Diabetes & Metabolism Journal

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Development of Various Diabetes Prediction Models Using Machine Learning Techniques: Juyoung Shin, Jaewon Kim, Chanjung Lee, Joon Young Yoon, Seyeon Kim, Seungjae Song, Hun-Sung Kim; Diabetes Metab J. 2022;46(4):650-657. Published online March 11, 2022; DOI: https://doi.org/10.4093/dmj.2021.0115

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Background
There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters.
Methods
Two sets of variables were used to develop eight DM prediction models. One set comprised 62 easily accessible examination results of commonly used variables from a tertiary university hospital. The second set comprised 27 of the 62 variables included in the national routine health checkups. Gradient boosting and random forest algorithms were used to develop the models. Internal validation was performed using the stratified 10-fold cross-validation method.
Results
The area under the receiver operating characteristic curve (ROC-AUC) for the 62-variable DM model making 12-month predictions for subjects without diabetes was the largest (0.928) among those of the eight DM prediction models. The ROC-AUC dropped by more than 0.04 when training with the simplified 27-variable set but still showed fairly good performance with ROC-AUCs between 0.842 and 0.880. The accuracy was up to 11.5% higher (from 0.807 to 0.714) when fasting glucose was included.
Conclusion
We created easily applicable diabetes prediction models that deliver good performance using parameters commonly assessed during tertiary university hospital and national routine health checkups. We plan to perform prospective external validation, hoping that the developed DM prediction models will be widely used in clinical practice.

Citations

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Predictive modeling for the development of diabetes mellitus using key factors in various machine learning approaches
Marenao Tanaka, Yukinori Akiyama, Kazuma Mori, Itaru Hosaka, Kenichi Kato, Keisuke Endo, Toshifumi Ogawa, Tatsuya Sato, Toru Suzuki, Toshiyuki Yano, Hirofumi Ohnishi, Nagisa Hanawa, Masato Furuhashi
Diabetes Epidemiology and Management.2024; 13: 100191. CrossRef
Validation of the Framingham Diabetes Risk Model Using Community-Based KoGES Data
Hye Ah Lee, Hyesook Park, Young Sun Hong
Journal of Korean Medical Science.2024;[Epub] CrossRef
Integrated Embedded system for detecting diabetes mellitus using various machine learning techniques
Rishita Konda, Anuraag Ramineni, Jayashree J, Niharika Singavajhala, Sai Akshaj Vanka
EAI Endorsed Transactions on Pervasive Health and Technology.2024;[Epub] CrossRef
Predicting diabetes in adults: identifying important features in unbalanced data over a 5-year cohort study using machine learning algorithm
Maryam Talebi Moghaddam, Yones Jahani, Zahra Arefzadeh, Azizallah Dehghan, Mohsen Khaleghi, Mehdi Sharafi, Ghasem Nikfar
BMC Medical Research Methodology.2024;[Epub] CrossRef
The Present and Future of Artificial Intelligence-Based Medical Image in Diabetes Mellitus: Focus on Analytical Methods and Limitations of Clinical Use
Ji-Won Chun, Hun-Sung Kim
Journal of Korean Medical Science.2023;[Epub] CrossRef
Machine learning for predicting diabetic metabolism in the Indian population using polar metabolomic and lipidomic features
Nikita Jain, Bhaumik Patel, Manjesh Hanawal, Anurag R. Lila, Saba Memon, Tushar Bandgar, Ashutosh Kumar
Metabolomics.2023;[Epub] CrossRef
Retrospective cohort analysis comparing changes in blood glucose level and body composition according to changes in thyroid‐stimulating hormone level
Hyunah Kim, Da Young Jung, Seung‐Hwan Lee, Jae‐Hyoung Cho, Hyeon Woo Yim, Hun‐Sung Kim
Journal of Diabetes.2022; 14(9): 620. CrossRef
Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
Juyoung Shin, Joonyub Lee, Taehoon Ko, Kanghyuck Lee, Yera Choi, Hun-Sung Kim
Journal of Personalized Medicine.2022; 12(11): 1899. CrossRef

