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2018
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Obesity and Metabolic Syndrome
Prediction of Gestational Diabetes Mellitus in Pregnant Korean Women Based on Abdominal Subcutaneous Fat Thickness as Measured by Ultrasonography
Sung Hee Yang, Changsoo Kim, Hyun Sook An, Hyun An, Jin Soo Lee
Diabetes Metab J. 2017;41(6):486-491.   Published online September 22, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.6.486
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  • 23 Web of Science
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AbstractAbstract PDFPubReader   
Background

This study was performed to verify the correlation between abdominal subcutaneous fat thickness (ASFT) measured by ultrasonography (US) during the first trimester of pregnancy and gestational diabetes mellitus (GDM) of the second trimester in Korean women and to establish a standard of ASFT for predicting GDM.

Methods

A total of 333 singleton pregnant women participated in this study. Their ASFT was measured by US during the 10+6 to 13+6 weeks of pregnancy; then a GDM confirmatory test (100 g oral glucose tolerance test) was conducted during the 24 to 28 week period of pregnancy. Based on the GDM tests, comparative analyses of the ages of the subjects, pre-pregnancy body mass index (BMI), and weight gain during pregnancy were conducted.

Results

The ages of the subjects and weight gains during pregnancy were not correlated to the GDM of the second trimester of pregnancy, but the pre-pregnancy BMIs (22±3.3 kg/m2) and the ASFT (1.9±0.5 cm) measurements between the control group and subjects during the first trimester of pregnancy were found to show significant differences (P<0.001). The cut-off value of the ASFT for predicting GDM was determined to be 2.4 cm (area under the curve=0.90, sensitivity 75.61%, specificity 91.78%, P<0.001). The odds ratio was 2.91 (95% confidence interval, 1.07 to 7.92; P=0.034), which was higher than the 2.4 cm ASFT.

Conclusion

It was determined that ASFT as measured by US during the first trimester of pregnancy can be used to predict the risk of developing GDM during the second trimester of pregnancy and for prognosis.

