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Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015) (Diabetes Metab J 2021;45:115-9)
Seong-Su Moon, Chong Hwa Kim, Seon Mee Kang, Eun Sook Kim, Tae Jung Oh, Jae-Seung Yun, Ho Chan Cho, Dae Jung Kim, Tae Sun Park
Diabetes Metab J. 2021;45(3):459-460.   Published online May 25, 2021
DOI: https://doi.org/10.4093/dmj.2021.0084
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  • 1 Crossref
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  • Comorbidity Patterns and Management in Inpatients with Endocrine Diseases by Age Groups in South Korea: Nationwide Data
    Sung-Soo Kim, Hun-Sung Kim
    Journal of Personalized Medicine.2023; 14(1): 42.     CrossRef
Brief Report
Complications
Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015)
Seong-Su Moon, Chong Hwa Kim, Seon Mee Kang, Eun Sook Kim, Tae Jung Oh, Jae-Seung Yun, Ho Chan Cho, Dae Jung Kim, Tae Sun Park
Diabetes Metab J. 2021;45(1):115-119.   Published online December 18, 2020
DOI: https://doi.org/10.4093/dmj.2020.0120
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  • 275 Download
  • 9 Web of Science
  • 10 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
This report presents the status of diabetic neuropathy (DN) in Korea as determined using a National Health Insurance ServiceNational Sample Cohort (NHIS-NSC). Annual prevalences of DN were estimated by age and gender using descriptive statistics. Pharmacological treatments for DN were also analyzed. The annual prevalence of DN increased from 24.9% in 2006 to 26.6% in 2007, and thereafter, gradually subsided to 20.8% in 2015. In most cases, pharmacological treatments involved a single drug, which accounted for 91.6% of total prescriptions in 2015. The most commonly used drugs (in decreasing order) were thioctic acid, an anti-convulsive agent, or a tricyclic antidepressant. In conclusion, the prevalence of DN decreased over the 10-year study period. Thioctic acid monotherapy was usually prescribed for DN. To reduce the socio-economic burden of DN, more attention should be paid to the diagnosis of this condition and to the appropriate management of patients.

