Contreras, Josep Vehi
    Sensors.2021; 21(2): 546.     CrossRef
  • Time in range–A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study
    Marina Valenzano, Ivan Cibrario Bertolotti, Adriano Valenzano, Giorgio Grassi
    BMJ Open Diabetes Research & Care.2021; 9(1): e001045.     CrossRef
  • Machine learning for the diagnosis of early-stage diabetes using temporal glucose profiles
    Woo Seok Lee, Junghyo Jo, Taegeun Song
    Journal of the Korean Physical Society.2021; 78(5): 373.     CrossRef
  • Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only
    Francesco Prendin, Simone Del Favero, Martina Vettoretti, Giovanni Sparacino, Andrea Facchinetti
    Sensors.2021; 21(5): 1647.     CrossRef
  • A “Slide Rule” to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life
    Daniela Bruttomesso, Federico Boscari, Giuseppe Lepore, Giulia Noaro, Giacomo Cappon, Angela Girelli, Lutgarda Bozzetto, Andrea Tumminia, Giorgio Grassi, Giovanni Sparacino, Luigi Laviola, Andrea Facchinetti
    Diabetes Therapy.2021; 12(5): 1313.     CrossRef
  • Glycemic variability and cardiovascular disease in patients with type 2 diabetes
    Marcela Martinez, Jimena Santamarina, Adrian Pavesi, Carla Musso, Guillermo E Umpierrez
    BMJ Open Diabetes Research & Care.2021; 9(1): e002032.     CrossRef
  • Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments
    Omar Diouri, Monika Cigler, Martina Vettoretti, Julia K. Mader, Pratik Choudhary, Eric Renard
    Diabetes/Metabolism Research and Reviews.2021;[Epub]     CrossRef
  • Smartphone-based colorimetric detection systems for glucose monitoring in the diagnosis and management of diabetes
    Özlem Kap, Volkan Kılıç, John G. Hardy, Nesrin Horzum
    The Analyst.2021; 146(9): 2784.     CrossRef
  • The impact of hypoglycaemia on the quality of life of family members of adults with type 1 or type 2 diabetes: A qualitative systematic review
    Mette Valdersdorf Jensen, Melanie Broadley, Jane Speight, Alison Scope, Louise Preston, Simon Heller, Bastiaan E. de Galan, Frans Pouwer, Christel Hendrieckx
    Diabetic Medicine.2021;[Epub]     CrossRef
  • A review of biosensor technology and algorithms for glucose monitoring
    Yaguang Zhang, Jingxue Sun, Liansheng Liu, Hong Qiao
    Journal of Diabetes and its Complications.2021; 35(8): 107929.     CrossRef
  • Optical glucose biosensor built-in disposable strips and wearable electronic devices
    Abdullah Reda, Sherif A. El-Safty, Mahmoud M. Selim, Mohamed A. Shenashen
    Biosensors and Bioelectronics.2021; 185: 113237.     CrossRef
  • Advances, Challenges, and Cost Associated with Continuous Glucose Monitor Use in Adolescents and Young Adults with Type 1 Diabetes
    Karishma A. Datye, Daniel R. Tilden, Angelee M. Parmar, Eveline R. Goethals, Sarah S. Jaser
    Current Diabetes Reports.2021;[Epub]     CrossRef
  • Is HbA1c an ideal biomarker of well-controlled diabetes?
