Endocrinology and Metabolism

Jin Yu

6 Articles

Thyroid
The Early Changes in Thyroid-Stimulating Immunoglobulin Bioassay over Anti-Thyroid Drug Treatment Could Predict Prognosis of Graves’ Disease: Jin Yu, Han-Sang Baek, Chaiho Jeong, Kwanhoon Jo, Jeongmin Lee, Jeonghoon Ha, Min Hee Kim, Jungmin Lee, Dong-Jun Lim; Endocrinol Metab. 2023;38(3):338-346. Published online June 9, 2023; DOI: https://doi.org/10.3803/EnM.2023.1664

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Background
To determine whether baseline thyroid-stimulating immunoglobulin (TSI) bioassay or its early response upon treatment with an anti-thyroid drug (ATD) can predict prognosis of Graves’ disease (GD) in real-world practice.
Methods
This retrospective study enrolled GD patients who had previous ATD treatment with TSI bioassay checked at baseline and at follow-up from April 2010 to November 2019 in one referral hospital. The study population were divided into two groups: patients who experienced relapse or continued ATD (relapse/persistence), and patients who experienced no relapse after ATD discontinuation (remission). The slope and area under the curve at 1st year (AUC_1yr) of thyroid-stimulating hormone receptor antibodies including TSI bioassay and thyrotropin-binding inhibitory immunoglobulin (TBII) were calculated as differences between baseline and second values divided by time duration (year).
Results
Among enrolled 156 study subjects, 74 (47.4%) had relapse/persistence. Baseline TSI bioassay values did not show significant differences between the two groups. However, the relapse/persistence group showed less decremental TSI bioassay in response to ATD than the remission group (–84.7 [TSI slope, –198.2 to 8.2] vs. –120.1 [TSI slope, –204.4 to –45.9], P=0.026), whereas the TBII slope was not significantly different between the two groups. The relapse/persistence group showed higher AUC_1yr of TSI bioassay and TBII in the 1st year during ATD treatment than the remission group (AUC_1yr for TSI bioassay, P=0.0125; AUC_1yr for TBII, P=0.001).
Conclusion
Early changes in TSI bioassay can better predict prognosis of GD than TBII. Measurement of TSI bioassay at beginning and follow-up could help predict GD prognosis.

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A Predictive Model for Graves’ Disease Recurrence After Antithyroid Drug Therapy: A Retrospective Multicenter Cohort Study
Omar El Kawkgi, David Toro-Tobon, Freddy J.K. Toloza, Sebastian Vallejo, Cristian Soto Jacome, Ivan N. Ayala, Bryan A. Vallejo, Camila Wenczenovicz, Olivia Tzeng, Horace J. Spencer, Jeff D. Thostenson, Dingfeng Li, Jacob Kohlenberg, Eddy Lincango, Sneha M
Endocrine Practice.2025; 31(4): 455. CrossRef
Enhanced predictive validity of integrative models for refractory hyperthyroidism considering baseline and early therapy characteristics: a prospective cohort study
Xinpan Wang, Tiantian Li, Yue Li, Qiuyi Wang, Yun Cai, Zhixiao Wang, Yun Shi, Tao Yang, Xuqin Zheng
Journal of Translational Medicine.2024;[Epub] CrossRef
Long-term Effect of Thyrotropin-binding Inhibitor Immunoglobulin on Atrial Fibrillation in Euthyroid Patients
Jung-Chi Hsu, Kang-Chih Fan, Ting-Chuan Wang, Shu-Lin Chuang, Ying-Ting Chao, Ting-Tse Lin, Kuan-Chih Huang, Lian-Yu Lin, Lung-Chun Lin
Endocrine Practice.2024; 30(6): 537. CrossRef
Dynamic Risk Model for the Medical Treatment of Graves’ Hyperthyroidism according to Treatment Duration
Meihua Jin, Chae A Kim, Min Ji Jeon, Won Bae Kim, Tae Yong Kim, Won Gu Kim
Endocrinology and Metabolism.2024; 39(4): 579. CrossRef

