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Effects of Teneligliptin on HbA1c levels, Continuous Glucose Monitoring-Derived Time in Range and Glycemic Variability in Elderly Patients with T2DM (TEDDY Study)
Ji Cheol Bae, Soo Heon Kwak, Hyun Jin Kim, Sang-Yong Kim, You-Cheol Hwang, Sunghwan Suh, Bok Jin Hyun, Ji Eun Cha, Jong Chul Won, Jae Hyeon Kim
Diabetes Metab J. 2022;46(1):81-92.   Published online June 16, 2021
DOI: https://doi.org/10.4093/dmj.2021.0016
  • 7,513 View
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  • 5 Web of Science
  • 5 Crossref
Graphical AbstractGraphical Abstract AbstractAbstract PDFSupplementary MaterialPubReader   ePub   
Background
To evaluate the effects of teneligliptin on glycosylated hemoglobin (HbA1c) levels, continuous glucose monitoring (CGM)-derived time in range, and glycemic variability in elderly type 2 diabetes mellitus patients.
Methods
This randomized, double-blinded, placebo-controlled study was conducted in eight centers in Korea (clinical trial registration number: NCT03508323). Sixty-five participants aged ≥65 years, who were treatment-naïve or had been treated with stable doses of metformin, were randomized at a 1:1 ratio to receive 20 mg of teneligliptin (n=35) or placebo (n=30) for 12 weeks. The main endpoints were the changes in HbA1c levels from baseline to week 12, CGM metrics-derived time in range, and glycemic variability.
Results
After 12 weeks, a significant reduction (by 0.84%) in HbA1c levels was observed in the teneligliptin group compared to that in the placebo group (by 0.08%), with a between-group least squares mean difference of –0.76% (95% confidence interval [CI], –1.08 to –0.44). The coefficient of variation, standard deviation, and mean amplitude of glycemic excursion significantly decreased in participants treated with teneligliptin as compared to those in the placebo group. Teneligliptin treatment significantly decreased the time spent above 180 or 250 mg/dL, respectively, without increasing the time spent below 70 mg/dL. The mean percentage of time for which glucose levels remained in the 70 to 180 mg/dL time in range (TIR70–180) at week 12 was 82.0%±16.0% in the teneligliptin group, and placebo-adjusted change in TIR70–180 from baseline was 13.3% (95% CI, 6.0 to 20.6).
Conclusion
Teneligliptin effectively reduced HbA1c levels, time spent above the target range, and glycemic variability, without increasing hypoglycemia in our study population.

Citations

Citations to this article as recorded by  
  • Comparison of teneligliptin and other gliptin-based regimens in addressing insulin resistance and glycemic control in type 2 diabetic patients: a cross-sectional study
    Harmanjit Singh, Ravi Rohilla, Shivani Jaswal, Mandeep Singla
    Expert Review of Endocrinology & Metabolism.2024; 19(1): 81.     CrossRef
  • Potential approaches using teneligliptin for the treatment of type 2 diabetes mellitus: current status and future prospects
    Harmanjit Singh, Jasbir Singh, Ravneet Kaur Bhangu, Mandeep Singla, Jagjit Singh, Farideh Javid
    Expert Review of Clinical Pharmacology.2023; 16(1): 49.     CrossRef
  • Mechanism of molecular interaction of sitagliptin with human DPP4 enzyme - New Insights
    Michelangelo Bauwelz Gonzatti, José Edvar Monteiro Júnior, Antônio José Rocha, Jonathas Sales de Oliveira, Antônio José de Jesus Evangelista, Fátima Morgana Pio Fonseca, Vânia Marilande Ceccatto, Ariclécio Cunha de Oliveira, José Ednésio da Cruz Freire
    Advances in Medical Sciences.2023; 68(2): 402.     CrossRef
  • A prospective multicentre open label study to assess effect of Teneligliptin on glycemic control through parameters of time in range (TIR) Metric using continuous glucose monitoring (TOP-TIR study)
    Banshi Saboo, Suhas Erande, A.G. Unnikrishnan
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2022; 16(2): 102394.     CrossRef
  • Association between Variability of Metabolic Risk Factors and Cardiometabolic Outcomes
    Min Jeong Park, Kyung Mook Choi
    Diabetes & Metabolism Journal.2022; 46(1): 49.     CrossRef
Obesity and Metabolic Syndrome
The Protective Effects of Increasing Serum Uric Acid Level on Development of Metabolic Syndrome
Tae Yang Yu, Sang-Man Jin, Jae Hwan Jee, Ji Cheol Bae, Moon-Kyu Lee, Jae Hyeon Kim
Diabetes Metab J. 2019;43(4):504-520.   Published online February 21, 2019
DOI: https://doi.org/10.4093/dmj.2018.0079
  • 4,671 View
  • 52 Download
  • 14 Web of Science
  • 11 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

It has not been determined whether changes in serum uric acid (SUA) level are associated with incident metabolic syndrome (MetS). The aim of the current study was to investigate the relationship between changes in SUA level and development of MetS in a large number of subjects.

Methods

In total, 13,057 subjects participating in a medical health check-up program without a diagnosis of MetS at baseline were enrolled. Cox proportional hazards models were used to test the independent association of percent changes in SUA level with development of MetS.

Results

After adjustment for age, systolic blood pressure, body mass index, fat-free mass (%), estimated glomerular filtration rate, smoking status, fasting glucose, triglyceride, low density lipoprotein cholesterol, high density lipoprotein cholesterol, and baseline SUA levels, the hazard ratios (HRs) (95% confidence intervals [CIs]) for incident MetS in the second, third, and fourth quartiles compared to the first quartile of percent change in SUA level were 1.055 (0.936 to 1.190), 0.927 (0.818 to 1.050), and 0.807 (0.707 to 0.922) in male (P for trend <0.001) and 1.000 (0.843 to 1.186), 0.744 (0.615 to 0.900), and 0.684 (0.557 to 0.840) in female (P for trend <0.001), respectively. As a continuous variable in the fully-adjusted model, each one-standard deviation increase in percent change in SUA level was associated with an HR (95% CI) for incident MetS of 0.944 (0.906 to 0.982) in male (P=0.005) and 0.851 (0.801 to 0.905) in female (P<0.001).