    Georgia Kaiafa, Stavroula Veneti, George Polychronopoulos, Dimitrios Pilalas, Stylianos Daios, Ilias Kanellos, Triantafyllos Didangelos, Stamatina Pagoni, Christos Savopoulos
    Postgraduate Medical Journal.2021; 97(1148): 380.     CrossRef
  • Technology in the management of type 2 diabetes: Present status and future prospects
    Aideen Daly, Roman Hovorka
    Diabetes, Obesity and Metabolism.2021; 23(8): 1722.     CrossRef
  • A Non-Invasive Flexible Glucose Monitoring Sensor Using a Broadband Reject Filter
    Moussa Bteich, Jessica Hanna, Joseph Costantine, Rouwaida Kanj, Youssef Tawk, Ali H. Ramadan, Assaad A. Eid
    IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology.2021; 5(2): 139.     CrossRef
  • Wearable patch delivery system for artificial pancreas health diagnostic-therapeutic application: A review
    Nur Farrahain Nadia Ahmad, Nik Nazri Nik Ghazali, Yew Hoong Wong
    Biosensors and Bioelectronics.2021; 189: 113384.     CrossRef
  • Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies
    Mary Katherine Ray, Alana McMichael, Maria Rivera-Santana, Jacob Noel, Tamara Hershey
    JMIR Diabetes.2021; 6(2): e27027.     CrossRef
  • Designing biomaterials for the modulation of allogeneic and autoimmune responses to cellular implants in Type 1 Diabetes
    Magdalena M. Samojlik, Cherie L. Stabler
    Acta Biomaterialia.2021; 133: 87.     CrossRef
  • Evaluation of a continuous glucose monitoring system in neonatal foals
    David Wong, Caitlin Malik, Katarzyna Dembek, Krista Estell, Megan Marchitello, Katie Wilson
    Journal of Veterinary Internal Medicine.2021; 35(4): 1995.     CrossRef
  • Flash Glucose Monitoring in the Netherlands: Increased monitoring frequency is associated with improvement of glycemic parameters
    Annel Lameijer, Nicole Lommerde, Timothy C. Dunn, Marion J. Fokkert, Mireille A. Edens, Kalvin Kao, Yongjin Xu, R.O.B. Gans, Henk J.G. Bilo, Peter R. van Dijk
    Diabetes Research and Clinical Practice.2021; 177: 108897.     CrossRef
  • Utilisation, access and recommendations regarding technologies for people living with type 1 diabetes: consensus statement of the ADS/ADEA/APEG/ADIPS Working Group
    Anthony J Pease, Sofianos Andrikopoulos, Mary B Abraham, Maria E Craig, Brett Fenton, Jane Overland, Sarah Price, David Simmons, Glynis P Ross
    Medical Journal of Australia.2021; 215(10): 473.     CrossRef
  • Catalytic effects of magnetic and conductive nanoparticles on immobilized glucose oxidase in skin sensors
    Lilian C Alarcón-Segovia, Amay J Bandodkar, John A Rogers, Ignacio Rintoul
    Nanotechnology.2021; 32(37): 375101.     CrossRef
  • Optical Glucose Sensor Using Pressure Sensitive Paint
    Jongwon Park
    Sensors.2021; 21(13): 4474.     CrossRef
  • Type 1 diabetes glycemic management: Insulin therapy, glucose monitoring, and automation
    Bruce A. Perkins, Jennifer L. Sherr, Chantal Mathieu
    Science.2021; 373(6554): 522.     CrossRef
  • Clinical Utilities of Continuous Glucose Monitoring and Insulin Pumps in Pediatric Patients with Type 1 Diabetes
    Jieun Lee, Jae Hyun Kim
    The Ewha Medical Journal.2021; 44(3): 55.     CrossRef
  • Personalized Postprandial Glucose Response–Targeting Diet Versus Mediterranean Diet for Glycemic Control in Prediabetes
    Orly Ben-Yacov, Anastasia Godneva, Michal Rein, Smadar Shilo, Dmitry Kolobkov, Netta Koren, Noa Cohen Dolev, Tamara Travinsky Shmul, Bat Chen Wolf, Noa Kosower, Keren Sagiv, Maya Lotan-Pompan, Niv Zmora, Adina Weinberger, Eran Elinav, Eran Segal
    Diabetes Care.2021; 44(9): 1980.     CrossRef
  • Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions
    Jong Il Park, Hwa Young Lee, Hyunah Kim, Jisan Lee, Jiwon Shinn, Hun-Sung Kim
    Journal of Korean Medical Science.2021;[Epub]     CrossRef
  • Benefits of a Switch from Intermittently Scanned Continuous Glucose Monitoring (isCGM) to Real-Time (rt) CGM in Diabetes Type 1 Suboptimal Controlled Patients in Real-Life: A One-Year Prospective Study §
