- Clinical Diabetes & Therapeutics
- Additional Effect of Dietary Fiber in Patients with Type 2 Diabetes Mellitus Using Metformin and Sulfonylurea: An Open-Label, Pilot Trial
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Seung-Eun Lee, Yongbin Choi, Ji Eun Jun, You-Bin Lee, Sang-Man Jin, Kyu Yeon Hur, Gwang Pyo Ko, Moon-Kyu Lee
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Diabetes Metab J. 2019;43(4):422-431. Published online April 23, 2019
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DOI: https://doi.org/10.4093/dmj.2018.0090
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- Background
Metformin, sulfonylurea, and dietary fiber are known to affect gut microbiota in patients with type 2 diabetes mellitus (T2DM). This open and single-arm pilot trial investigated the effects of the additional use of fiber on glycemic parameters, insulin, incretins, and microbiota in patients with T2DM who had been treated with metformin and sulfonylurea. MethodsParticipants took fiber for 4 weeks and stopped for the next 4 weeks. Glycemic parameters, insulin, incretins during mixed-meal tolerance test (MMTT), lipopolysaccharide (LPS) level, and fecal microbiota were analyzed at weeks 0, 4, and 8. The first tertile of difference in glucose area under the curve during MMTT between weeks 0 and 4 was defined as ‘responders’ and the third as ‘nonresponders,’ respectively. ResultsIn all 10 participants, the peak incretin levels during MMTT were higher and LPS were lower at week 4 as compared with at baseline. While the insulin sensitivity of the ‘responders’ increased at week 4, that of the ‘nonresponders’ showed opposite results. However, the results were not statistically significant. In all participants, metabolically unfavorable microbiota decreased at week 4 and were restored at week 8. At baseline, metabolically hostile bacteria were more abundant in the ‘nonresponders.’ In ‘responders,’ Roseburia intestinalis increased at week 4. ConclusionWhile dietary fiber did not induce additional changes in glycemic parameters, it showed a trend of improvement in insulin sensitivity in ‘responders.’ Even if patients are already receiving diabetes treatment, the additional administration of fiber can lead to additional benefits in the treatment of diabetes.
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Yue Wang, Xianxian Jia, Bin Cong Frontiers in Microbiology.2024;[Epub] CrossRef - The effects of prebiotics on gastrointestinal side effects of metformin in youth: A pilot randomized control trial in youth-onset type 2 diabetes
Sydney A. Dixon, Sidharth Mishra, Katrina B. Dietsche, Shalini Jain, Lilian Mabundo, Michael Stagliano, Andrea Krenek, Amber Courville, Shanna Yang, Sara A. Turner, Abby G. Meyers, Doris E. Estrada, Hariom Yadav, Stephanie T. Chung Frontiers in Endocrinology.2023;[Epub] CrossRef - The impact of dietary, surgical, and pharmacological interventions on gut microbiota in individuals with diabetes mellitus: A systematic review
Patricia M. Bock, Andreza F. Martins, Rafaela Ramalho, Gabriela H. Telo, Gabriel Leivas, Clara K. Maraschin, Beatriz D. Schaan Diabetes Research and Clinical Practice.2022; 189: 109944. CrossRef - Assessment of the safety and probiotic properties of Roseburia intestinalis: A potential “Next Generation Probiotic”
Chao Zhang, Kejia Ma, Kai Nie, Minzi Deng, Weiwei Luo, Xing Wu, Yujun Huang, Xiaoyan Wang Frontiers in Microbiology.2022;[Epub] CrossRef - The Effect of Prebiotics and Oral Anti-Diabetic Agents on Gut Microbiome in Patients with Type 2 Diabetes: A Systematic Review and Network Meta-Analysis of Randomised Controlled Trials
Omorogieva Ojo, Xiaohua Wang, Osarhumwese Osaretin Ojo, Joanne Brooke, Yiqing Jiang, Qingqing Dong, Trevor Thompson Nutrients.2022; 14(23): 5139. CrossRef - The Effect of Dietary Interventions on Chronic Inflammatory Diseases in Relation to the Microbiome: A Systematic Review
Carlijn A. Wagenaar, Marieke van de Put, Michelle Bisschops, Wendy Walrabenstein, Catharina S. de Jonge, Hilde Herrema, Dirkjan van Schaardenburg Nutrients.2021; 13(9): 3208. CrossRef - The Role of Dietary Fibre in Modulating Gut Microbiota Dysbiosis in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomised Controlled Trials