Conclusion

The current study demonstrated that increasing SUA level independently protected against the development of MetS, suggesting a possible role of SUA as an antioxidant in the pathogenesis of incident MetS.

Citations

Citations to this article as recorded by  
  • High prevalence of hyperuricemia and the association with metabolic syndrome in the rural areas of Southwestern China: A structural equation modeling based on the Zhuang minority cohort
    Xiaofen Tang, Shun Liu, Xiaoqiang Qiu, Li Su, Dongping Huang, Jun Liang, Yu Yang, Jennifer Hui Juan Tan, Xiaoyun Zeng, Yihong Xie
    Nutrition, Metabolism and Cardiovascular Diseases.2024; 34(2): 497.     CrossRef
  • Predictive Value of Collagen Biomarkers in Advanced Chronic Kidney Disease Patients
    Carina Ureche, Gianina Dodi, Adela Mihaela Șerban, Andreea Simona Covic, Luminița Voroneanu, Simona Hogaș, Radu Andy Sascău, Cristian Stătescu, Adrian Covic
    Biomolecules.2023; 13(2): 389.     CrossRef
  • The bidirectional relationship between metabolic syndrome and hyperuricemia in China: A longitudinal study from CHARLS
    Wen-Yu Chen, Yan-Peng Fu, Min Zhou
    Endocrine.2022; 76(1): 62.     CrossRef
  • Correlation between Serum Oxidative Stress Level and Serum Uric Acid and Prognosis in Patients with Hepatitis B-Related Liver Cancer before Operation
    Maowen Yu, Chaozhu Zhang, Hongbo Tang, Chaohui Xiao, Hangjun Che
    Journal of Healthcare Engineering.2022; 2022: 1.     CrossRef
  • Association between metabolic syndrome and uric acid: a systematic review and meta-analysis
    Elena Raya-Cano, Manuel Vaquero-Abellán, Rafael Molina-Luque, Domingo De Pedro-Jiménez, Guillermo Molina-Recio, Manuel Romero-Saldaña
    Scientific Reports.2022;[Epub]     CrossRef
  • Acute moderate‐intensity aerobic exercise promotes purinergic and inflammatory responses in sedentary, overweight and physically active subjects
    Cesar Eduardo Jacintho Moritz, Franccesco Pinto Boeno, Alexandra Ferreira Vieira, Samuel Vargas Munhoz, Juliete Nathali Scholl, Amanda de Fraga Dias, Pauline Rafaela Pizzato, Fabrício Figueiró, Ana Maria Oliveira Battastini, Alvaro Reischak‐Oliveira
    Experimental Physiology.2021; 106(4): 1024.     CrossRef
  • Association between baseline and changes in serum uric acid and incident metabolic syndrome: a nation-wide cohort study and updated meta-analysis
    Sen Chen, Nianwei Wu, Chuan Yu, Ying Xu, Chengfu Xu, Yuli Huang, Jian Zhao, Ningxiu Li, Xiong-Fei Pan
    Nutrition & Metabolism.2021;[Epub]     CrossRef
  • Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review
    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
  • Inverse associations between serum urate and glycemic status in a general population and in persons with diabetes mellitus
    Ichiro Wakabayashi
    Diabetology & Metabolic Syndrome.2020;[Epub]     CrossRef
  • Association of Serum Uric Acid with Metabolic Syndrome and Its Components: A Mendelian Randomization Analysis
    Lu Wang, Tao Zhang, Yafei Liu, Fang Tang, Fuzhong Xue
    BioMed Research International.2020; 2020: 1.     CrossRef
  • Association between Serum Uric Acid and Metabolic Syndrome in Koreans
    Jihyun Jeong, Young Ju Suh
    Journal of Korean Medical Science.2019;[Epub]     CrossRef
Editorial
Epidemiology
Trends of Diabetes Epidemic in Korea
Ji Cheol Bae
Diabetes Metab J. 2018;42(5):377-379.   Published online October 22, 2018
DOI: https://doi.org/10.4093/dmj.2018.0194
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  • 37 Download
  • 22 Web of Science
  • 21 Crossref
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Citations