Diabetes, Obesity and Metabolism Big Data Articles (National Health Insurance Service Database)
Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea: Seung-Hwan Lee, Jin Yu, Kyungdo Han, Seung Woo Lee, Sang Youn You, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Mee Kyoung Kim; Endocrinol Metab. 2023;38(1):129-138. Published online January 27, 2023; DOI: https://doi.org/10.3803/EnM.2022.1609

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Background
The severity of gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes. We aimed to generate a risk model for predicting insulin-requiring GDM before pregnancy in Korean women.
Methods
A total of 417,210 women who received a health examination within 52 weeks before pregnancy and delivered between 2011 and 2015 were recruited from the Korean National Health Insurance database. The risk prediction model was created using a sample of 70% of the participants, while the remaining 30% were used for internal validation. Risk scores were assigned based on the hazard ratios for each risk factor in the multivariable Cox proportional hazards regression model. Six risk variables were selected, and a risk nomogram was created to estimate the risk of insulin-requiring GDM.
Results
A total of 2,891 (0.69%) women developed insulin-requiring GDM. Age, body mass index (BMI), current smoking, fasting blood glucose (FBG), total cholesterol, and γ-glutamyl transferase were significant risk factors for insulin-requiring GDM and were incorporated into the risk model. Among the variables, old age, high BMI, and high FBG level were the main contributors to an increased risk of insulin-requiring GDM. The concordance index of the risk model for predicting insulin-requiring GDM was 0.783 (95% confidence interval, 0.766 to 0.799). The validation cohort’s incidence rates for insulin-requiring GDM were consistent with the risk model’s predictions.
Conclusion
A novel risk engine was generated to predict insulin-requiring GDM among Korean women. This model may provide helpful information for identifying high-risk women and enhancing prepregnancy care.

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Establishment and validation of a nomogram to predict the neck contracture after skin grafting in burn patients: A multicentre cohort study
Rui Li, Yangyang Zheng, Xijuan Fan, Zilong Cao, Qiang Yue, Jincai Fan, Cheng Gan, Hu Jiao, Liqiang Liu
International Wound Journal.2023; 20(9): 3648. CrossRef
Predicting the Need for Insulin Treatment: A Risk-Based Approach to the Management of Women with Gestational Diabetes Mellitus
Anna S. Koefoed, H. David McIntyre, Kristen S. Gibbons, Charlotte W. Poulsen, Jens Fuglsang, Per G. Ovesen
Reproductive Medicine.2023; 4(3): 133. CrossRef
Prepregnancy Glucose Levels Within Normal Range and Its Impact on Obstetric Complications in Subsequent Pregnancy: A Population Cohort Study
Ho Yeon Kim, Ki Hoon Ahn, Geum Joon Cho, Soon-Cheol Hong, Min-Jeong Oh, Hai-Joong Kim
Journal of Korean Medical Science.2023;[Epub] CrossRef
Risk of Cause-Specific Mortality across Glucose Spectrum in Elderly People: A Nationwide Population-Based Cohort Study
Joonyub Lee, Hun-Sung Kim, Kee-Ho Song, Soon Jib Yoo, Kyungdo Han, Seung-Hwan Lee
Endocrinology and Metabolism.2023; 38(5): 525. CrossRef
The CHANGED Score—A New Tool for the Prediction of Insulin Dependency in Gestational Diabetes
Paul Rostin, Selina Balke, Dorota Sroka, Laura Fangmann, Petra Weid, Wolfgang Henrich, Josefine Theresia Königbauer
Journal of Clinical Medicine.2023; 12(22): 7169. CrossRef