Guideline/Fact Sheet
Diabetes Fact Sheets in Korea, 2020: An Appraisal of Current Status: Chan-Hee Jung, Jang Won Son, Shinae Kang, Won Jun Kim, Hun-Sung Kim, Hae Soon Kim, Mihae Seo, Hye-Jung Shin, Seong-Su Lee, Su Jin Jeong, Yongin Cho, Seung Jin Han, Hyang Mi Jang, Mira Rho, Shinbi Lee, Mihyun Koo, Been Yoo, Jung-Wha Moon, Hye Young Lee, Jae-Seung Yun, Sun Young Kim, Sung Rae Kim, In-Kyung Jeong, Ji-Oh Mok, Kun Ho Yoon; Diabetes Metab J. 2021;45(1):1-10. Published online January 13, 2021; DOI: https://doi.org/10.4093/dmj.2020.0254

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Background
This study aimed to investigate the recent prevalence, management, and comorbidities of diabetes among Korean adults aged ≥30 years by analyzing nationally representative data.
Methods
This study used data from the Korea National Health and Nutrition Examination Survey from 2016 to 2018, and the percentage and total number of people ≥30 years of age with diabetes and impaired fasting glucose (IFG) were estimated.
Results
In 2018, 13.8% of Korean adults aged ≥30 years had diabetes, and adults aged ≥65 years showed a prevalence rate of 28%. The prevalence of IFG was 26.9% in adults aged ≥30 years. From 2016 to 2018, 35% of the subjects with diabetes were not aware of their condition. Regarding comorbidities, 53.2% and 61.3% were obese and hypertensive, respectively, and 72% had hypercholesterolemia as defined by low-density lipoprotein cholesterol (LDL-C) ≥100 mg/dL in people with diabetes. Of the subjects with diabetes, 43.7% had both hypertension and hypercholesterolemia. With regard to glycemic control, only 28.3% reached the target level of <6.5%. Moreover, only 11.5% of subjects with diabetes met all three targets of glycosylated hemoglobin, blood pressure, and LDL-C. The percentage of energy intake from carbohydrates was higher in diabetes patients than in those without diabetes, while that from protein and fat was lower in subjects with diabetes.
Conclusion
The high prevalence and low control rate of diabetes and its comorbidities in Korean adults were confirmed. More stringent efforts are needed to improve the comprehensive management of diabetes to reduce diabetes-related morbidity and mortality.

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Response

Response: Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence (Diabetes Metab J 2020;44:555-65): Jeongmin Lee, Hun-Sung Kim; Diabetes Metab J. 2020;44(5):779-780. Published online October 21, 2020; DOI: https://doi.org/10.4093/dmj.2020.0215

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Original Articles

Complications
Differences in Clinical Outcomes between Patients with and without Hypoglycemia during Hospitalization: A Retrospective Study Using Real-World Evidence: Jeongmin Lee, Tong Min Kim, Hyunah Kim, Seung-Hwan Lee, Jae Hyoung Cho, Hyunyong Lee, Hyeon Woo Yim, Kun-Ho Yoon, Hun-Sung Kim; Diabetes Metab J. 2020;44(4):555-565. Published online May 8, 2020; DOI: https://doi.org/10.4093/dmj.2019.0064

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Abstract PDF Supplementary Material PubReader ePub

Background

Some patients admitted to hospitals for glycemic control experience hypoglycemia despite regular meals and despite adhering to standard blood glucose control protocols. Different factors can have a negative impact on blood glucose control and prognosis after discharge. This study investigated risk factors for hypoglycemia and its effects on glycemic control during the hospitalization of patients in the general ward.

Methods

This retrospective study included patients who were admitted between 2009 and 2018. Patients were provided regular meals at fixed times according to ideal body weights during hospitalization. We categorized the patients into two groups: those with and those without hypoglycemia during hospitalization.