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  • Dynamic changes in prevalence of type 2 diabetes along with associated factors in Bangladesh: Evidence from two national cross-sectional surveys (BDHS 2011 and BDHS 2017–18)
    Sabiha Shirin Sara, Ashis Talukder, Ka Yiu Lee, Nayan Basak, Shaharior Rahman Razu, Iqramul Haq, Chuton Deb Nath
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2023; 17(2): 102706.     CrossRef
  • Inverse Association between Oxidative Balance Score and Incident Type 2 Diabetes Mellitus
    Yu-Jin Kwon, Hye-Min Park, Jun-Hyuk Lee
    Nutrients.2023; 15(11): 2497.     CrossRef
  • Non-HDL cholesterol as a predictor for incident type 2 diabetes in community-dwelling adults: longitudinal findings over 12 years
    In-Ho Seo, Da-Hye Son, Hye Sun Lee, Yong-Jae Lee
    Translational Research.2022; 243: 52.     CrossRef
  • Severe Hypoglycemia Increases Dementia Risk and Related Mortality: A Nationwide, Population-based Cohort Study
    Eugene Han, Kyung-do Han, Byung-Wan Lee, Eun Seok Kang, Bong-Soo Cha, Seung-Hyun Ko, Yong-ho Lee
    The Journal of Clinical Endocrinology & Metabolism.2022; 107(5): e1976.     CrossRef
  • Effects of Teneligliptin on HbA1c levels, Continuous Glucose Monitoring-Derived Time in Range and Glycemic Variability in Elderly Patients with T2DM (TEDDY Study)
    Ji Cheol Bae, Soo Heon Kwak, Hyun Jin Kim, Sang-Yong Kim, You-Cheol Hwang, Sunghwan Suh, Bok Jin Hyun, Ji Eun Cha, Jong Chul Won, Jae Hyeon Kim
    Diabetes & Metabolism Journal.2022; 46(1): 81.     CrossRef
  • Fatty liver index as a predictor for incident type 2 diabetes in community-dwelling adults: longitudinal findings over 12 years
    In-Ho Seo, Hye Sun Lee, Yong-Jae Lee
    Cardiovascular Diabetology.2022;[Epub]     CrossRef
  • Triglyceride glucose (TyG) index as a predictor of incident type 2 diabetes among nonobese adults: a 12-year longitudinal study of the Korean Genome and Epidemiology Study cohort
    Byoungjin Park, Hye Sun Lee, Yong-Jae Lee
    Translational Research.2021; 228: 42.     CrossRef
  • Leukocyte count, C-reactive protein level and incidence risk of type 2 diabetes among non-smoking adults: A longitudinal finding over 12 years from the Korean Genome and Epidemiology Study
    A-Ra Cho, Jun-Hyuk Lee, Hye Sun Lee, Yong-Jae Lee
    Primary Care Diabetes.2021; 15(2): 385.     CrossRef
  • White Blood Cell Count as a Predictor of Incident Type 2 Diabetes Mellitus Among Non-Obese Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study
    Jae-Min Park, Hye Sun Lee, Ju-Young Park, Dong-Hyuk Jung, Ji-Won Lee
    Journal of Inflammation Research.2021; Volume 14: 1235.     CrossRef
  • C-reactive protein-to-albumin ratio and 8‐year incidence of type 2 diabetes: the Korean genome and epidemiology study
    A.-Ra Cho, Sung‐Bum Lee, Kyung-Won Hong, Dong‐Hyuk Jung
    Acta Diabetologica.2021; 58(11): 1525.     CrossRef
  • Comparison of fracture risk between type 1 and type 2 diabetes: a comprehensive real-world data
    J. Ha, C. Jeong, K.-D. Han, Y. Lim, M.K. Kim, H.-S. Kwon, K.-H. Song, M.I. Kang, K.-H. Baek
    Osteoporosis International.2021; 32(12): 2543.     CrossRef
  • Lung function as a predictor of incident type 2 diabetes in community-dwelling adults: A longitudinal finding over 12 years from the Korean Genome and Epidemiology Study
    J.H. Lee, H.S. Lee, Y.J. Lee
    Diabetes & Metabolism.2020; 46(5): 392.     CrossRef
  • Metformin Treatment for Patients with Diabetes and Chronic Kidney Disease: A Korean Diabetes Association and Korean Society of Nephrology Consensus Statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Diabetes & Metabolism Journal.2020; 44(1): 3.     CrossRef
  • Serum γ-glutamyltransferase as an independent predictor for incident type 2 diabetes in middle-aged and older adults: Findings from the KoGES over 12 years of follow-up
    Jun-Hyuk Lee, Hye Sun Lee, Yong-Jae Lee
    Nutrition, Metabolism and Cardiovascular Diseases.2020; 30(9): 1484.     CrossRef
  • Metformin treatment for patients with diabetes and chronic kidney disease: A Korean Diabetes Association and Korean Society of Nephrology consensus statement
    Kyu Yeon Hur, Mee Kyoung Kim, Seung Hyun Ko, Miyeun Han, Dong Won Lee, Hyuk-Sang Kwon
    Kidney Research and Clinical Practice.2020; 39(1): 32.     CrossRef
  • The incidence and seasonal variation of necrotizing fasciitis in Korea: a nationwide cross-sectional study
    H.K. Choi, G.H. Seo, E. Han
    Clinical Microbiology and Infection.2020; 26(8): 1090.e1.     CrossRef
  • Triglyceride to HDL-cholesterol ratio and the incidence risk of type 2 diabetes in community dwelling adults: A longitudinal 12-year analysis of the Korean Genome and Epidemiology Study
    Tae-Kyeong Lim, Hye Sun Lee, Yong-Jae Lee
    Diabetes Research and Clinical Practice.2020; 163: 108150.     CrossRef
  • Diabetic Retinopathy and Related Clinical Practice for People with Diabetes in Korea: A 10-Year Trend Analysis
    Yoo-Ri Chung, Kyoung Hwa Ha, Kihwang Lee, Dae Jung Kim
    Diabetes & Metabolism Journal.2020; 44(6): 928.     CrossRef
  • Elderly Hepatocellular Carcinoma Patients: Open or Laparoscopic Approach?
    Jong Man Kim, Sangjin Kim, Jinsoo Rhu, Gyu-Seong Choi, Choon Hyuck David Kwon, Jae-Won Joh
    Cancers.2020; 12(8): 2281.     CrossRef
  • Diabetes and the Risk of Infection: A National Cohort Study
    Eun Jin Kim, Kyoung Hwa Ha, Dae Jung Kim, Young Hwa Choi
    Diabetes & Metabolism Journal.2019; 43(6): 804.     CrossRef
  • Premeal Consumption of a Protein-Enriched, Dietary Fiber-Fortified Bar Decreases Total Energy Intake in Healthy Individuals
    Chang Ho Ahn, Jae Hyun Bae, Young Min Cho
    Diabetes & Metabolism Journal.2019; 43(6): 879.     CrossRef
Original Articles
Obesity and Metabolic Syndrome
Utility of Serum Albumin for Predicting Incident Metabolic Syndrome According to Hyperuricemia
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
Diabetes Metab J. 2018;42(6):529-537.   Published online September 28, 2018
DOI: https://doi.org/10.4093/dmj.2018.0012
  • 4,354 View
  • 47 Download
  • 9 Web of Science
  • 10 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
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.

Methods

In 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.

Results

During 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).

Conclusion

Higher 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.