Citations

Citations to this article as recorded by  
  • Abdominal subcutaneous fat thickness combined with a 50-g glucose challenge test at 24-28 weeks of pregnancy in predicting gestational diabetes mellitus
    Süleyman Cemil Oğlak, Emine Zeynep Yılmaz, Mehmet Şükrü Budak
    Journal of Obstetrics and Gynaecology.2024;[Epub]     CrossRef
  • The Value of Maternal Upper Abdominal Ad-ipose Thickness in Predicting GDM in Early Pregnancy
    娜娜 郭
    Advances in Clinical Medicine.2023; 13(03): 4702.     CrossRef
  • Evaluating the Adipose Tissue Depth as a Predictor Factor for Gestational Diabetes in Later Pregnancy—A Systematic Review
    Bianca-Margareta Salmen, Valeria-Anca Pietrosel, Cristiana-Elena Durdu, Teodor Salmen, Cosmina Theodora Diaconu, Ioana-Cristina Bica, Claudia Gabriela Potcovaru, Florentina Gherghiceanu, Roxana-Adriana Stoica, Anca Pantea Stoian
    Biomedicines.2023; 11(5): 1492.     CrossRef
  • The Association Between Body Fat Index and Gestational Diabetes Mellitus: A Prospective Cohort Study
    Sawanya Benchahong, Prasert Sunsaneevithayakul, Dittakarn Boriboonhirunsarn
    Cureus.2023;[Epub]     CrossRef
  • Ultrasound evaluation of subcutaneous and visceral abdominal fat as a predictor of gestational diabetes mellitus: a systematic review
    Fernanda Teixeira Benevides, Edward Araujo Júnior, Carla Soraya Costa Maia, Renan Magalhães Montenegro Junior, Francisco Herlânio Costa Carvalho
    The Journal of Maternal-Fetal & Neonatal Medicine.2022; 35(11): 2216.     CrossRef
  • The Early Sonographic Prediction of Gestational Diabetes in Women From India
    Shivani Gupta, Arjun Gupta, C. P. Swarnakar, Monika Rathore, Ramesh Beniwal, Kiran Meena, Anita Simlot, Nidhi Gupta
    Journal of Diagnostic Medical Sonography.2022; 38(1): 18.     CrossRef
  • Can maternal abdominal fat thickness predict antenatal insulin therapy in patients with gestational diabetes mellitus?
    Sedat Akgöl, Mehmet Şükrü Budak, Süleyman Cemil Oğlak, Fatma Ölmez, Mehmet Emin Dilek, Serhat Kartal
    Journal of Obstetrics and Gynaecology Research.2022; 48(3): 634.     CrossRef
  • Prediction of gestational diabetes mellitus by different obesity indices
    Zhimin Song, Yan Cheng, Tingting Li, Yongfang Fan, Qingying Zhang, Haidong Cheng
    BMC Pregnancy and Childbirth.2022;[Epub]     CrossRef
  • Association between maternal adiposity measures and adverse maternal outcomes of pregnancy: Systematic review and meta‐analysis
    Nicola Heslehurst, Lem Ngongalah, Theophile Bigirumurame, Giang Nguyen, Adefisayo Odeniyi, Angela Flynn, Vikki Smith, Lisa Crowe, Becky Skidmore, Laura Gaudet, Alexandre Simon, Louise Hayes
    Obesity Reviews.2022;[Epub]     CrossRef
  • Association of body composition in early pregnancy with gestational diabetes mellitus: A meta-analysis
    Fatemeh Alsadat Rahnemaei, Fatemeh Abdi, Reza Pakzad, Seyedeh Hajar Sharami, Fatemeh Mokhtari, Elham Kazemian, Rajakumar Anbazhagan
    PLOS ONE.2022; 17(8): e0271068.     CrossRef
  • Early Gestational Diabetes Detection Using Neural Network
    Tanzina Rahman Hera, Md. Ashikur Rahman Khan, Nishu Nath
    WSEAS TRANSACTIONS ON BIOLOGY AND BIOMEDICINE.2021; 18: 1.     CrossRef
  • The association of general obesity, central obesity and visceral body fat with the risk of gestational diabetes mellitus: Evidence from a systematic review and meta-analysis
    Sura M. Alwash, H. David McIntyre, Abdullah Mamun
    Obesity Research & Clinical Practice.2021; 15(5): 425.     CrossRef
  • Abdominal skin subcutaneous fat thickness over the gestational period in Korean pregnant women: a descriptive observational study
    Moon Sook Hwang
    Korean Journal of Women Health Nursing.2021; 27(4): 318.     CrossRef
  • Relationship between Maternal Central Obesity and the Risk of Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis of Cohort Studies
    Da Yao, Qing Chang, Qi-Jun Wu, Shan-Yan Gao, Huan Zhao, Ya-Shu Liu, Yu-Ting Jiang, Yu-Hong Zhao
    Journal of Diabetes Research.2020; 2020: 1.     CrossRef
  • Maternal Adipose Tissue Expansion, A Missing Link in the Prediction of Birth Weight Centile
    Eleanor M Jarvie, Frances M Stewart, Jane E Ramsay, E Ann Brown, Barbara J Meyer, Gunilla Olivecrona, Bruce A Griffin, Dilys J Freeman
    The Journal of Clinical Endocrinology & Metabolism.2020; 105(3): e814.     CrossRef
  • Ultrasound assessment of maternal adipose tissue during 1st trimester screening for aneuploidies and risk of developing gestational diabetes
    Francesco D’Ambrosi, Gabriele Rossi, Chiara M. Soldavini, Matteo Di Maso, Ilma F. Carbone, Giulia E. Cetera, Enrico Colosi, Enrico Ferrazzi
    Acta Obstetricia et Gynecologica Scandinavica.2020; 99(5): 644.     CrossRef
  • Vitamin D Deficiency at Mid-Pregnancy Is Associated with a Higher Risk of Postpartum Glucose Intolerance in Women with Gestational Diabetes Mellitus
    Kyung-Soo Kim, Seok Won Park, Yong-Wook Cho, Soo-Kyung Kim
    Endocrinology and Metabolism.2020; 35(1): 97.     CrossRef
  • Fetal pancreatic hyperechogenicity may be an early ultrasonographic sign of gestational diabetes mellitus
    Hatice Akkaya, Barış Büke, Gülsüm Uysal
    The Journal of Maternal-Fetal & Neonatal Medicine.2020; 33(14): 2387.     CrossRef
  • The Body Composition in Early Pregnancy is Associated with the Risk of Development of Gestational Diabetes Mellitus Late During the Second Trimester