Results

Of the 3,031 patients, 379 experienced at least one episode of hypoglycemia during hospitalization (HYPO group). Hypoglycemia occurred more frequently particularly in cases of premixed insulin therapy. Compared with the control group, the HYPO group was older (61.0±16.8 years vs. 59.1±16.5 years, P=0.035), with more females (60.4% vs. 49.6%, P<0.001), lower body mass index (BMI) (23.5±4.2 kg/m² vs. 25.1±4.4 kg/m², P<0.001), and higher prevalence of type 1 diabetes mellitus (6.1% vs. 2.6%, P<0.001), They had longer hospital stay (11.1±13.5 days vs. 7.6±4.6 days, P<0.001). After discharge the HYPO group had lower glycosylated hemoglobin reduction rate (−2.0%±0.2% vs. −2.5%±0.1%, P=0.003) and tended to have more frequent cases of cardiovascular disease.

Conclusion

Hypoglycemia occurred more frequently in older female patients with lower BMI and was associated with longer hospital stay and poorer glycemic control after discharge. Therefore, clinicians must carefully ensure that patients do not experience hypoglycemia during hospitalization.

Citations

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Epidemiology
Diabetes Fact Sheets in Korea, 2018: An Appraisal of Current Status: Bo-Yeon Kim, Jong Chul Won, Jae Hyuk Lee, Hun-Sung Kim, Jung Hwan Park, Kyoung Hwa Ha, Kyu Chang Won, Dae Jung Kim, Kyong Soo Park; Diabetes Metab J. 2019;43(4):487-494. Published online July 17, 2019; DOI: https://doi.org/10.4093/dmj.2019.0067

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Background

The objective of this study was to investigate the prevalence, management, and comorbidities of diabetes among Korean adults aged 30 years and older.

Methods

This study used 2013 to 2016 data from the Korea National Health and Nutrition Examination Survey, a nationally-representative survey of the Korean population. Diabetes was defined as fasting glucose ≥126 mg/dL, current use of antidiabetic medication, a previous history of diabetes, or glycosylated hemoglobin (HbA1c) ≥6.5%.

Results

In 2016, 14.4% (approximately 5.02 million) of Korean adults had diabetes. The prevalence of impaired fasting glucose was 25.3% (8.71 million). From 2013 to 2016, the awareness, control, and treatment rates for diabetes were 62.6%, 56.7%, and 25.1%, respectively. People with diabetes had the following comorbidities: obesity (50.4%), abdominal obesity (47.8%), hypertension (55.3%), and hypercholesterolemia (34.9%). The 25.1%, 68.4%, and 44.2% of people with diabetes achieved HbA1c <6.5%, blood pressure <140/85 mm Hg, and low density lipoprotein cholesterol <100 mg/dL. Only 8.4% of people with diabetes had good control of all three targets.

Conclusion

This study confirms that diabetes is as an important public health problem. Efforts should be made to increase awareness, detection, and comprehensive management of diabetes to reduce diabetes-related morbidity and mortality.

Citations

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Others
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 Metab J. 2017;41(3):213-222. Published online June 21, 2017; DOI: https://doi.org/10.4093/dmj.2017.41.3.213

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Abstract PDF PubReader

Background

Private local clinics in Korea have little experience with information technology (IT)-based glucose monitoring (ITGM). Our aim is to examine user satisfaction and the possibility of using ITGM service practically.

Methods

Patients sent their blood glucose levels to physicians in local clinics. The physicians reviewed the blood glucose values online and provided personal consultations through text messaging or phone calls. Thereafter, a satisfaction survey on the ITGM service, the modified Morisky scale, and patient assessment of chronic illness care were administered.

Results

One hundred and seventy patients from seven private local clinics used the ITGM. Overall satisfaction, including that about the ITGM service, the device, and its usefulness, was rated higher than “mostly satisfied” (score 4.2±0.8 out of 5.0) and even higher among the elderly. Satisfaction was positively associated with age, especially in those older than 60 years. The main reason for intent for future use of the service was the time/place flexibility. Highly motivated patients tended to answer positively regarding information satisfaction (P=0.0377).

Conclusion

Our study is the first to investigate ITGM satisfaction in private local clinics. The feasibility of users utilizing ITGM should be clarified, and future clinical research on the service's clinical effects and cost-benefit analysis is needed.