Citations

Citations to this article as recorded by  
  • Dissecting the risk factors for hyperuricemia in vegetarians in Taiwan
    Kai-Chieh Chang, Sin-Yi Huang, Wen-Hsin Tsai, Hao-Wen Liu, Jia-Sin Liu, Chia-Lin Wu, Ko-Lin Kuo
    Journal of the Chinese Medical Association.2024; 87(4): 393.     CrossRef
  • A predictive model for hyperuricemia among type 2 diabetes mellitus patients in Urumqi, China
    Palizhati Abudureyimu, Yuesheng Pang, Lirun Huang, Qianqian Luo, Xiaozheng Zhang, Yifan Xu, Liang Jiang, Patamu Mohemaiti
    BMC Public Health.2023;[Epub]     CrossRef
  • Synergistic Interaction between Hyperuricemia and Abdominal Obesity as a Risk Factor for Metabolic Syndrome Components in Korean Population
    Min Jin Lee, Ah Reum Khang, Yang Ho Kang, Mi Sook Yun, Dongwon Yi
    Diabetes & Metabolism Journal.2022; 46(5): 756.     CrossRef
  • Nutritional Biomarkers and Heart Rate Variability in Patients with Subacute Stroke
    Eo Jin Park, Seung Don Yoo
    Nutrients.2022; 14(24): 5320.     CrossRef
  • Mean and visit-to-visit variability of glycemia and left ventricular diastolic dysfunction: A longitudinal analysis of 3025 adults with serial echocardiography
    Jiyeon Ahn, Janghyun Koh, Darae Kim, Gyuri Kim, Kyu Yeon Hur, Sang Won Seo, Kyunga Kim, Jae Hyeon Kim, Jeong Hoon Yang, Sang-Man Jin
    Metabolism.2021; 116: 154451.     CrossRef
  • Can biomarkers be used to improve diagnosis and prediction of metabolic syndrome in childhood cancer survivors? A systematic review
    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
    Nermin Karaosmanoglu, Engin Karaaslan, Pınar Ozdemir Cetinkaya
    Archives of Dermatological Research.2020; 312(6): 447.     CrossRef
  • Letter: Increased Serum Angiopoietin-Like 6 Ahead of Metabolic Syndrome in a Prospective Cohort Study (Diabetes Metab J 2019;43:521-9)
    Jin Hwa Kim
    Diabetes & Metabolism Journal.2019; 43(5): 727.     CrossRef
Obesity and Metabolic Syndrome
Serum Calcium and the Risk of Incident Metabolic Syndrome: A 4.3-Year Retrospective Longitudinal Study
Jong Ha Baek, Sang-Man Jin, Ji Cheol Bae, Jae Hwan Jee, Tae Yang Yu, Soo Kyoung Kim, Kyu Yeon Hur, Moon-Kyu Lee, Jae Hyeon Kim
Diabetes Metab J. 2017;41(1):60-68.   Published online December 26, 2016
DOI: https://doi.org/10.4093/dmj.2017.41.1.60
  • 4,033 View
  • 32 Download
  • 9 Web of Science
  • 9 Crossref
AbstractAbstract PDFPubReader   
Background

An association between serum calcium level and risk of metabolic syndrome (MetS) has been suggested in cross-sectional studies. This study aimed to evaluate the association between baseline serum calcium level and risk of incident MetS in a longitudinal study.

Methods

We conducted a retrospective longitudinal study of 12,706 participants without MetS who participated in a health screening program, had normal range serum calcium level at baseline (mean age, 51 years), and were followed up for 4.3 years (18,925 person-years). The risk of developing MetS was analyzed according to the baseline serum calcium levels.

Results

A total of 3,448 incident cases (27.1%) of MetS developed during the follow-up period. The hazard ratio (HR) for incident MetS did not increase with increasing tertile of serum calcium level in an age- and sex-matched model (P for trend=0.915). The HRs (95% confidence interval [CI]) for incident MetS comparing the second and the third tertiles to the first tertile of baseline serum calcium level were 0.91 (95% CI, 0.84 to 0.99) and 0.85 (95% CI, 0.78 to 0.92) in a fully adjusted model, respectively (P for trend=0.001). A decreased risk of incident MetS in higher tertiles of serum calcium level was observed in subjects with central obesity and/or a metabolically unhealthy state at baseline.

Conclusion

There was no positive correlation between baseline serum calcium levels and incident risk of MetS in this longitudinal study. There was an association between higher serum calcium levels and decreased incident MetS in individuals with central obesity or two components of MetS at baseline.

Citations

Citations to this article as recorded by  
  • Independent associations of serum calcium with or without albumin adjustment and serum phosphorus with nonalcoholic fatty liver disease: results from NHANES 1999-2018
    Haolong Qi, Bin Wang, Lei Zhu
    Frontiers in Endocrinology.2024;[Epub]     CrossRef
  • Association of the serum calcium level with metabolic syndrome and its components among adults in Taiwan
    Jer-min Chen, Tai-yin Wu, Yi-fan Wu, Kuan-liang Kuo
    Archives of Endocrinology and Metabolism.2023;[Epub]     CrossRef
  • Elevated Chinese visceral adiposity index increases the risk of stroke in Chinese patients with metabolic syndrome
    Zeyu Liu, Qin Huang, Bi Deng, Minping Wei, Xianjing Feng, Fang Yu, Jie Feng, Yang Du, Jian Xia
    Frontiers in Endocrinology.2023;[Epub]     CrossRef
  • Metformin: Expanding the Scope of Application—Starting Earlier than Yesterday, Canceling Later
    Yulia A. Kononova, Nikolai P. Likhonosov, Alina Yu. Babenko
    International Journal of Molecular Sciences.2022; 23(4): 2363.     CrossRef
  • Metformin in prediabetes: key mechanisms for the prevention of diabetes and cardiometabolic risks
    A. Yu. Babenko
    Meditsinskiy sovet = Medical Council.2022; (10): 96.     CrossRef
  • Calcium and Phosphate Levels are Among Other Factors Associated with Metabolic Syndrome in Patients with Normal Weight