    Yanping Liu, Jing Liu, Yinjie Gao, Dan Zheng, Wei Pan, Min Nie, Liangkun Ma
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 2367.     CrossRef
  • New Diagnostic Criteria for Gestational Diabetes Mellitus and Pregnancy Outcomes in Korea
    Kyu Yeon Hur
    Diabetes & Metabolism Journal.2019; 43(6): 763.     CrossRef
  • Inter and intra-reliability of ultrasonography for the measurement of abdominal subcutaneous & visceral adipose tissue thickness at 12 weeks gestation
    Alexandra Cremona, Kevin Hayes, Clodagh S. O’Gorman, Ciara Ní Laighin, Khadijah I. Ismail, Alan E. Donnelly, Jill Hamilton, Amanda Cotter
    BMC Medical Imaging.2019;[Epub]     CrossRef
  • Maternal abdominal subcutaneous fat thickness as a simple predictor for gestational diabetes mellitus
    Mehmet Sukru Budak, Ilker Kahramanoglu, Salvatore Giovanni Vitale, Sedat Akgol, Mehmet Emin Dilek, Serhat Kartal, Salvatore Caruso, Bekir Kahveci, Mehmet Obut, Muhammed Hanifi Bademkiran, Antonio Cianci
    Journal of Perinatal Medicine.2019; 47(6): 605.     CrossRef
  • Hypertriglyceridemia and Waist Phenotype as Markers in the Prediction of Gestational Diabetes in Iraqi Women
    Faris Anwer Rasheed, Raghad Hasan Mshattat, Ulfat Mohammad Alnakkash, Saad Abdulrahma
    Research Journal of Obstetrics and Gynecology.2018; 11(1): 25.     CrossRef
  • The importance of treating mild hyperglycemia in pregnant women with diabetes
    Kyung-Soo Kim
    The Korean Journal of Internal Medicine.2018; 33(6): 1079.     CrossRef
  • Anthropometric and ultrasound measures of maternal adiposity in the first trimester of pregnancy
    Narelle Kennedy, Ann Quinton, Michael John Peek, Valeria Lanzarone, Ron Benzie, Ralph Nanan
    Australasian Journal of Ultrasound in Medicine.2018; 21(3): 147.     CrossRef
  • Simple Screening Using Ultrasonography for Prediction of Gestational Diabetes Mellitus
    Seung Min Chung, Jun Sung Moon
    Diabetes & Metabolism Journal.2017; 41(6): 438.     CrossRef
Others
Generation of Insulin-Expressing Cells in Mouse Small Intestine by Pdx1, MafA, and BETA2/NeuroD
So-Hyun Lee, Marie Rhee, Ji-Won Kim, Kun-Ho Yoon
Diabetes Metab J. 2017;41(5):405-416.   Published online September 5, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.5.405
  • 5,211 View
  • 64 Download
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AbstractAbstract PDFSupplementary MaterialPubReader   
Background

To develop surrogate insulin-producing cells for diabetes therapy, adult stem cells have been identified in various tissues and studied for their conversion into β-cells. Pancreatic progenitor cells are derived from the endodermal epithelium and formed in a manner similar to gut progenitor cells. Here, we generated insulin-producing cells from the intestinal epithelial cells that induced many of the specific pancreatic transcription factors using adenoviral vectors carrying three genes: PMB (pancreatic and duodenal homeobox 1 [Pdx1], V-maf musculoaponeurotic fibrosarcoma oncogene homolog A [MafA], and BETA2/NeuroD).