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Luca Schiliró Tristão, Guilherme Tavares, Francisco Tustumi, Wanderley Marques Bernardo, Márcio Luis Duarte, Maria Stella Peccin, Lucas Ribeiro dos Santos
Current Diabetes Reviews.2023;[Epub] CrossRef
The effectiveness of mobile application for monitoring diabetes mellitus and hypertension in the adult and elderly population: systematic review and meta-analysis
Emily de Souza Ferreira, Fernanda de Aguiar Franco, Marina Marilac dos Santos Lara, André Amaral Levcovitz, Mateus Araújo Dias, Tiago Ricardo Moreira, Ary Henrique Morais de Oliveira, Rosângela Minardi Mitre Cotta
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International Journal of Environmental Research and Public Health.2021; 18(5): 2502. CrossRef
Lessons from Use of Continuous Glucose Monitoring Systems in Digital Healthcare
Hun-Sung Kim, Kun-Ho Yoon
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Apprehensions about Excessive Belief in Digital Therapeutics: Points of Concern Excluding Merits
Hun-Sung Kim
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Mobile Phone–Based Telemedicine Practice in Older Chinese Patients with Type 2 Diabetes Mellitus: Randomized Controlled Trial
Chenglin Sun, Lin Sun, Shugang Xi, Hong Zhang, Huan Wang, Yakun Feng, Yufeng Deng, Haimin Wang, Xianchao Xiao, Gang Wang, Yuan Gao, Guixia Wang
JMIR mHealth and uHealth.2019; 7(1): e10664. CrossRef

Clinical Care/Education
Physician-Directed Diabetes Education without a Medication Change and Associated Patient Outcomes: Hun-Sung Kim, Hyunah Kim, Hae-Kyung Yang, Eun Young Lee, Yoo Jin Jeong, Tong Min Kim, So Jung Yang, Seo Yeon Baik, Seung-Hwan Lee, Jae Hyoung Cho, In Young Choi, Hyeon Woo Yim, Bong-Yun Cha; Diabetes Metab J. 2017;41(3):187-194. Published online May 12, 2017; DOI: https://doi.org/10.4093/dmj.2017.41.3.187

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Background

When patients with diabetes mellitus (DM) are first referred to a hospital from primary health care clinics, physicians have to decide whether to administer an oral hypoglycemic agent (OHA) immediately or postpone a medication change in favor of diabetes education regarding diet or exercise. The aim of this study was to determine the effect of diabetes education alone (without alterations in diabetes medication) on blood glucose levels.

Methods

The study was conducted between January 2009 and December 2013 and included patients with DM. The glycosylated hemoglobin (HbA1c) levels were evaluated at the first visit and after 3 months. During the first medical examination, a designated doctor also conducted a diabetes education session that mainly covered dietary management.

Results

Patients were divided into those who received no diabetic medications (n=66) and those who received an OHA (n=124). Education resulted in a marked decrease in HbA1c levels in the OHA group among patients who had DM for <1 year (from 7.0%±1.3% to 6.6%±0.9%, P=0.0092) and for 1 to 5 years (from 7.5%±1.8% to 6.9%±1.1%, P=0.0091). Those with DM >10 years showed a slightly lower HbA1c target achievement rate of <6.5% (odds ratio, 0.089; P=0.0024).

Conclusion

For patients who had DM for more than 5 years, higher doses or changes in medication were more effective than intensive active education. Therefore, individualized and customized education are needed for these patients. For patients with a shorter duration of DM, it may be more effective to provide initial intensive education for diabetes before prescribing medicines, such as OHAs.