    Kamila Osadnik, Tadeusz Osadnik, Marcin Delijewski, Mateusz Lejawa, Martyna Fronczek, Rafał Reguła, Mariusz Gąsior, Natalia Pawlas
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 1281.     CrossRef
  • Association between selected trace elements and body mass index and waist circumference: A cross sectional study
    Mahnaz Zohal, Saeedeh Jam-Ashkezari, Nasim Namiranian, Amin Moosavi, Akram Ghadiri-Anari
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2019; 13(2): 1293.     CrossRef
  • Letter: Increased Serum Angiopoietin-Like 6 Ahead of Metabolic Syndrome in a Prospective Cohort Study (Diabetes Metab J 2019;43:521-9)
    Jin Hwa Kim
    Diabetes & Metabolism Journal.2019; 43(5): 727.     CrossRef
  • Genotype effects of glucokinase regulator on lipid profiles and glycemic status are modified by circulating calcium levels: results from the Korean Genome and Epidemiology Study
    Oh Yoen Kim, So-Young Kwak, Hyunjung Lim, Min-Jeong Shin
    Nutrition Research.2018; 60: 96.     CrossRef
A Randomized Controlled Trial of an Internet-Based Mentoring Program for Type 1 Diabetes Patients with Inadequate Glycemic Control
Sunghwan Suh, Cheol Jean, Mihyun Koo, Sun Young Lee, Min Ja Cho, Kang-Hee Sim, Sang-Man Jin, Ji Cheol Bae, Jae Hyeon Kim
Diabetes Metab J. 2014;38(2):134-142.   Published online April 18, 2014
DOI: https://doi.org/10.4093/dmj.2014.38.2.134
  • 4,962 View
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  • 21 Web of Science
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AbstractAbstract PDFPubReader   
Background

To determine whether an internet-based mentoring program can improve glycemic control in subjects with type 1 diabetes mellitus (T1DM).

Methods

Subjects with T1DM on intensive insulin therapy and with hemoglobin A1c (HbA1c) ≥8.0% were randomized to mentored (glucometer transmission with feedback from mentors) or control (glucometer transmission without feedback) groups and were examined for 12 weeks. Five mentors were interviewed and selected, of which two were T1DM patients themselves and three were parents with at least one child diagnosed with T1DM since more than 5 years ago.

Results

A total of 57 T1DM adult subjects with a mean duration after being diagnosed with diabetes of 7.4 years were recruited from Samsung Medical Center. Unfortunately, the mentored group failed to show significant improvements in HbA1c levels or other outcomes, including the quality of life, after completion of the study. However, the mentored group monitored their blood glucose (1.41 vs. 0.30) and logged into our website (http://ubisens.co.kr/) more frequently (20.59 times vs. 5.07 times) than the control group.

Conclusion

A 12-week internet-based mentoring program for T1DM patients with inadequate glycemic control did not prove to be superior to the usual follow-up. However, the noted increase in the subjects' frequency of blood glucose monitoring may lead to clinical benefits.

Citations

Citations to this article as recorded by  
  • The Effectiveness of Telemedicine Solutions in Type 1 Diabetes Management: A Systematic Review and Meta-analysis
    Flemming Witt Udsen, Stine Hangaard, Clara Bender, Jonas Andersen, Thomas Kronborg, Peter Vestergaard, Ole Hejlesen, Sisse Laursen
    Journal of Diabetes Science and Technology.2023; 17(3): 782.     CrossRef
  • Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes
    Kristin J Konnyu, Sharlini Yogasingam, Johanie Lépine, Katrina Sullivan, Mostafa Alabousi, Alun Edwards, Michael Hillmer, Sathya Karunananthan, John N Lavis, Stefanie Linklater, Braden J Manns, David Moher, Sameh Mortazhejri, Samir Nazarali, P. Alison Pap
    Cochrane Database of Systematic Reviews.2023;[Epub]     CrossRef
  • Clinical Effects of a Home Care Pilot Program for Patients with Type 1 Diabetes Mellitus: A Retrospective Cohort Study
    Sejeong Lee, KyungYi Kim, Ji Eun Kim, Yura Hyun, Minyoung Lee, Myung-Il Hahm, Sang Gyu Lee, Eun Seok Kang
    Diabetes & Metabolism Journal.2023; 47(5): 693.     CrossRef
  • Evaluation of nurse‐led social media intervention for diabetes self‐management: A mixed‐method study
    Su Hyun Kim, Younghee Kim, Sookyung Choi, Bomin Jeon
    Journal of Nursing Scholarship.2022; 54(5): 569.     CrossRef
  • ISPAD Clinical Practice Consensus Guidelines 2022: Diabetes in adolescence
    John W. Gregory, Fergus J. Cameron, Kriti Joshi, Mirjam Eiswirth, Christopher Garrett, Katharine Garvey, Shivani Agarwal, Ethel Codner
    Pediatric Diabetes.2022; 23(7): 857.     CrossRef
  • Diabetes Self-Management Education and Support to Improve Outcomes for Children and Young Adults With Type 1 Diabetes: An Umbrella Review of Systematic Reviews
    Latika Rohilla, Sukhpal Kaur, Mona Duggal, Prahbhjot Malhi, Bhavneet Bharti, Devi Dayal
    The Science of Diabetes Self-Management and Care.2021; 47(5): 332.     CrossRef
  • Smartphones and Apps to Control Glycosylated Hemoglobin (HbA1c) Level in Diabetes: A Systematic Review and Meta-Analysis
    María Begoña Martos-Cabrera, Almudena Velando-Soriano, Laura Pradas-Hernández, Nora Suleiman-Martos, Guillermo A. Cañadas-De la Fuente, Luis Albendín-García, José L. Gómez-Urquiza
    Journal of Clinical Medicine.2020; 9(3): 693.     CrossRef
  • Are We Ready to Treat Our Diabetes Patients Using Social Media? Yes, We Are
    Goran Petrovski, Marija Zivkovic
    Journal of Diabetes Science and Technology.2019; 13(2): 171.     CrossRef
  • Clinical Effectiveness of Telemedicine in Diabetes Mellitus: A Meta-Analysis of 42 Randomized Controlled Trials
    Huidi Tchero, Pauline Kangambega, Christine Briatte, Solenne Brunet-Houdard, Gerald-Reparate Retali, Emmanuel Rusch
    Telemedicine and e-Health.2019; 25(7): 569.     CrossRef
  • Distal technologies and type 1 diabetes management
    Danny C Duke, Samantha Barry, David V Wagner, Jane Speight, Pratik Choudhary, Michael A Harris
    The Lancet Diabetes & Endocrinology.2018; 6(2): 143.     CrossRef
  • Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study
    Yiyu Zhang, Xia Li, Shuoming Luo, Chaoyuan Liu, Fang Liu, Zhiguang Zhou
    JMIR mHealth and uHealth.2018; 6(9): e11400.     CrossRef
  • An information and communication technology-based centralized clinical trial to determine the efficacy and safety of insulin dose adjustment education based on a smartphone personal health record application: a randomized controlled trial
    Gyuri Kim, Ji Cheol Bae, Byoung Kee Yi, Kyu Yeon Hur, Dong Kyung Chang, Moon-Kyu Lee, Jae Hyeon Kim, Sang-Man Jin
    BMC Medical Informatics and Decision Making.2017;[Epub]     CrossRef
  • Telemedicine for the Management of Glycemic Control and Clinical Outcomes of Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Studies
    Shaun W. H. Lee, Leanne Ooi, Yin K. Lai
    Frontiers in Pharmacology.2017;[Epub]     CrossRef
  • Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials
    Da Tao, Tieyan Wang, Tieshan Wang, Shuang Liu, Xingda Qu
    Journal of the American Medical Informatics Association.2017; 24(5): 1014.     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
  • 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
  • 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
    Applied Clinical Informatics.2016; 07(03): 899.     CrossRef
  • Does telemedicine improve treatment outcomes for diabetes? A meta-analysis of results from 55 randomized controlled trials
    Dejun Su, Junmin Zhou, Megan S. Kelley, Tzeyu L. Michaud, Mohammad Siahpush, Jungyoon Kim, Fernando Wilson, Jim P. Stimpson, José A. Pagán
    Diabetes Research and Clinical Practice.2016; 116: 136.     CrossRef
  • Adherence to Glycemic Monitoring in Diabetes
    Susana R. Patton
    Journal of Diabetes Science and Technology.2015; 9(3): 668.     CrossRef
  • Internet-Based Mentoring Program for Patients with Type 1 Diabetes
    Sun-Hye Ko, Seung-Hyun Ko
    Diabetes & Metabolism Journal.2014; 38(2): 107.     CrossRef
Education as Prescription for Patients with Type 2 Diabetes Mellitus: Compliance and Efficacy in Clinical Practice
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 Metab J. 2012;36(6):452-459.   Published online December 12, 2012
DOI: https://doi.org/10.4093/dmj.2012.36.6.452
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AbstractAbstract PDFPubReader   
Background