Omorogieva Ojo, Qian-Qian Feng, Osarhumwese Osaretin Ojo, Xiao-Hua Wang Nutrients.2020; 12(11): 3239. CrossRef - High Fiber and Beta Carotene from Sweet Potatoes and Pumpkin Improve Insulin Resistance by Inhibition of Sterol Regulatory Binding Protein 1c in Liver of Hypertriglyceridemic Rats
Sunarti Sunarti, Umar Santoso, Abrory Agus Cahya Pramana, Emy Huriyati, Dianandha Septiana Rubi Open Access Macedonian Journal of Medical Sciences.2020; 8(A): 898. CrossRef
- Epidemiology
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- High Proportion of Adult Cases and Prevalence of Metabolic Syndrome in Type 1 Diabetes Mellitus Population in Korea: A Nationwide Study
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You-Bin Lee, Kyungdo Han, Bongsung Kim, Sang-Man Jin, Seung-Eun Lee, Ji Eun Jun, Jiyeon Ahn, Gyuri Kim, Jae Hyeon Kim
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Diabetes Metab J. 2019;43(1):76-89. Published online August 22, 2018
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DOI: https://doi.org/10.4093/dmj.2018.0048
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- Background
The prevalence and incidence of type 1 diabetes mellitus (T1DM) in all age groups and the prevalence of metabolic syndrome in patients with T1DM in Korea were estimated. MethodsThe incidence and prevalence of T1DM between 2007 and 2013 were calculated using the Korean National Health Insurance Service (NHIS) datasets of claims. Clinical characteristics and prevalence of metabolic syndrome in individuals with T1DM between 2009 and 2013 were determined using the database of NHIS preventive health checkups. ResultsThe prevalence of T1DM in Korea between 2007 and 2013 was 0.041% to 0.047%. The annual incidence rate of T1DM in Korea in 2007 to 2013 was 2.73 to 5.02/100,000 people. Although the incidence rate of typical T1DM was highest in teenagers, it remained steady in adults over 30 years of age. In contrast, the incidence rate of atypical T1DM in 2013 was higher in people aged 40 years or older than in younger age groups. Age- and sex-adjusted prevalence of metabolic syndrome in patients with T1DM was 51.65% to 55.06% between 2009 and 2013. ConclusionT1DM may be more common in Korean adults than previously believed. Metabolic syndrome may be a frequent finding in individuals with T1DM in Korea.
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Du Wang, Xiaoli Hou, Juan Huang, Jianjing Sun, Takashi Kadowaki, Moon-Kyu Lee, Alicia J. Jenkins, Linong Ji Diabetes Research and Clinical Practice.2024; 207: 111055. CrossRef - Prevalence of Metabolic Syndrome and Its Risk Factors Influence on Microvascular Complications in Patients With Type 1 and Type 2 Diabetes Mellitus
Asad Riaz, Shoaib Asghar, Salman Shahid, Haider Tanvir, Muhammad Hamza Ejaz, Mamuna Akram Cureus.2024;[Epub] CrossRef - Risk of Depression according to Cumulative Exposure to a Low-Household Income Status in Individuals with Type 2 Diabetes Mellitus: A Nationwide Population- Based Study
So Hee Park, You-Bin Lee, Kyu-na Lee, Bongsung Kim, So Hyun Cho, So Yoon Kwon, Jiyun Park, Gyuri Kim, Sang-Man Jin, Kyu Yeon Hur, Kyungdo Han, Jae Hyeon Kim Diabetes & Metabolism Journal.2024; 48(2): 290. CrossRef - Comparison of Insulin-Treated Patients with Ambiguous Diabetes Type with Definite Type 1 and Type 2 Diabetes Mellitus Subjects: A Clinical Perspective
Insa Laspe, Juris J. Meier, Michael A. Nauck Diabetes & Metabolism Journal.2023; 47(1): 140. CrossRef - Clinical and biochemical profile of childhood–adolescent-onset type 1 diabetes and adult-onset type 1 diabetes among Asian Indians
Viswanathan Mohan, Ganesan Uma Sankari, Anandakumar Amutha, Ranjit Mohan Anjana, Saravanan Jeba Rani, Ranjit Unnikrishnan, Ulagamathesan Venkatesan, Coimbatore Subramanian Shanthi Rani Acta Diabetologica.2023; 60(4): 579. CrossRef - Subtypes of type 2 diabetes and their association with outcomes in Korean adults - A cluster analysis of community-based prospective cohort
You-Cheol Hwang, Hong-Yup Ahn, Ji Eun Jun, In-Kyung Jeong, Kyu Jeung Ahn, Ho Yeon Chung Metabolism.2023; 141: 155514. CrossRef - Insulin Fact Sheet in Type 1 and 2 Diabetes Mellitus and Trends of Antidiabetic Medication Use in Insulin Users with Type 2 Diabetes Mellitus: 2002 to 2019