Citations

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Management Status of Patients with Type 2 Diabetes Mellitus at General Hospitals in Korea: A 5-Year Follow-Up Study
Jin Hee Jung, Jung Hwa Lee, Hyang Mi Jang, Young Na, Hee Sun Choi, Yeon Hee Lee, Yang Gyo Kang, Na Rae Kim, Jeong Rim Lee, Bok Rye Song, Kang Hee Sim
The Journal of Korean Diabetes.2022; 23(1): 64. CrossRef
Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial
Da Young Lee, Seung-Hyun Yoo, Kyong Pil Min, Cheol-Young Park
JMIR mHealth and uHealth.2020; 8(9): e19153. CrossRef
Developing a multi-center clinical data mart of ACEI and ARB for real-world evidence (RWE)
Hun-Sung Kim, Sue Hyun Lee, Tong Min Kim, Ju Han Kim
Clinical Hypertension.2018;[Epub] CrossRef

Effects of 6-Month Sitagliptin Treatment on Insulin and Glucagon Responses in Korean Patients with Type 2 Diabetes Mellitus: Hae Kyung Yang, Borami Kang, Seung-Hwan Lee, Hun-Sung Kim, Kun-Ho Yoon, Bong-Yun Cha, Jae-Hyoung Cho; Diabetes Metab J. 2015;39(4):335-341. Published online July 17, 2015; DOI: https://doi.org/10.4093/dmj.2015.39.4.335

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Background

This study aimed to evaluate the effect of sitagliptin, an oral dipeptidyl peptidase-4 inhibitor, on insulin secretion and glucagon suppression in Korean subjects with type 2 diabetes mellitus.

Methods

Twenty-four subjects underwent a 75-g oral glucose tolerance test (OGTT) before and after 6 months of sitagliptin treatment. Sitagliptin, insulin, and sulfonylurea were withdrawn for 3 days before OGTT to eliminate any acute effects on β-cell insulin or α-cell glucagon secretion. Venous samples were drawn five times during each OGTT to measure plasma glucose, insulin, and glucagon. Indices on insulin secretion and resistance were calculated.

Results

Early phase insulin secretion, measured by the insulinogenic index significantly increased after 6 months of sitagliptin treatment, especially in the higher baseline body mass index group and higher baseline glycosylated hemoglobin (HbA1c) group. There were no significant differences in the insulin resistance indices before and after sitagliptin treatment. Although no significant differences were observed in the absolute levels of glucagon and the glucagon-to-insulin ratio, there was a significant reduction in the percentile change of glucagon-to-insulin ratio at 30- and 120-minute during the OGTT.

Conclusion

Although the HbA1c level did not decrease significantly after 6 months of sitagliptin treatment, an increase in insulin secretion and reduction in early phase postprandial plasma glucagon-to-insulin ratio excursion was confirmed in Korean subjects with type 2 diabetes.

Citations

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A genetic variant in GLP1R is associated with response to DPP-4 inhibitors in patients with type 2 diabetes
Eugene Han, Hye Sun Park, Obin Kwon, Eun Yeong Choe, Hye Jin Wang, Yong-ho Lee, Sang-Hak Lee, Chul Hoon Kim, Lee-Kyung Kim, Soo Heon Kwak, Kyong Soo Park, Chul Sik Kim, Eun Seok Kang
Medicine.2016; 95(44): e5155. CrossRef
Effects of sitagliptin on circulating zinc-α2-glycoprotein levels in newly diagnosed type 2 diabetes patients: a randomized trial
Mingyuan Tian, Zerong Liang, Rui Liu, Ke Li, Xinrong Tan, Yong Luo, Mengliu Yang, Harvest F Gu, Hua Liu, Ling Li, Gangyi Yang
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Efficacy of the Smartphone-Based Glucose Management Application Stratified by User Satisfaction: Hun-Sung Kim, Wona Choi, Eun Kyoung Baek, Yun A Kim, So Jung Yang, In Young Choi, Kun-Ho Yoon, Jae-Hyoung Cho; Diabetes Metab J. 2014;38(3):204-210. Published online June 17, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.3.204

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Abstract PDF PubReader

Background

We aimed to assess the efficacy of the smartphone-based health application for glucose control and patient satisfaction with the mobile network system used for glucose self-monitoring.

Methods

Thirty-five patients were provided with a smartphone device, and self-measured blood glucose data were automatically transferred to the medical staff through the smartphone application over the course of 12 weeks. The smartphone user group was divided into two subgroups (more satisfied group vs. less satisfied group) based on the results of questionnaire surveys regarding satisfaction, comfort, convenience, and functionality, as well as their willingness to use the smartphone application in the future. The control group was set up via a review of electronic medical records by group matching in terms of age, sex, doctor in charge, and glycated hemoglobin (HbA1c).