Methods

By direct injection into the intestine through the cranial mesenteric artery, adenoviruses (Ad) were successfully delivered to the entire intestine. After virus injection, we could confirm that the small intestine of the mouse was appropriately infected with the Ad-Pdx1 and triple Ad-PMB.

Results

Four weeks after the injection, insulin mRNA was expressed in the small intestine, and the insulin gene expression was induced in Ad-Pdx1 and Ad-PMB compared to control Ad-green fluorescent protein. In addition, the conversion of intestinal cells into insulin-expressing cells was detected in parts of the crypts and villi located in the small intestine.

Conclusion

These data indicated that PMB facilitate the differentiation of mouse intestinal cells into insulin-expressing cells. In conclusion, the small intestine is an accessible and abundant source of surrogate insulin-producing cells.

Citations

Citations to this article as recorded by  
  • Harnessing gut cells for functional insulin production: Strategies and challenges
    Kelvin Baafi, John C. March
    Biotechnology Notes.2023; 4: 7.     CrossRef
  • Differential Morphological Diagnosis of Various Forms of Congenital Hyperinsulinism in Children
    Lubov Borisovna Mitrofanova, Anastasia Arkadyevna Perminova, Daria Viktorovna Ryzhkova, Anna Andreyevna Sukhotskaya, Vladimir Gireyevich Bairov, Irina Leorovna Nikitina
    Frontiers in Endocrinology.2021;[Epub]     CrossRef
  • Generation of iPSC-derived insulin-producing cells from patients with type 1 and type 2 diabetes compared with healthy control
    Min Jung Kim, Eun Young Lee, Young-Hye You, Hae Kyung Yang, Kun-Ho Yoon, Ji-Won Kim
    Stem Cell Research.2020; 48: 101958.     CrossRef
  • ERK Regulates NeuroD1-mediated Neurite Outgrowth via Proteasomal Degradation
    Tae-young Lee, In-Su Cho, Narayan Bashyal, Francisco J Naya, Ming-Jer Tsai, Jeong Seon Yoon, Jung-Mi Choi, Chang-Hwan Park, Sung-Soo Kim, Haeyoung Suh-Kim
    Experimental Neurobiology.2020; 29(3): 189.     CrossRef
  • Generation of a PDX1–EGFP reporter human induced pluripotent stem cell line, KSCBi005-A-3, using the CRISPR/Cas9 system
    Youngsun Lee, Hye Young Choi, Ara Kwon, Hyeyeon Park, Mi-Hyun Park, Ji-Won Kim, Min Jung Kim, Yong-Ou Kim, Sungwook Kwak, Soo Kyung Koo
    Stem Cell Research.2019; 41: 101632.     CrossRef
Clinical Diabetes & Therapeutics
Determinants of Long-Term Durable Glycemic Control in New-Onset Type 2 Diabetes Mellitus
Kyoung Jin Kim, Ju Hee Choi, Kyeong Jin Kim, Jee Hyun An, Hee Young Kim, Sin Gon Kim, Nam Hoon Kim
Diabetes Metab J. 2017;41(4):284-295.   Published online August 3, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.4.284
  • 4,465 View
  • 81 Download
  • 11 Web of Science
  • 11 Crossref
AbstractAbstract PDFSupplementary MaterialPubReader   
Background

Long-term durable glycemic control is a difficult goal in the management of type 2 diabetes mellitus (T2DM). We evaluated the factors associated with durable glycemic control in a real clinical setting.

Methods

We retrospectively reviewed the medical records of 194 new-onset, drug-naïve patients with T2DM who were diagnosed between January 2011 and March 2013, and were followed up for >2 years. Glycemic durability was defined as the maintenance of optimal glycemic control (glycosylated hemoglobin [HbA1c] <7.0%) for 2 years without substitution or adding other glucose-lowering agents. Clinical factors and glycemic markers associated with glycemic durability were compared between two groups: a durability group and a non-durability group.