Jiyun Park, Gyuri Kim, Bong-Sung Kim, Kyung-Do Han, So Yoon Kwon, So Hee Park, You-Bin Lee, Sang-Man Jin, Jae Hyeon Kim Diabetes & Metabolism Journal.2023; 47(2): 211. CrossRef - Insulin resistance is more frequent in type 1 diabetes patients with long disease duration
Yuting Xie, Mei Shi, Xiaolin Ji, Fansu Huang, Li Fan, Xia Li, Zhiguang Zhou Diabetes/Metabolism Research and Reviews.2023;[Epub] CrossRef - Long-term Effectiveness of the National Diabetes Quality Assessment Program in South Korea
Ji Hye Huh, Serim Kwon, Gui Ok Kim, Bo Yeon Kim, Kyoung Hwa Ha, Dae Jung Kim Diabetes Care.2023; 46(9): 1700. CrossRef - Low Household Income Status and Death from Pneumonia in People with Type 2 Diabetes Mellitus: A Nationwide Study
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Joonsang Yoo, Jimin Jeon, Minyoul Baek, Sun Ok Song, Jinkwon Kim Journal of Translational Medicine.2023;[Epub] CrossRef - The emergence of obesity in type 1 diabetes
Martin T. W. Kueh, Nicholas W. S. Chew, Ebaa Al-Ozairi, Carel W. le Roux International Journal of Obesity.2023;[Epub] CrossRef - Association between Metabolic Syndrome and Microvascular Complications in Chinese Adults with Type 1 Diabetes Mellitus
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Jessica L. Harding, Pandora L. Wander, Xinge Zhang, Xia Li, Suvi Karuranga, Hongzhi Chen, Hong Sun, Yuting Xie, Richard A. Oram, Dianna J. Magliano, Zhiguang Zhou, Alicia J. Jenkins, Ronald C.W. Ma Diabetes Care.2022; 45(4): 994. CrossRef - Age at Diagnosis and the Risk of Diabetic Nephropathy in Young Patients with Type 1 Diabetes Mellitus
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Joungyoun Kim, Sang-Jun Shin, Ye-Seul Kim, Hee-Taik Kang Cardiovascular Diabetology.2021;[Epub] CrossRef - Mortality and causes of death in a population with blindness in Korea: A longitudinal follow-up study using a national sample cohort
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Jae Hyeon Kim The Journal of Korean Diabetes.2020; 21(4): 197. CrossRef - Risk of early mortality and cardiovascular disease in type 1 diabetes: a comparison with type 2 diabetes, a nationwide study
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- Obesity and Metabolic Syndrome
- Utility of Serum Albumin for Predicting Incident Metabolic Syndrome According to Hyperuricemia
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You-Bin Lee, Ji Eun Jun, Seung-Eun Lee, Jiyeon Ahn, Gyuri Kim, Jae Hwan Jee, Ji Cheol Bae, Sang-Man Jin, Jae Hyeon Kim
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Diabetes Metab J. 2018;42(6):529-537. Published online September 28, 2018
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DOI: https://doi.org/10.4093/dmj.2018.0012
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- Background
Serum albumin and uric acid have been positively linked to metabolic syndrome (MetS). However, the association of MetS incidence with the combination of uric acid and albumin levels has not been investigated. We explored the association of albumin and uric acid with the risk of incident MetS in populations divided according to the levels of these two parameters. MethodsIn this retrospective longitudinal study, 11,613 non-MetS participants were enrolled among 24,185 individuals who had undergone at least four annual check-ups between 2006 and 2012. The risk of incident MetS was analyzed according to four groups categorized by the sex-specific medians of serum albumin and uric acid. ResultsDuring 55,407 person-years of follow-up, 2,439 cases of MetS developed. The risk of incident MetS increased as the uric acid category advanced in individuals with lower or higher serum albumin categories with hazard ratios (HRs) of 1.386 (95% confidence interval [CI], 1.236 to 1.554) or 1.314 (95% CI, 1.167 to 1.480). However, the incidence of MetS increased with higher albumin levels only in participants in the lower uric acid category with a HR of 1.143 (95% CI, 1.010 to 1.294). ConclusionHigher levels of albumin were associated with an increased risk of incident MetS only in individuals with lower uric acid whereas higher levels of uric acid were positively linked to risk of incident MetS regardless of albumin level.