Results

Both the smartphone group and the control group showed a tendency towards a decrease in the HbA1c level after 3 months (7.7%±0.7% to 7.5%±0.7%, P=0.077). In the more satisfied group (n=27), the HbA1c level decreased from 7.7%±0.8% to 7.3%±0.6% (P=0.001), whereas in the less satisfied group (n=8), the HbA1c result increased from 7.7%±0.4% to 8.1%±0.5% (P=0.062), showing values much worse than that of the no-smartphone control group (from 7.7%±0.5% to 7.7%±0.7%, P=0.093).

Conclusion

In addition to medical feedback, device and network-related patient satisfaction play a crucial role in blood glucose management. Therefore, for the smartphone app-based blood glucose monitoring to be effective, it is essential to provide the patient with a well-functioning high quality tool capable of increasing patient satisfaction and willingness to use.

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What do we know about mobile applications for diabetes self-management? A review of reviews
Megan Hood, Rebecca Wilson, Joyce Corsica, Lauren Bradley, Diana Chirinos, Amanda Vivo
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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
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JMIR mHealth and uHealth.2016; 4(2): e34. CrossRef
Social Networking Services-Based Communicative Care for Patients with Diabetes Mellitus in Korea
Hun-Sung Kim, Yoo Jeong, Sun Baik, So Yang, Tong Kim, Hyunah Kim, Hyunyong Lee, Seung-Hwan Lee, Jae Cho, In-Young Choi, Kun-Ho Yoon
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Use of Mobile Health Technology in the Prevention and Management of Diabetes Mellitus
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Kuei‐Feng Chiang, Hsiu‐Hung Wang
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Does nutritional counseling in telemedicine improve treatment outcomes for diabetes? A systematic review and meta-analysis of results from 92 studies
Dejun Su, Chelsea McBride, Junmin Zhou, Megan S Kelley
Journal of Telemedicine and Telecare.2016; 22(6): 333. CrossRef
A Smartphone Application Significantly Improved Diabetes Self-Care Activities with High User Satisfaction
Yu Jin Kim, Sang Youl Rhee, Jong Kyu Byun, So Young Park, Soo Min Hong, Sang Ouk Chin, Suk Chon, Seungjoon Oh, Jeong-taek Woo, Sung Woon Kim, Young Seol Kim
Diabetes & Metabolism Journal.2015; 39(3): 207. CrossRef
New Directions in Chronic Disease Management
Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon
Endocrinology and Metabolism.2015; 30(2): 159. CrossRef
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Hun-Sung Kim, Hyunah Kim, Suehyun Lee, Kye Hwa Lee, Ju Han Kim
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Hun-Sung Kim, Kye-Hwa Lee, Hyunah Kim, Ju Han Kim
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Pattern of Stress-Induced Hyperglycemia according to Type of Diabetes: A Predator Stress Model: Jin-Sun Chang, Young-Hye You, Shin-Young Park, Ji-Won Kim, Hun-Sung Kim, Kun-Ho Yoon, Jae-Hyoung Cho; Diabetes Metab J. 2013;37(6):475-483. Published online December 12, 2013; DOI: https://doi.org/10.4093/dmj.2013.37.6.475

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Abstract PDF PubReader

Background

We aimed to quantify stress-induced hyperglycemia and differentiate the glucose response between normal animals and those with diabetes. We also examined the pattern in glucose fluctuation induced by stress according to type of diabetes.

Methods

To load psychological stress on animal models, we used a predator stress model by exposing rats to a cat for 60 minutes and measured glucose level from the beginning to the end of the test to monitor glucose fluctuation. We induced type 1 diabetes model (T1D) for ten Sprague-Dawley rats using streptozotocin and used five Otsuka Long-Evans Tokushima Fatty rats as obese type 2 diabetes model (OT2D) and 10 Goto-Kakizaki rats as nonobese type 2 diabetes model (NOT2D). We performed the stress loading test in both the normal and diabetic states and compared patterns of glucose fluctuation among the three models. We classified the pattern of glucose fluctuation into A, B, and C types according to speed of change in glucose level.