Results

Patients in the durability group had a higher baseline body mass index (26.1 kg/m2 vs. 24.9 kg/m2) and lower HbA1c (8.6% vs. 9.7%) than the non-durability group. The initial choice of glucose-lowering agents was similar in both groups, except for insulin and sulfonylureas, which were more frequently prescribed in the non-durability group. In multiple logistic regression analyses, higher levels of education, physical activity, and homeostasis model assessment of β-cell function (HOMA-β) were associated with glycemic durability. Notably, lower HbA1c (<7.0%) at baseline and first follow-up were significantly associated with glycemic durability (adjusted odds ratio [OR], 7.48; 95% confidence interval [CI], 2.51 to 22.3) (adjusted OR, 9.27; 95% CI, 1.62 to 53.1, respectively), after adjusting for confounding variables including the types of glucose-lowering agents.

Conclusion

Early achievement of HbA1c level within the glycemic target was a determinant of long-term glycemic durability in new-onset T2DM, as were higher levels of education, physical activity, and HOMA-β.

Citations

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  • Initial Combination Therapy in Type 2 Diabetes
    Ji Yoon Kim, Nam Hoon Kim
    Endocrinology and Metabolism.2024; 39(1): 23.     CrossRef
  • Validation of RSSDI therapeutic wheel with clinical experience of Indian physicians
    Dhruvi Hasnani, Vipul Chavda, Dinesh Agrawal, Bijay Patni, Ashwin David, Sachin Gathe, Rajeev Chawla, Jothydev Kesavadev, Sunil Gupta, Shriji Hasnani, Banshi Saboo
    International Journal of Diabetes in Developing Countries.2022; 42(3): 451.     CrossRef
  • Greater Glycemic Burden Is Associated with Further Poorer Glycemic Control in Newly-Diagnosed Type 2 Diabetes Mellitus Patients
    Wei-Lun Wen, Hui-Chun Huang, Hsiu-Chu Lin, Wan-Ching Lo, Szu-Chia Chen, Mei-Yueh Lee
    Nutrients.2022; 14(2): 320.     CrossRef
  • Durability of glucose-lowering effect of dulaglutide in patients with type 2 diabetes mellitus: A real-world data study
    Hwi Seung Kim, Yun Kyung Cho, Myung Jin Kim, Chang Hee Jung, Joong-Yeol Park, Woo Je Lee
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Durability of glycaemic control in type 2 diabetes: A systematic review and meta‐analysis for its association with body weight changes
    Danpei Li, HuaJie Zou, Ping Yin, Wenjun Li, Junyu He, Shuyun Wang, Li Huang, Shiying Shao, Yong Chen, Yan Yang, Xuefeng Yu
    Diabetes, Obesity and Metabolism.2021; 23(1): 208.     CrossRef
  • Early combination versus initial metformin monotherapy in the management of newly diagnosed type 2 diabetes: AnEast Asianperspective
    Linong Ji, Juliana C. N. Chan, Miao Yu, Kun Ho Yoon, Sin Gon Kim, Sung Hee Choi, Chien‐Ning Huang, Shih Te Tu, Chih‐Yuan Wang, Päivi Maria Paldánius, Wayne H. H. Sheu
    Diabetes, Obesity and Metabolism.2021; 23(1): 3.     CrossRef
  • Time to Reach Target Glycosylated Hemoglobin Is Associated with Long-Term Durable Glycemic Control and Risk of Diabetic Complications in Patients with Newly Diagnosed Type 2 Diabetes Mellitus: A 6-Year Observational Study
    Kyoung Jin Kim, Jimi Choi, Jae Hyun Bae, Kyeong Jin Kim, Hye Jin Yoo, Ji A Seo, Nan Hee Kim, Kyung Mook Choi, Sei Hyun Baik, Sin Gon Kim, Nam Hoon Kim
    Diabetes & Metabolism Journal.2021; 45(3): 368.     CrossRef
  • Effectiveness of Resistance Training and Associated Program Characteristics in Patients at Risk for Type 2 Diabetes: a Systematic Review and Meta-analysis
    Raza Qadir, Nicholas F. Sculthorpe, Taylor Todd, Elise C. Brown
    Sports Medicine - Open.2021;[Epub]     CrossRef
  • Time to Reach Target Glycosylated Hemoglobin Is Associated with Long-Term Durable Glycemic Control and Risk of Diabetic Complications in Patients with Newly Diagnosed Type 2 Diabetes Mellitus: A 6-Year Observational Study (Diabetes Metab J 2021;45:368-78)
    Ja Young Jeon
    Diabetes & Metabolism Journal.2021; 45(4): 613.     CrossRef
  • Association of Habitual Daily Physical Activity With Glucose Tolerance and β-Cell Function in Adults With Impaired Glucose Tolerance or Recently Diagnosed Type 2 Diabetes From the Restoring Insulin Secretion (RISE) Study
    Karla A. Temple, Ashley H. Tjaden, Karen M. Atkinson, Elena Barengolts, Tamara S. Hannon, Kieren J. Mather, Kristina M. Utzschneider, Sharon L. Edelstein, David A. Ehrmann, Babak Mokhlesi, Philip S. Zeitler, Jayne Williams, Melanie Cree-Green, Yesenia Gar
    Diabetes Care.2019; 42(8): 1521.     CrossRef
  • Factors Associated with Poor Hemoglobin A1c Control in Patients with Type 2 Diabetes
    Salam Alqudah, Anan S. Jarab, Eman A. Alefishat, Fadia Mayyas, Maher Khdour, Sharrel Pinto
    Current Diabetes Reviews.2019; 15(2): 164.     CrossRef
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
  • 4,939 View
  • 40 Download
  • 8 Web of Science
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AbstractAbstract PDFPubReader   
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.