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  • Risk of cardiovascular events according to the tricyclic antidepressant dosage in patients with chronic pain: a retrospective cohort study
    Hyunji Koo, Seung Hun You, Sewon Park, Kyeong Hye Jeong, Nakyung Jeon, Sun-Young Jung
    European Journal of Clinical Pharmacology.2023; 79(1): 159.     CrossRef
  • How does diabetic peripheral neuropathy impact patients' burden of illness and the economy? A retrospective study in Beijing, China
    Qi Pan, Sijia Fei, Lina Zhang, Huan Chen, Jingyi Luo, Weihao Wang, Fei Xiao, Lixin Guo
    Frontiers in Public Health.2023;[Epub]     CrossRef
  • Chronic disease management program applied to type 2 diabetes patients and prevention of diabetic complications: a retrospective cohort study using nationwide data
    Min Kyung Hyun, Jang Won Lee, Seung-Hyun Ko
    BMC Public Health.2023;[Epub]     CrossRef
  • Pharmacological and Nonpharmacological Treatments for Painful Diabetic Peripheral Neuropathy
    Han Na Jang, Tae Jung Oh
    Diabetes & Metabolism Journal.2023; 47(6): 743.     CrossRef
  • Are herbal medicines alone or in combination for diabetic peripheral neuropathy more effective than methylcobalamin alone? A systematic review and meta-analysis
    Chang-Woo Lee, Joon-Soo Jin, Seungwon Kwon, Chul Jin, Seung-Yeon Cho, Seong-Uk Park, Woo-Sang Jung, Sang-Kwan Moon, Jung-Mi Park, Chang-Nam Ko, Ki-Ho Cho
    Complementary Therapies in Clinical Practice.2022; 49: 101657.     CrossRef
  • Pathogenesis and Treatment of Diabetic Peripheral Neuropathy
    Seon Mee Kang
    The Journal of Korean Diabetes.2022; 23(4): 222.     CrossRef
  • Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015) (Diabetes Metab J 2021;45:115-9)
    Seong-Su Moon, Chong Hwa Kim, Seon Mee Kang, Eun Sook Kim, Tae Jung Oh, Jae-Seung Yun, Ho Chan Cho, Dae Jung Kim, Tae Sun Park
    Diabetes & Metabolism Journal.2021; 45(3): 459.     CrossRef
  • Status of Diabetic Neuropathy in Korea: A National Health Insurance Service-National Sample Cohort Analysis (2006 to 2015) (Diabetes Metab J 2021;45:115-9)
    Tímea Csákvári, Diána Elmer, Lilla Horváth, Imre Boncz
    Diabetes & Metabolism Journal.2021; 45(3): 454.     CrossRef
  • Time to Reach Target Glycosylated Hemoglobin Is Associated with Long-Term Durable Glycemic Control and Risk of Diabetic Complications in Patients with Newly Diagnosed Type 2 Diabetes Mellitus: A 6-Year Observational Study (Diabetes Metab J 2021;45:368-78)
    Ja Young Jeon
    Diabetes & Metabolism Journal.2021; 45(4): 613.     CrossRef
  • Diffculties and ways to overcome them in selection of therapy for pain syndromes in patients with diabetes mellitus
    K. A. Makhinov, P. R. Kamchatnov
    Medical alphabet.2021; (22): 25.     CrossRef
Original Articles
A Survey on Ubiquitous Healthcare Service Demand among Diabetic Patients
Soo Lim, So-Youn Kim, Jung Im Kim, Min Kyung Kwon, Sei Jin Min, Soo Young Yoo, Seon Mee Kang, Hong Il Kim, Hye Seung Jung, Kyong Soo Park, Jun Oh Ryu, Hayley Shin, Hak Chul Jang
Diabetes Metab J. 2011;35(1):50-57.   Published online February 28, 2011
DOI: https://doi.org/10.4093/dmj.2011.35.1.50
  • 6,795 View
  • 30 Download
  • 23 Crossref
AbstractAbstract PDFPubReader   
Background

Advanced information technology can be used when developing diagnostic and treatment strategies to provide better care for diabetic patients. However, the levels of need and demand for the use of technological advances have not been investigated in diabetic patients. We proposed and developed an individualized, ubiquitous (U)-healthcare service using advanced information technology for more effective glucose control. Prior to our service initiation, we surveyed patient needs and other pertinent information.

Methods

During August 2009, we conducted a 34-item questionnaire survey among patients with diabetes who were older than 40 years in two certain hospitals in Korea.

Results

The mean age of the 228 participants was 61.2±9 years, and males made up 49.1% of the sample. Seventy-one percent replied that they wanted individualized healthcare service, and they also wanted their health information to be delivered through mobile devices such as a cellular phone or a personal digital assistant (40.4%). Most patients had never heard of U-healthcare services (81.1%); however, after explaining the concept, 71.1% of participants responded that they would use the service if it was provided. Despite their willingness, participants were concerned about technical difficulty in using the service (26.3%) as well as the cost of the service (29.8%).

Conclusion

The current study suggests that more than 70% of diabetic patients are interested in using U-healthcare services. To encourage widespread use, the application program or device of U-healthcare services should be simple, easy to use and affordable while also including a policy for the protection of private information.