Diabetes self-management education has an important role in diabetes management. The efficacy of education has been proven in several randomized trials. However, the status of diabetes education programs in real Korean clinical practice has not yet been evaluated in terms of patient compliance with the education prescription.

Methods

We retrospectively analyzed clinical and laboratory data from all patients who were ordered to undergo diabetes education during 2009 at Samsung Medical Center, Seoul, Korea (n=2,291). After excluding ineligible subjects, 588 patients were included in the analysis.

Results

Among the 588 patients, 433 received education. The overall compliance rate was 73.6%, which was significantly higher in the subjects with a short duration or living in a rural area compared to those with a long duration (85.0% vs. 65.1%, respectively; P<0.001) or living in an urban area (78.2% vs. 70.4%, respectively; P=0.037). The hemoglobin A1c decreased greater in the compliant group (from 7.84±1.54 at baseline to 6.79±1.06 at 3 months and 6.97±1.20 at 12 months after prescription in the compliant group vs. from 7.74±1.25 to 7.14±1.02 and 7.24±1.24 in the non-compliant group; P=0.001). The decrease in hemoglobin A1c was greater in the subjects with a short duration (P=0.032).

Conclusion

In our study a large percent of patients refuse to get education despite having a prescription from their physician. This refusal rate was higher in the patients with long-standing diabetes or in urban residence. Furthermore, education was more effective in patients with a short duration of diabetes in clinical practice.

Citations

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  • Clinical Effects of a Home Care Pilot Program for Patients with Type 1 Diabetes Mellitus: A Retrospective Cohort Study
    Sejeong Lee, KyungYi Kim, Ji Eun Kim, Yura Hyun, Minyoung Lee, Myung-Il Hahm, Sang Gyu Lee, Eun Seok Kang
    Diabetes & Metabolism Journal.2023; 47(5): 693.     CrossRef
  • 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
  • The Effectiveness of Multidisciplinary Team-Based Education in the Management of Type 2 Diabetes
    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
  • The diabetes self-management educational programs and their integration in the usual care: A systematic literature review
    Emmanuel Kumah, Giulia Sciolli, Maria Laura Toraldo, Anna Maria Murante
    Health Policy.2018; 122(8): 866.     CrossRef
  • Diabetes Camp as Continuing Education for Diabetes Self-Management in Middle-Aged and Elderly People with Type 2 Diabetes Mellitus
    So Young Park, Sun Young Kim, Hye Mi Lee, Kyu Yeon Hur, Jae Hyeon Kim, Moon-Kyu Lee, Kang-Hee Sim, Sang-Man Jin
    Diabetes & Metabolism Journal.2017; 41(2): 99.     CrossRef
  • Educational attainment moderates the associations of diabetes education with health outcomes
    Su Hyun Kim
    International Journal of Nursing Practice.2016; 22(5): 444.     CrossRef
  • Experiences of Diabetes Education among Educators of Diabetes : a content analysis approach
    Soo Jin Kang, Soo Jung Chang
    Journal of Korean Public Health Nursing.2016; 30(2): 221.     CrossRef
  • Barrier Factors to the Completion of Diabetes Education in Korean Diabetic Adult Patients: Korea National Health and Nutrition Examination Surveys 2007-2012
    Hee-Tae Kim, Kiheon Lee, Se Young Jung, Seung-Min Oh, Su-Min Jeong, Yoon-Jung Choi
    Korean Journal of Family Medicine.2015; 36(5): 203.     CrossRef
  • Determinants of glycaemic control in a practice setting: the role of weight loss and treatment adherence (The DELTA Study)
    C. McAdam‐Marx, B. K. Bellows, S. Unni, J. Mukherjee, G. Wygant, U. Iloeje, J. N. Liberman, X. Ye, F. J. Bloom, D. I. Brixner
    International Journal of Clinical Practice.2014; 68(11): 1309.     CrossRef
  • Health education via mobile text messaging for glycemic control in adults with type 2 diabetes: A systematic review and meta-analysis
    Mohsen Saffari, Ghader Ghanizadeh, Harold G. Koenig
    Primary Care Diabetes.2014; 8(4): 275.     CrossRef
  • The Appropriateness of the Length of Insulin Needles Based on Determination of Skin and Subcutaneous Fat Thickness in the Abdomen and Upper Arm in Patients with Type 2 Diabetes
    Kang Hee Sim, Moon Sook Hwang, Sun Young Kim, Hye Mi Lee, Ji Yeun Chang, Moon Kyu Lee
    Diabetes & Metabolism Journal.2014; 38(2): 120.     CrossRef
  • Diabetes Attitudes, Wishes and Needs second study (DAWN2™): Cross‐national benchmarking of diabetes‐related psychosocial outcomes for people with diabetes
    A. Nicolucci, K. Kovacs Burns, R. I. G. Holt, M. Comaschi, N. Hermanns, H. Ishii, A. Kokoszka, F. Pouwer, S. E. Skovlund, H. Stuckey, I. Tarkun, M. Vallis, J. Wens, M. Peyrot
    Diabetic Medicine.2013; 30(7): 767.     CrossRef
Smaller Mean LDL Particle Size and Higher Proportion of Small Dense LDL in Korean Type 2 Diabetic Patients
Sunghwan Suh, Hyung-Doo Park, Se Won Kim, Ji Cheol Bae, Alice Hyun-Kyung Tan, Hye Soo Chung, Kyu Yeon Hur, Jae Hyeon Kim, Kwang-Won Kim, Moon-Kyu Lee
Diabetes Metab J. 2011;35(5):536-542.   Published online October 31, 2011
DOI: https://doi.org/10.4093/dmj.2011.35.5.536
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AbstractAbstract PDFPubReader   
Background