Citations

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  • Exploring Quantitative Methodologies for Assessing the Environmental, Social, and Economic Impacts of Telemedicine: A Literature Review
    Anna Savoldelli, Daniele Landi, Caterina Rizzi
    Sustainability.2024; 16(6): 2438.     CrossRef
  • Telemedicine for Diabetes Mellitus Management in Older Adults: A Systematic Review
    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
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  • Effects of the Physician–Primary-Healthcare Nurse Telemedicine Model (P-NTM) on Medication Adherence and Health-Related Quality of Life (HRQoL) of Patients with Chronic Disease at Remote Rural Areas
    Mi Young Kwak, Eun Jeong Hwang, Tae Ho Lee
    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
    Endocrinology and Metabolism.2020; 35(3): 541.     CrossRef
  • Apprehensions about Excessive Belief in Digital Therapeutics: Points of Concern Excluding Merits
    Hun-Sung Kim
    Journal of Korean Medical Science.2020;[Epub]     CrossRef
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    Ji-Hee Sung, Da Young Lee, Kyoung Pil Min, Cheol-Young Park
    Clinical Therapeutics.2019; 41(11): 2426.     CrossRef
  • 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
Others
Addition of Ipragliflozin to Metformin Treatment in Korean Patients with Type 2 Diabetes Mellitus: Subgroup Analysis of a Phase 3 Trial
Kyung-Wan Min, Bon Jeong Ku, Ji-Hyun Lee, Min-Seon Kim, Kyu-Jeung Ahn, Moon-Kyu Lee, Satoshi Kokubo, Satoshi Yoshida, Hyun-Ji Cho, Bong-Soo Cha
Diabetes Metab J. 2017;41(2):135-145.   Published online January 11, 2017
DOI: https://doi.org/10.4093/dmj.2017.41.2.135
  • 5,159 View
  • 59 Download
  • 14 Web of Science
  • 14 Crossref
AbstractAbstract PDFPubReader   
Background

This is a subgroup analysis of Korean patients from a phase 3 clinical trial investigating the efficacy and safety of ipragliflozin in patients with type 2 diabetes mellitus inadequately controlled with metformin.

Methods

This multicenter, placebo-controlled, double-blind, parallel-group study was carried out between November 2011 and January 2013. Patients entered a 2-week placebo pretreatment period, followed by a 24-week treatment period with either ipragliflozin (50 mg/day) or placebo, while continuing metformin. Efficacy outcomes (glycosylated hemoglobin [HbA1c], fasting plasma glucose [FPG], and body weight) and safety outcomes (treatment-emergent adverse events [TEAEs]) were measured and compared between the two treatment groups for patients enrolled in all 18 study sites in Korea.