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  • Willingness of diabetes mellitus patients to use mHealth applications and its associated factors for self-care management in a low-income country: an input for digital health implementation
    Agmasie Damtew Walle, Tigist Andargie Ferede, Adamu Ambachew Shibabaw, Sisay Maru Wubante, Habtamu Alganeh Guadie, Chalachew Msganaw Yehula, Addisalem Workie Demsash
    BMJ Health & Care Informatics Online.2023; 30(1): e100761.     CrossRef
  • Development and Operation of a Video Teleconsultation System Using Integrated Medical Equipment Gateway: a National Project for Workers in Underserved Areas
    Hyun Sang Park, Kwang il Kim, Jae Young Soh, Young Ho Hyun, Bang Eun Lee, Jong Hwa Lee, Jung Gwon Jo, Han Chae Lee, Hwa Sun Kim
    Journal of Medical Systems.2020;[Epub]     CrossRef
  • Patient experience with an educational mobile health application: A pilot study on usability and feasibility in a Saudi population
    Sireen Abdul Rahim Shilbayeh, Sahar Abd El Rahman Ismail, Meihua Qian
    Cogent Psychology.2020;[Epub]     CrossRef
  • Smart Care Based on Telemonitoring and Telemedicine for Type 2 Diabetes Care: Multi-Center Randomized Controlled Trial
    Ji Yun Jeong, Jae-Han Jeon, Kwi-Hyun Bae, Yeon-Kyung Choi, Keun-Gyu Park, Jung-Guk Kim, Kyu Chang Won, Bong Soo Cha, Chul Woo Ahn, Dong Won Kim, Chang Hee Lee, In-Kyu Lee
    Telemedicine and e-Health.2018; 24(8): 604.     CrossRef
  • Satisfaction Survey on Information Technology-Based Glucose Monitoring System Targeting Diabetes Mellitus in Private Local Clinics in Korea
    Hun-Sung Kim, So Jung Yang, Yoo Jin Jeong, Young-Eun Kim, Seok-Won Hong, Jae Hyoung Cho
    Diabetes & Metabolism Journal.2017; 41(3): 213.     CrossRef
  • Willingness of patients with diabetes to use an ICT-based self-management tool: a cross-sectional study
    Tomomi Shibuta, Kayo Waki, Nobuko Tomizawa, Ayumi Igarashi, Noriko Yamamoto-Mitani, Satoko Yamaguchi, Hideo Fujita, Shigeko Kimura, Katsuhito Fujiu, Hironori Waki, Yoshihiko Izumida, Takayoshi Sasako, Masatoshi Kobayashi, Ryo Suzuki, Toshimasa Yamauchi, T
    BMJ Open Diabetes Research & Care.2017; 5(1): e000322.     CrossRef
  • Evaluating the Effect of Web-Based Iranian Diabetic Personal Health Record App on Self-Care Status and Clinical Indicators: Randomized Controlled Trial
    Amirabbas Azizi, Robab Aboutorabi, Zahra Mazloum-Khorasani, Monavar Afzal-Aghaea, Hamed Tabesh, Mahmood Tara
    JMIR Medical Informatics.2016; 4(4): e32.     CrossRef
  • Development, Validation, and Evaluation of Web-Based Iranian Diabetic Personal Health Record: Rationale for and Protocol of a Randomized Controlled Trial
    Amirabbas Azizi, Robab Aboutorabi, Zahra Mazloum-Khorasani, Monavar Afzal-Aghaea, Mahmood Tara
    JMIR Research Protocols.2016; 5(1): e39.     CrossRef
  • Randomized, Open-Label, Parallel Group Study to Evaluate the Effect of Internet-Based Glucose Management System on Subjects with Diabetes in China
    Hun-Sung Kim, Chenglin Sun, So Jung Yang, Lin Sun, Fei Li, In Young Choi, Jae-Hyoung Cho, Guixia Wang, Kun-Ho Yoon
    Telemedicine and e-Health.2016; 22(8): 666.     CrossRef
  • Environment and Its Influence on Health and Demographics in South Korea
    Ramiro Bravo Santisteban, Young Kim, Umar Farooq, Tae-Seong Kim, Sekyoung Youm, Seung-Hun Park