Small dense low density lipoprotein (sdLDL) has recently emerged as an important risk factor of coronary heart disease.

Methods

The mean LDL particle size was measured in 203 patients with type 2 diabetes mellitus (T2DM) and 212 matched subjects without diabetes using polyacrylamide tube gel electrophoresis. Major vascular complications were defined as stroke, angiographically-documented coronary artery disease or a myocardial infarction. Peripheral vascular stenosis, carotid artery stenosis (≥50% in diameter) or carotid artery plaque were considered minor vascular complications. Overall vascular complications included both major and minor vascular complications.

Results

Diabetic patients had significantly smaller mean-LDL particle size (26.32 nm vs. 26.49 nm) and a higher percentage of sdLDL to total LDL compared to those of subjects without diabetes (21.39% vs. 6.34%). The independent predictors of sdLDL in this study were serum triglyceride level and body mass index (odds ratio [OR], 1.020 with P<0.001 and OR 1.152 with P<0.027, respectively). However, no significant correlations were found between sdLDL and major vascular complications (P=0.342), minor vascular complications (P=0.573) or overall vascular complications (P=0.262) in diabetic subjects.

Conclusion

Diabetic patients had a smaller mean-LDL particle size and higher proportion of sdLDL compared to those of subjects without diabetes. Obese diabetic patients with hypertriglyceridemia have an increased risk for atherogenic small dense LDL. However, we could not verify an association between LDL particle size and vascular complications in this study.