    Yannis Préau, Sébastien Galie, Pauline Schaepelynck, Martine Armand, Denis Raccah
    Sensors.2021; 21(18): 6131.     CrossRef
  • A Hybrid Automata Approach for Monitoring the Patient in the Loop in Artificial Pancreas Systems
    Aleix Beneyto, Vicenç Puig, B. Wayne Bequette, Josep Vehi
    Sensors.2021; 21(21): 7117.     CrossRef
  • Editors’ Choice—Review—From Polarography to Electrochemical Biosensors: The 100-Year Quest for Selectivity and Sensitivity
    William R. Heineman, Peter T. Kissinger, Kenneth R. Wehmeyer
    Journal of The Electrochemical Society.2021; 168(11): 116504.     CrossRef
  • Digital health and diabetes: experience from India
    Jothydev Kesavadev, Gopika Krishnan, Viswanathan Mohan
    Therapeutic Advances in Endocrinology and Metabolism.2021; 12: 204201882110546.     CrossRef
  • Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence
    Sun Joon Moon, Inha Jung, Cheol-Young Park
    Diabetes & Metabolism Journal.2021; 45(6): 813.     CrossRef
  • Factors Associated with Adherence to Self-Monitoring of Blood Glucose Among Young People with Type 1 Diabetes in China: A Cross-Sectional Study
    Wencong Lv, Jiaxin Luo, Qing Long, Jundi Yang, Xin Wang, Jia Guo
    Patient Preference and Adherence.2021; Volume 15: 2809.     CrossRef
  • Continuous glucose monitoring devices: A brief presentation (Review)
    Doina Mihai, Diana Stefan, Daniela Stegaru, Georgiana Bernea, Ileana Vacaroiu, Toma Papacocea, Mircea Lupușoru, Adriana Nica, Ovidiu Stiru, Dorin Dragos, Octavian Olaru
    Experimental and Therapeutic Medicine.2021;[Epub]     CrossRef
  • Acute glycemic variability on admission predicts the prognosis in hospitalized patients with coronary artery disease: a meta-analysis
    Zhaokun Pu, Lihong Lai, Xishan Yang, Yanyu Wang, Pingshuan Dong, Dan Wang, Yingli Xie, Zesen Han
    Endocrine.2020; 67(3): 526.     CrossRef
  • Glycemic profile of women with normoglycemia and gestational diabetes mellitus during early pregnancy using continuous glucose monitoring system
    Charandeep Singh, Yashdeep Gupta, Alpesh Goyal, Mani Kalaivani, Vineeta Garg, Juhi Bharti, Seema Singhal, Garima Kachhawa, Vidushi Kulshrestha, Rajesh Kumari, Reeta Mahey, Jai B Sharma, Neerja Bhatla, Rajesh Khadgawat, Nandita Gupta, Nikhil Tandon
    Diabetes Research and Clinical Practice.2020; 169: 108409.     CrossRef
  • Efficacy of Intermittently Scanned Continuous Glucose Monitoring in the Prevention of Recurrent Severe Hypoglycemia
    Timothy M.E. Davis, Penny Dwyer, Michelle England, P. Gerry Fegan, Wendy A. Davis
    Diabetes Technology & Therapeutics.2020; 22(5): 367.     CrossRef
  • How was the Diabetes Metabolism Journal added to MEDLINE?
    Hye Jin Yoo
    Science Editing.2020; 7(2): 201.     CrossRef
  • Applying Nanomaterials to Modern Biomedical Electrochemical Detection of Metabolites, Electrolytes, and Pathogens
    Itthipon Jeerapan, Thitaporn Sonsa-ard, Duangjai Nacapricha
    Chemosensors.2020; 8(3): 71.     CrossRef
  • Clinical Opportunities for Continuous Biosensing and Closed-Loop Therapies
    Jason Li, Jia Y. Liang, Steven J. Laken, Robert Langer, Giovanni Traverso
    Trends in Chemistry.2020; 2(4): 319.     CrossRef
  • A single-blind, randomised, crossover study to reduce hypoglycaemia risk during postprandial exercise with closed-loop insulin delivery in adults with type 1 diabetes: announced (with or without bolus reduction) vs unannounced exercise strategies
    Sémah Tagougui, Nadine Taleb, Laurent Legault, Corinne Suppère, Virginie Messier, Inès Boukabous, Azadeh Shohoudi, Martin Ladouceur, Rémi Rabasa-Lhoret
    Diabetologia.2020; 63(11): 2282.     CrossRef
  • Bimetallic PtAu alloy nanomaterials for nonenzymatic selective glucose sensing at low potential
    Lingling Lin, Shaohuang Weng, Yanjie Zheng, Xiyao Liu, Shaoming Ying, Feng Chen, Donghong You
    Journal of Electroanalytical Chemistry.2020; 865: 114147.     CrossRef
  • Type 1 Diabetes in Youth and Technology-Based Advances in Management