Results

Increase in glucose, total amount of hyperglycemic exposure, time of stress-induced hyperglycemia, and speed of glucose increase were significantly increased in all models compared to the normal state. While the early increase in glucose after exposure to stress was higher in T1D and NOT2D, it was slower in OT2D. The rate of speed of the decrease in glucose level was highest in NOT2D and lowest in OT2D.

Conclusion

The diabetic state was more vulnerable to stress compared to the normal state in all models, and the pattern of glucose fluctuation differed among the three types of diabetes. The study provides basic evidence for stress-induced hyperglycemia patterns and characteristics used for the management of diabetes patients.

Citations

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Stress hyperglycemia as first sign of asymptomatic type 1 diabetes: an instructive case
Wei-De Wang, Chun-Hao Chu, Chiung-Hsi Tien, Shuo-Yu Wang, Shih-Yao Liu, Chien-Ming Lin
BMC Pediatrics.2021;[Epub] CrossRef
Genetic determinants of obesity heterogeneity in type II diabetes
Somayeh Alsadat Hosseini Khorami, Mohd Sokhini Abd Mutalib, Mohammad Feili Shiraz, Joseph Anthony Abdullah, Zulida Rejali, Razana Mohd Ali, Huzwah Khaza’ai
Nutrition & Metabolism.2020;[Epub] CrossRef
Sex Dimorphic Responses of the Hypothalamus–Pituitary–Thyroid Axis to Maternal Separation and Palatable Diet
Lorraine Jaimes-Hoy, Fidelia Romero, Jean-Louis Charli, Patricia Joseph-Bravo
Frontiers in Endocrinology.2019;[Epub] CrossRef
Hesperidin protects against stress induced gastric ulcer through regulation of peroxisome proliferator activator receptor gamma in diabetic rats
Shimaa M. Elshazly, Dalia M. Abd El Motteleb, Islam A.A.E-H. Ibrahim
Chemico-Biological Interactions.2018; 291: 153. CrossRef
Physiology and Neurobiology of Stress and the Implications for Physical Health
B Sivaprakash
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Predictive Clinical Parameters and Glycemic Efficacy of Vildagliptin Treatment in Korean Subjects with Type 2 Diabetes: Jin-Sun Chang, Juyoung Shin, Hun-Sung Kim, Kyung-Hee Kim, Jeong-Ah Shin, Kun-Ho Yoon, Bong-Yun Cha, Ho-Young Son, Jae-Hyoung Cho; Diabetes Metab J. 2013;37(1):72-80. Published online February 15, 2013; DOI: https://doi.org/10.4093/dmj.2013.37.1.72

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37 Download
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Abstract PDF PubReader

Background

The aims of this study are to investigate the glycemic efficacy and predictive parameters of vildagliptin therapy in Korean subjects with type 2 diabetes.

Methods

In this retrospective study, we retrieved data for subjects who were on twice-daily 50 mg vildagliptin for at least 6 months, and classified the subjects into five treatment groups. In three of the groups, we added vildagliptin to their existing medication regimen; in the other two groups, we replaced one of their existing medications with vildagliptin. We then analyzed the changes in glucose parameters and clinical characteristics.

Results

Ultimately, 327 subjects were analyzed in this study. Vildagliptin significantly improved hemoglobin A1c (HbA1c) levels over 6 months. The changes in HbA1c levels (ΔHbA1c) at month 6 were -2.24% (P=0.000), -0.77% (P=0.000), -0.80% (P=0.001), -0.61% (P=0.000), and -0.34% (P=0.025) for groups 1, 2, 3, 4, and 5, respectively, with significance. We also found significant decrements in fasting plasma glucose levels in groups 1, 2, 3, and 4 (P<0.05). Of the variables, initial HbA1c levels (P=0.032) and history of sulfonylurea use (P=0.026) were independently associated with responsiveness to vildagliptin treatment.

Conclusion

Vildagliptin was effective when it was used in subjects with poor glycemic control. It controlled fasting plasma glucose levels as well as sulfonylurea treatment in Korean type 2 diabetic subjects.