    International Journal of Environmental Research and Public Health.2016; 13(2): 183.     CrossRef
  • U-Healthcare Center Service in Busan City, South Korea: An Empirical Analysis and the Results of 1 Year of Service
    Ramiro D. Bravo Santisteban, Sekyoung Youm, Seung-Hun Park
    Telemedicine and e-Health.2015; 21(10): 774.     CrossRef
  • Users’ perception on telemedicine service: a comparative study of public healthcare and private healthcare
    Mi Jung Rho, Kun Ho Yoon, Hun-Sung Kim, In Young Choi
    Multimedia Tools and Applications.2015; 74(7): 2483.     CrossRef
  • An Activity Recognition Model Using Inertial Sensor Nodes in a Wireless Sensor Network for Frozen Shoulder Rehabilitation Exercises
    Hsueh-Chun Lin, Shu-Yin Chiang, Kai Lee, Yao-Chiang Kan
    Sensors.2015; 15(1): 2181.     CrossRef
  • Current Clinical Status of Telehealth in Korea: Categories, Scientific Basis, and Obstacles
    Hun-Sung Kim, Hyunah Kim, Suehyun Lee, Kye Hwa Lee, Ju Han Kim
    Healthcare Informatics Research.2015; 21(4): 244.     CrossRef
  • New Directions in Chronic Disease Management
    Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon
    Endocrinology and Metabolism.2015; 30(2): 159.     CrossRef
  • Using mobile phones in healthcare management for the elderly
    Hun-Sung Kim, Kye-Hwa Lee, Hyunah Kim, Ju Han Kim
    Maturitas.2014; 79(4): 381.     CrossRef
  • Future Prospects of Health Management Systems Using Cellular Phones
    Hun-Sung Kim, Yunji Hwang, Jae-Ho Lee, Hye Young Oh, Yi-Jun Kim, Hyeon Yoon Kwon, Hyoseung Kang, Hyunah Kim, Rae Woong Park, Ju Han Kim
    Telemedicine and e-Health.2014; 20(6): 544.     CrossRef
  • Exploring the Relationship Among User Satisfaction, Compliance, and Clinical Outcomes of Telemedicine Services for Glucose Control
    Mi Jung Rho, Si Ra Kim, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Seong K. Mun, In Young Choi
    Telemedicine and e-Health.2014; 20(8): 712.     CrossRef
  • Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany
    Rolf-Dietrich Berndt, Claude Takenga, Petra Preik, Sebastian Kuehn, Luise Berndt, Herbert Mayer, Alexander Kaps, Ralf Schiel
    Journal of Personalized Medicine.2014; 4(2): 200.     CrossRef
  • Perception of Influencing Factors on Acceptance of Mobile Health Monitoring Service: A Comparison between Users and Non-users
    Jaebeom Lee, Mi Jung Rho
    Healthcare Informatics Research.2013; 19(3): 167.     CrossRef
  • Telerehabilitation Needs: A Bidirectional Survey of Health Professionals and Individuals with Spinal Cord Injury in South Korea
    Jongbae Kim, Shinyoung Lim, Jayeon Yun, Da-hye Kim
    Telemedicine and e-Health.2012; 18(9): 713.     CrossRef
  • Development of a smartphone-based diabetes self-care management system
    Sang Youl Rhee, Jeong-taek Woo, Young Seol Kim, Young Kil Choi
    Personalized Medicine Universe.2012; 1(1): 85.     CrossRef
  • Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines
    Taridzo Chomutare, Luis Fernandez-Luque, Eirik Årsand, Gunnar Hartvigsen
    Journal of Medical Internet Research.2011; 13(3): e65.     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
  • 4,854 View
  • 50 Download
  • 14 Crossref
AbstractAbstract PDFPubReader   
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.