Citations

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  • Evaluation of measured and calculated small dense low-density lipoprotein in capillary blood and association with the metabolic syndrome
    Sara Deza, Inmaculada Colina, Oscar Beloqui, José Ignacio Monreal, Estéfani Martínez-Chávez, Julia Maroto-García, Carmen Mugueta, Alvaro González, Nerea Varo
    Clinica Chimica Acta.2024; 557: 117897.     CrossRef
  • Association between measured or calculated small dense low‐density lipoprotein cholesterol and oxidized low‐density lipoprotein in subjects with or without type 2 diabetes mellitus
    Hyun‐Ki Kim, Jinyoung Hong, Sunyoung Ahn, Woochang Lee, Sail Chun, Won‐Ki Min
    Journal of Clinical Laboratory Analysis.2023;[Epub]     CrossRef
  • The association of apolipoprotein in the risk of ST-elevation myocardial infarction in patients with documented coronary artery disease
    Astuti Giantini, Nur Gifarani Pratiwi, Renan Sukmawan, Joedo Prihartono, Suzanna Immanuel, Merci Monica Pasaribu, Sri Suryo Adiyanti, Yusuf Bahasoan
    International Journal of Cardiology Cardiovascular Risk and Prevention.2023; 18: 200194.     CrossRef
  • Atherogenic Index of Plasma and Its Association with Risk Factors of Coronary Artery Disease and Nutrient Intake in Korean Adult Men: The 2013–2014 KNHANES
    Hye Ran Shin, SuJin Song, Jin Ah Cho, Sun Yung Ly
    Nutrients.2022; 14(5): 1071.     CrossRef
  • The Atherogenic Index of Plasma: A Powerful and Reliable Predictor for Coronary Artery Disease in Patients With Type 2 Diabetes
    Kuo Zhou, Zheng Qin, Jinfan Tian, Kongyong Cui, Yunfeng Yan, Shuzheng Lyu
    Angiology.2021; 72(10): 934.     CrossRef
  • Direct bilirubin is associated with low-density lipoprotein subfractions and particle size in overweight and centrally obese women
    Y.-J. Kwon, H.-S. Lee, J.-W. Lee
    Nutrition, Metabolism and Cardiovascular Diseases.2018; 28(10): 1021.     CrossRef
  • Correlation between Cholesterol, Triglycerides, Calculated, and Measured Lipoproteins: Whether Calculated Small Density Lipoprotein Fraction Predicts Cardiovascular Risks
    Sikandar Hayat Khan, Nadeem Fazal, Athar Abbas Gilani Shah, Syed Mohsin Manzoor, Naveed Asif, Aamir Ijaz, Najmusaqib Khan Niazi, Muhammad Yasir
    Journal of Lipids.2017; 2017: 1.     CrossRef
  • Effects of Small Dense LDL in Diabetic Nephropathy in Females with Type 2 Diabetes Mellitus
    Seongyul Ryu, Youngwoo Kim, Mee Kyoung Kim, Hyuk-Sang Kwon, Ki-Hyun Baek, Ki-Ho Song, Kyung-Jin Yun
    Journal of Lipid and Atherosclerosis.2016; 5(1): 11.     CrossRef
  • Prepregnancy Adverse Lipid Profile and Subsequent Risk of Gestational Diabetes
    Emily S. Han, Ronald M. Krauss, Fei Xu, Sneha B. Sridhar, Assiamira Ferrara, Charles P. Quesenberry, Monique M. Hedderson
    The Journal of Clinical Endocrinology & Metabolism.2016; 101(7): 2721.     CrossRef
  • Meta-analysis of Atherogenic Index of Plasma and other lipid parameters in relation to risk of type 2 diabetes mellitus
    Xiao-Wei Zhu, Fei-Yan Deng, Shu-Feng Lei
    Primary Care Diabetes.2015; 9(1): 60.     CrossRef
  • Higher levels of small dense low‐density lipoprotein (LDL) are associated with cardiac autonomic neuropathy in patients with Type 2 diabetes
    E.‐H. Jang, Y.‐M. Park, J. Hur, M.‐K. Kim, S.‐H. Ko, K.‐H. Baek, K.‐H. Song, K.‐W. Lee, H.‐S. Kwon
    Diabetic Medicine.2013; 30(6): 694.     CrossRef
  • Sleep Status and Low-Density Lipoprotein Particle Size in a General Japanese Female Population: The Mima Study
    Kazuhiko Kotani, Kokoro Tsuzaki, Shinji Fujiwara, Naoki Sakane
    Medical Principles and Practice.2013; 22(5): 510.     CrossRef
  • Serum small-dense LDL abnormalities in chronic renal disease patients
    M. Chu, A. Y. M. Wang, I. H. S. Chan, S. H. Chui, C. W. K. Lam
    British Journal of Biomedical Science.2012; 69(3): 99.     CrossRef
  • Small Dense Low-density Lipoprotein and Cardiovascular Disease
    Sunghwan Suh, Moon-Kyu Lee
    Journal of Lipid and Atherosclerosis.2012; 1(1): 1.     CrossRef
The Cutoff Value of HbA1c in Predicting Diabetes in Korean Adults in a University Hospital in Seoul.
Ji Cheol Bae, Eun Jung Rhee, Eun Suk Choi, Ji Hoon Kim, Won Jun Kim, Seung Hyun Yoo, Se Eun Park, Cheol Young Park, Won Young Lee, Ki Won Oh, Sung Woo Park, Sun Woo Kim
Korean Diabetes J. 2009;33(6):503-510.   Published online December 1, 2009
DOI: https://doi.org/10.4093/kdj.2009.33.6.503
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AbstractAbstract PDF
BACKGROUND
Glycated hemoglobin (HbA1c) levels represent a 2~3 month average of blood glucose concentration. The use of HbA1c as a diagnostic tool for diabetes is gaining interest. Therefore, we determined the cutoff point of HbA1c for predicting abnormal glucose tolerance status in non-diabetic Korean subjects. METHODS: We analyzed the data from 1,482 subjects without diabetes mellitus in whom a 75-g oral glucose tolerance test (OGTT) was performed due to suspected abnormal glucose tolerance. We obtained an HbA1c cutoff point for predicting diabetes using Receiver Operating Characteristic (ROC) curve analysis. RESULTS: A cut-off point of 5.95% HbA1c yielded sensitivity of 60.8% and specificity of 85.6%, respectively, for predicting diabetes. There was a difference in HbA1c cut-off value between men and women, 5.85% and 6.05%, respectively. CONCLUSION: To use the cut-off point of 5.95% HbA1c for predicting undiagnosed diabetes in Koreans may be reliable. However, studies of different ethnic groups have reported disparate HbA1c cut-off points. Thus, ethnicity, age, gender, and population prevalence of diabetes are important factors to consider in using elevated HbA1c value as a tool to diagnose diabetes.

Citations

Citations to this article as recorded by  
  • The Cutoff Value of HbA1c in Predicting Diabetes and Impaired Fasting Glucose
    Seyoung Kwon, Youngak Na
    The Korean Journal of Clinical Laboratory Science.2017; 49(2): 114.     CrossRef
  • Role of HbA1c in the Screening of Diabetes Mellitus in a Korean Rural Community
    Jae Hyun Kim, Gun Woo Kim, Mi Young Lee, Jang Yel Shin, Young Goo Shin, Sang Baek Koh, Choon Hee Chung
    Diabetes & Metabolism Journal.2012; 36(1): 37.     CrossRef
  • Impact of HbA1c Criterion on the Detection of Subjects with Increased Risk for Diabetes among Health Check-Up Recipients in Korea
    Hong-Kyu Kim, Sung-Jin Bae, Jaeone Choe
    Diabetes & Metabolism Journal.2012; 36(2): 151.     CrossRef
  • The Utility of HbA1c as a Diagnostic Criterion of Diabetes
    Hee-Jung Kim, Eun Young Choi, Eal Whan Park, Yoo Seock Cheong, Hong-Yoen Lee, Ji Hyun Kim
    Korean Journal of Family Medicine.2011; 32(7): 383.     CrossRef
  • 2011 Clinical Practice Guidelines for Type 2 Diabetes in Korea
    Seung-Hyun Ko, Sung-Rea Kim, Dong-Joon Kim, Seung-Joon Oh, Hye-Jin Lee, Kang-Hee Shim, Mi-Hye Woo, Jun-Young Kim, Nan-Hee Kim, Jae-Taik Kim, Chong Hwa Kim, Hae Jin Kim, In-Kyung Jeong, Eun-Kyung Hong, Jae-Hyoung Cho, Ji-Oh Mok, Kun-Ho Yoon
    Diabetes & Metabolism Journal.2011; 35(5): 431.     CrossRef
  • 2011 Clinical Practice Guidelines for Type 2 Diabetes in Korea
    Seung-Hyun Ko, Dong-Joon Kim, Seung-Joon Oh, Hye-Jin Lee, Kang-Hee Shim, Mi-Hye Woo, Jun-Young Kim, Nan-Hee Kim, Jae-Taik Kim, Chong Hwa Kim, Hye Jin Kim, In-Kyung Jeong, Eun-Gyoung Hong, Jae-Hyoung Cho, Ji-Oh Mok, Kun-Ho Yoon, Sung-Rea Kim
    Journal of Korean Diabetes.2011; 12(4): 183.     CrossRef

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