Citations

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Predictive clinical parameters for the hemoglobin A1c-lowering effect of vildagliptin in Japanese patients with type 2 diabetes
Yukihiro Bando, Masayuki Yamada, Keiko Aoki, Hideo Kanehara, Azusa Hisada, Kazuhiro Okafuji, Daisyu Toya, Nobuyoshi Tanaka
Diabetology International.2014; 5(4): 229. CrossRef
The Efficacy of Vildagliptin in Korean Patients with Type 2 Diabetes
Jun Sung Moon, Kyu Chang Won
Diabetes & Metabolism Journal.2013; 37(1): 36. CrossRef

Effects of a 6-Month Exenatide Therapy on HbA1c and Weight in Korean Patients with Type 2 Diabetes: A Retrospective Cohort Study: Juyoung Shin, Jin-Sun Chang, Hun-Sung Kim, Sun-Hee Ko, Bong-Yun Cha, Ho-Young Son, Kun-Ho Yoon, Jae-Hyoung Cho; Diabetes Metab J. 2012;36(5):364-370. Published online October 18, 2012; DOI: https://doi.org/10.4093/dmj.2012.36.5.364

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Abstract PDF PubReader

Background

While many studies have shown the good efficacy and safety of exenatide in patients with diabetes, limited information is available about exenatide in clinical practice in Korean populations. Therefore, this retrospective cohort study was designed to analyze the effects of exenatide on blood glucose level and body weight in Korean patients with type 2 diabetes mellitus.

Methods

We reviewed the records of the patients with diabetes who visited Seoul St. Mary's Hospital and for whom exenatide was prescribed from June 2009 to October 2011. After excluding subjects based on their race/ethnicity, medical history, whether or not they changed more than 2 kinds of oral hypoglycemic agents with exenatide treatment, loss to follow-up, or whether they stopped exenatide therapy within 6 months, a total of 52 subjects were included in the final analysis.

Results

The mean glycated hemoglobin (HbA1c) level and weight remarkably decreased from 8.5±1.7% to 6.7±1.0% (P<0.001) and from 82.3±15.8 kg to 78.6±16.3 kg (P<0.001), respectively. The multiple regression analysis indicated that the reduction in HbA1c level was significantly associated with a shorter duration of diabetes, a higher baseline HbA1c level, and greater weight reduction, whereas weight loss had no significant correlation with other factors. No severe adverse events were observed.

Conclusion

These results suggest that a 6-month exenatide injection therapy significantly improved patients' HbA1c levels and body weights without causing serious adverse effects in Korean patients with type 2 diabetes.

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Review

Ubiquitous Diabetes Management System via Interactive Communication Based on Information Technologies: Clinical Effects and Perspectives: Jae-Hyoung Cho, Hun-Sung Kim, Jae-Hoon Han, Jin-Hee Lee, Jeong-Ah Oh, Yoon-Hee Choi, Kun-Ho Yoon; Korean Diabetes J. 2010;34(5):267-273. Published online October 31, 2010; DOI: https://doi.org/10.4093/kdj.2010.34.5.267

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Abstract PDF PubReader

New diabetes management systems based on interactive communication have been introduced recently, accompanying rapid advances in information technology; these systems are referred to as "ubiquitous diabetes management systems." In such ubiquitous systems, patients and medical teams can communicate via Internet or telecommunications, with patients uploading their glucose data and personal information, and medical teams sending optimal feedback. Clinical evidence from both long-term and short-term trials has been reported by some researchers. Such systems appear to be effective not only in reducing the levels of HbA1c but also in stabilizing glucose control. However, most notably, evidence for the cost-effectiveness of such a system should be demonstrated before it can be propagated out to the general population in actual clinical practice. To establish a cost-effective model, various types of clinical decision supporting software designed to reduce the labor time of physicians must first be developed. A number of sensors and devices for monitoring patients' data are expected to be available in the near future; thus, methods for automatic interconnections between devices and web charts were also developed. Further investigations to demonstrate the clinical outcomes of such a system should be conducted, hopefully leading to a new paradigm of diabetes management.

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