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Vincent G. Pluimakers, Selveta S. van Santen, Marta Fiocco, Marie‐Christine E. Bakker, Aart J. van der Lelij, Marry M. van den Heuvel‐Eibrink, Sebastian J. C. M. M. Neggers Obesity Reviews.2021;[Epub] CrossRef - Heart Disease and Stroke Statistics—2020 Update: A Report From the American Heart Association
Salim S. Virani, Alvaro Alonso, Emelia J. Benjamin, Marcio S. Bittencourt, Clifton W. Callaway, April P. Carson, Alanna M. Chamberlain, Alexander R. Chang, Susan Cheng, Francesca N. Delling, Luc Djousse, Mitchell S.V. Elkind, Jane F. Ferguson, Myriam Forn Circulation.2020;[Epub] CrossRef - Association between dairy product consumption and hyperuricemia in an elderly population with metabolic syndrome
Guillermo Mena-Sánchez, Nancy Babio, Nerea Becerra-Tomás, Miguel Á. Martínez-González, Andrés Díaz-López, Dolores Corella, Maria D. Zomeño, Dora Romaguera, Jesús Vioque, Ángel M. Alonso-Gómez, Julia Wärnberg, José A. Martínez, Luís Serra-Majem, Ramon Estr Nutrition, Metabolism and Cardiovascular Diseases.2020; 30(2): 214. CrossRef - Evaluation of serum uric acid levels in patients with rosacea
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- Effect on Glycemic, Blood Pressure, and Lipid Control according to Education Types
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Mi-Ju Choi, Seung-Hyun Yoo, Kum-Rae Kim, Yoo-Mi Bae, Sun-Hee Ahn, Seong-Shin Kim, Seong-Ah Min, Jin-Sun Choi, Seung-Eun Lee, Yeo-Jin Moon, Eun Jung Rhee, Cheol-Young Park, Won Young Lee, Ki Won Oh, Sung Woo Park, Sun Woo Kim
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Diabetes Metab J. 2011;35(6):580-586. Published online December 26, 2011
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DOI: https://doi.org/10.4093/dmj.2011.35.6.580
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56,048
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- Background
Diabetes self-management education and reinforcement are important for effective management of the disease. We investigated the effectiveness of interactive small-group education on glycemic, blood pressure, and lipid levels. MethodsFor this study, 207 type 2 diabetes patients with suboptimal glycemic control (HbA1c levels >6.5%) were enrolled. The conventional education group received an existing education program from April to November in 2006, and the interactive education group received a new small-group education program from December 2006 to July 2007. The two groups were comparatively analyzed for changes in blood sugar, glycated hemoglobin, lipid, and blood pressure at baseline, 3, 6, and 12 months and the proportion of patients achieving target goals at 12 months. ResultsAfter 12 months of follow-up, HbA1c levels in the interactive education group were significantly lower than in the conventional education group (6.7% vs. 6.4%, P<0.001). Fasting and 2 hour postprandial glucose concentrations, total cholesterol, and low density lipoprotein cholesterol were significantly lower in the interactive education group than in the conventional education group. The proportion of patients that achieved target goals was significantly higher in the interactive education group. ConclusionThe small-group educational method improved and re-established the existing group educational method. This finding suggests that the importance of education appears to be related to the method by which it is received rather than the education itself. Thus, the use of small-group educational methods to supplement existing educational methods established for diverse age levels should be considered in the future.
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Jong Ho Kim, Yun Jeong Nam, Won Jin Kim, Kyung Ah Lee, A Ran Baek, Jung Nam Park, Jin Mi Kim, Seo Young Oh, Eun Heui Kim, Min Jin Lee, Yun Kyung Jeon, Bo Hyun Kim, In Joo Kim, Yong Ki Kim, Sang Soo Kim The Journal of Korean Diabetes.2018; 19(2): 119. CrossRef - Diabetes Camp as Continuing Education for Diabetes Self-Management in Middle-Aged and Elderly People with Type 2 Diabetes Mellitus
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Mi Yeon Kim, Sunghwan Suh, Sang-Man Jin, Se Won Kim, Ji Cheol Bae, Kyu Yeon Hur, Sung Hye Kim, Mi Yong Rha, Young Yun Cho, Myung-Shik Lee, Moon Kyu Lee, Kwang-Won Kim, Jae Hyeon Kim Diabetes & Metabolism Journal.2012; 36(6): 452. CrossRef
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