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  • 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
  • Correlation between short- and mid-term hemoglobin A1c and glycemic control determined by continuous glucose monitoring
    Jen-Hung Huang, Yung-Kuo Lin, Ting-Wei Lee, Han-Wen Liu, Yu-Mei Chien, Yu-Chun Hsueh, Ting-I Lee, Yi-Jen Chen
    Diabetology & Metabolic Syndrome.2021;[Epub]     CrossRef
  • Accuracy of Flash Glucose Monitoring During Postprandial Rest and Different Walking Conditions in Overweight or Obese Young Adults
    Xiaoyuan Zhang, Fenghua Sun, Waris Wongpipit, Wendy Y. J. Huang, Stephen H. S. Wong
    Frontiers in Physiology.2021;[Epub]     CrossRef
  • The MEDGICarb-Study: Design of a multi-center randomized controlled trial to determine the differential health-promoting effects of low- and high-glycemic index Mediterranean-style eating patterns
    Robert E. Bergia, Izabela Biskup, Rosalba Giacco, Giuseppina Costabile, Savanna Gray, Amy Wright, Marilena Vitale, Wayne W. Campbell, Rikard Landberg, Gabriele Riccardi
    Contemporary Clinical Trials Communications.2020; 19: 100640.     CrossRef
  • A genetic programming-based regression for extrapolating a blood glucose-dynamics model from interstitial glucose measurements and their first derivatives
    I. De Falco, A. Della Cioppa, A. Giugliano, A. Marcelli, T. Koutny, M. Krcma, U. Scafuri, E. Tarantino
    Applied Soft Computing.2019; 77: 316.     CrossRef
  • Genetic Programming-based induction of a glucose-dynamics model for telemedicine
    Ivanoe De Falco, Antonio Della Cioppa, Tomas Koutny, Michal Krcma, Umberto Scafuri, Ernesto Tarantino
    Journal of Network and Computer Applications.2018; 119: 1.     CrossRef
  • A high-accuracy measurement method of glucose concentration in interstitial fluid based on microdialysis
    Dachao Li, Qingmei Xu, Yu Liu, Ridong Wang, Kexin Xu, Haixia Yu
    Measurement Science and Technology.2017; 28(11): 115701.     CrossRef
  • Effects of Higher Dietary Protein and Fiber Intakes at Breakfast on Postprandial Glucose, Insulin, and 24-h Interstitial Glucose in Overweight Adults
    Akua Amankwaah, R. Sayer, Amy Wright, Ningning Chen, Megan McCrory, Wayne Campbell
    Nutrients.2017; 9(4): 352.     CrossRef
  • High Surface Area Electrodes Generated via Electrochemical Roughening Improve the Signaling of Electrochemical Aptamer-Based Biosensors
    Netzahualcóyotl Arroyo-Currás, Karen Scida, Kyle L. Ploense, Tod E. Kippin, Kevin W. Plaxco
    Analytical Chemistry.2017; 89(22): 12185.     CrossRef
  • Hyperglycemia-Induced Changes in Hyaluronan Contribute to Impaired Skin Wound Healing in Diabetes: Review and Perspective
    Sajina Shakya, Yan Wang, Judith A. Mack, Edward V. Maytin
    International Journal of Cell Biology.2015; 2015: 1.     CrossRef
  • Hypoglycemia in everyday life after gastric bypass and duodenal switch
    Niclas Abrahamsson, Britt Edén Engström, Magnus Sundbom, F Anders Karlsson
    European Journal of Endocrinology.2015; 173(1): 91.     CrossRef
  • The use of reinforcement learning algorithms to meet the challenges of an artificial pancreas
    Melanie K Bothe, Luke Dickens, Katrin Reichel, Arn Tellmann, Björn Ellger, Martin Westphal, Ahmed A Faisal
    Expert Review of Medical Devices.2013; 10(5): 661.     CrossRef
  • Continuous glucose monitoring: current clinical use
    Hun‐Sung Kim, Jeong‐Ah Shin, Jin‐Sun Chang, Jae‐Hyoung Cho, Ho‐Young Son, Kun‐Ho Yoon
    Diabetes/Metabolism Research and Reviews.2012; 28(s2): 73.     CrossRef
  • Correlations of Glucose Levels in Interstitial Fluid Estimated by Continuous Glucose Monitoring Systems and Venous Plasma
    Byung-Joon Kim
    Korean Diabetes Journal.2010; 34(6): 338.     CrossRef

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