Results

Eighty-two Korean patients received ipragliflozin (n=43) or placebo (n=39) during the study period. Mean changes in HbA1c levels from baseline to the end of treatment were –0.97% in the ipragliflozin group and –0.31% in the placebo group, with an adjusted between-group difference of –0.60% (P<0.001). Compared to placebo, FPG and body weight also decreased significantly (both P<0.001) from baseline after treatment in the ipragliflozin group, with between-group differences of –21.4 mg/dL and –1.53 kg, respectively. Decreased weight was the most common TEAE in the ipragliflozin group (7.0%); there were no reports of genital and urinary tract infection.

Conclusion

Ipragliflozin treatment in addition to metformin led to significant improvement in glycemic outcomes and reduction in body weight in Korean patients with type 2 diabetes mellitus, compared with metformin treatment alone; the safety profile was comparable in both groups.

Citations

Citations to this article as recorded by  
  • Effects of sodium-glucose cotransporter 2 inhibitors on bone metabolism in patients with type 2 diabetes mellitus: a systematic review and meta-analysis
    Jing Wang, Xin Li, Yang Li, Chen Lei
    BMC Endocrine Disorders.2024;[Epub]     CrossRef
  • Add-on therapy with dapagliflozin in routine outpatient care of type 2 diabetes patients from Turkey: a retrospective cohort study on HbA1c, body weight, and blood pressure outcomes
    Derun Taner Ertugrul, Erdal Kan, Cigdem Bahadir Tura, Haci Bayram Tugtekin, Hayati Ayakta, Mehmet Celebioglu, Ceren Yılmaz, Onur Utebay, Ilhan Yetkin, Eren Gurkan, Kerem Sezer, Ramazan Gen, Suleyman Ozcaylak, Yildiz Okuturlar, Mehmet Coskun, Nilgun Govec
    International Journal of Diabetes in Developing Countries.2022; 42(1): 147.     CrossRef
  • SGLT2 Inhibitors as Add-On Therapy to Metformin for People with Type 2 Diabetes: A Review of Placebo-Controlled Trials in Asian versus Non-Asian Patients


    André J Scheen
    Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 2765.     CrossRef
  • Ipragliflozin Additively Ameliorates Non-Alcoholic Fatty Liver Disease in Patients with Type 2 Diabetes Controlled with Metformin and Pioglitazone: A 24-Week Randomized Controlled Trial
    Eugene Han, Yong-ho Lee, Byung-Wan Lee, Eun Seok Kang, Bong-Soo Cha
    Journal of Clinical Medicine.2020; 9(1): 259.     CrossRef
  • Safety of Ipragliflozin in Patients with Type 2 Diabetes Mellitus: Pooled Analysis of Phase II/III/IV Clinical Trials
    Atsunori Kashiwagi, Marina V. Shestakova, Yuichiro Ito, Masahiro Noguchi, Wim Wilpshaar, Satoshi Yoshida, John P. H. Wilding
    Diabetes Therapy.2019; 10(6): 2201.     CrossRef
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    Habib Yaribeygi, Stephen L. Atkin, Amirhossein Sahebkar
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2019; 13(2): 1679.     CrossRef
  • Ipragliflozin as an add-on therapy in type 2 diabetes mellitus patients: An evidence-based pharmacoeconomics evaluation
    Hongmei Wang, Gaoqiong Yao, Xi Chen, Jing Ouyang, Jiadan Yang
    Diabetes Research and Clinical Practice.2019; 157: 107867.     CrossRef
  • Characteristics of Dapagliflozin Responders: A Longitudinal, Prospective, Nationwide Dapagliflozin Surveillance Study in Korea
    Eugene Han, Ari Kim, Sung Jae Lee, Je-Yon Kim, Jae Hyeon Kim, Woo Je Lee, Byung-Wan Lee
    Diabetes Therapy.2018; 9(4): 1689.     CrossRef
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Diabetes Metab J : Diabetes & Metabolism Journal