    Christopher Ferber, Catherine S. Mao, Jennifer K. Yee
    Advances in Pediatrics.2020; 67: 73.     CrossRef
  • Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors
    Martina Vettoretti, Giacomo Cappon, Andrea Facchinetti, Giovanni Sparacino
    Sensors.2020; 20(14): 3870.     CrossRef
  • Efficacy and safety of evogliptin treatment in patients with type 2 diabetes: A multicentre, active‐controlled, randomized, double‐blind study with open‐label extension (the EVERGREEN study)
    Gyuri Kim, Soo Lim, Hyuk‐Sang Kwon, Ie B. Park, Kyu J. Ahn, Cheol‐Young Park, Su K. Kwon, Hye S. Kim, Seok W. Park, Sin G. Kim, Min K. Moon, Eun S. Kim, Choon H. Chung, Kang S. Park, Mikyung Kim, Dong J. Chung, Chang B. Lee, Tae H. Kim, Moon‐Kyu Lee
    Diabetes, Obesity and Metabolism.2020; 22(9): 1527.     CrossRef
  • Association Between Continuous Glucose Monitoring-Derived Time in Range, Other Core Metrics, and Albuminuria in Type 2 Diabetes
    Jee Hee Yoo, Min Sun Choi, Jiyeon Ahn, Sung Woon Park, Yejin Kim, Kyu Yeon Hur, Sang-Man Jin, Gyuri Kim, Jae Hyeon Kim
    Diabetes Technology & Therapeutics.2020; 22(10): 768.     CrossRef
  • A New Approach to Determining Liquid Concentration Using Multiband Annular Ring Microwave Sensor and Polarity Correlator
    Waleed Sethi, Ahmed Ibrahim, Khaled Issa, Ali Albishi, Saleh Alshebeili
    Electronics.2020; 9(10): 1616.     CrossRef
  • Estrategia terapéutica en el paciente diabético (I). Empoderamiento del paciente y formación. Objetivos terapéuticos. Estilo de vida, alimentación, vacunación y consejos al paciente diabético
    F.B. Rivas Sánchez, J. Sanz Cánovas, J. Martín Carmona, S. Jansen Chaparro
    Medicine - Programa de Formación Médica Continuada Acreditado.2020; 13(17): 943.     CrossRef
  • Current status of continuous glucose monitoring among Korean children and adolescents with type 1 diabetes mellitus
    Jae Hyun Kim
    Annals of Pediatric Endocrinology & Metabolism.2020; 25(3): 145.     CrossRef
  • Towards sensor-based calving detection in the rangelands: a systematic review of credible behavioral and physiological indicators
    Anita Z Chang, David L Swain, Mark G Trotter
    Translational Animal Science.2020;[Epub]     CrossRef
  • Electrochemical glucose sensors in diabetes management: an updated review (2010–2020)
    Hazhir Teymourian, Abbas Barfidokht, Joseph Wang
    Chemical Society Reviews.2020; 49(21): 7671.     CrossRef
  • An analytical approach to determine the optimal duration of continuous glucose monitoring data required to reliably estimate time in hypoglycemia
    Nunzio Camerlingo, Martina Vettoretti, Andrea Facchinetti, Giovanni Sparacino, Julia K. Mader, Pratik Choudhary, Simone Del Favero
    Scientific Reports.2020;[Epub]     CrossRef
  • Smartphone-Based Data Collection in Ophthalmology
    Florian Philipp Raber, Rokas Gerbutavicius, Armin Wolf, Karsten Kortüm
    Klinische Monatsblätter für Augenheilkunde.2020; 237(12): 1420.     CrossRef
  • Glycemic Status Assessment by the Latest Glucose Monitoring Technologies
    Ilaria Malandrucco, Benedetta Russo, Fabiana Picconi, Marika Menduni, Simona Frontoni
    International Journal of Molecular Sciences.2020; 21(21): 8243.     CrossRef
  • Medical Nutrition Therapy Using Continuous Glucose Monitoring System
    Mee Ra Kweon
    The Journal of Korean Diabetes.2020; 21(4): 216.     CrossRef
  • Use of Flash Glucose Monitoring in Patients on Intensive Insulin Treatment
    Jun Sung Moon
    The Journal of Korean Diabetes.2020; 21(4): 184.     CrossRef
  • Data Analysis and Accuracy Evaluation of a Continuous Glucose-Monitoring Device
    Lijun Cai, Wancheng Ge, Zhigang Zhu, Xueling Zhao, Zhanhong Li
    Journal of Sensors.2019; 2019: 1.     CrossRef
  • Development of an Error Model for a Factory-Calibrated Continuous Glucose Monitoring Sensor with 10-Day Lifetime
    Martina Vettoretti, Cristina Battocchio, Giovanni Sparacino, Andrea Facchinetti
    Sensors.2019; 19(23): 5320.     CrossRef

Diabetes Metab J : Diabetes & Metabolism Journal