Diabetes, Obesity and Metabolism
Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes (Endocrinol Metab 2022;37:641-51, Han-sang Baek et al.): Han-sang Baek, Ji-Yeon Park, Jin Yu, Joonyub Lee, Yeoree Yang, Jeonghoon Ha, Seung Hwan Lee, Jae Hyoung Cho, Dong-Jun Lim, Hun-Sung Kim; Endocrinol Metab. 2022;37(6):945-946. Published online December 2, 2022; DOI: https://doi.org/10.3803/EnM.2022.602

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Diabetes, Obesity and Metabolism
Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes: Han-sang Baek, Ji-Yeon Park, Jin Yu, Joonyub Lee, Yeoree Yang, Jeonghoon Ha, Seung Hwan Lee, Jae Hyoung Cho, Dong-Jun Lim, Hun-Sung Kim; Endocrinol Metab. 2022;37(4):641-651. Published online August 29, 2022; DOI: https://doi.org/10.3803/EnM.2022.1501

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Background
The prevalence of young-onset diabetes (YOD) has been increasing worldwide. As the incidence of YOD increases, it is necessary to determine the characteristics of YOD and the factors that influence its development and associated complications.
Methods
In this retrospective study, we recruited patients who were diagnosed with type 2 diabetes mellitus between June 2001 and December 2021 at a tertiary hospital. The study population was categorized according to age: YOD (age <40 years), middle-age-onset diabetes (MOD, 40≤ age <65 years), and late-onset diabetes (LOD, age ≥65 years). We examined trends in glycemic control by analyzing fasting glucose levels during the first year in each age group. A Cox proportional-hazards model was used to determine the relative risk of developing complications according to glycemic control trends.
Results
The fasting glucose level at the time of diagnosis was highest in the YOD group (YOD 149±65 mg/dL; MOD 143±54 mg/dL; and LOD 140±55 mg/dL; p=0.009). In the YOD group, glucose levels decreased at 3 months, but increased by 12 months. YOD patients and those with poor glycemic control in the first year were at a higher risk of developing complications, whereas the risk in patients with LOD was not statistically significant.
Conclusion
YOD patients had higher glucose levels at diagnosis, and their glycemic control was poorly maintained. As poor glycemic control can influence the development of complications, especially in young patients, intensive treatment is necessary for patients with YOD.

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Differential Exercise Requirements for Nonalcoholic Fatty Liver Disease Resolution Across Age Groups: A Longitudinal Study of Korean Military Officers
Jaejun Lee, Dong Yeup Lee, Jae Hyeop Jung, Eunkyoung Bae, Jeong A. Yu, Hyun Yang
Journal of Physical Activity and Health.2025; 22(3): 323. CrossRef
Increased risk of incident mental disorders in adults with new-onset type 1 diabetes diagnosed after the age of 19: A nationwide cohort study
Seohyun Kim, Gyuri Kim, So Hyun Cho, Rosa Oh, Ji Yoon Kim, You-Bin Lee, Sang-Man Jin, Kyu Yeon Hur, Jae Hyeon Kim
Diabetes & Metabolism.2024; 50(1): 101505. CrossRef
Association between age at diagnosis of type 2 diabetes and cardiovascular morbidity and mortality risks: A nationwide population-based study
Da Hea Seo, Mina Kim, Young Ju Suh, Yongin Cho, Seong Hee Ahn, Seongbin Hong, So Hun Kim
Diabetes Research and Clinical Practice.2024; 208: 111098. CrossRef
Impact of diabetes distress on glycemic control and diabetic complications in type 2 diabetes mellitus
Hye-Sun Park, Yongin Cho, Da Hea Seo, Seong Hee Ahn, Seongbin Hong, Young Ju Suh, Suk Chon, Jeong-Taek Woo, Sei Hyun Baik, Kwan Woo Lee, So Hun Kim
Scientific Reports.2024;[Epub] CrossRef
Early onset type 2 diabetes mellitus: an update
Myrsini Strati, Melpomeni Moustaki, Theodora Psaltopoulou, Andromachi Vryonidou, Stavroula A. Paschou
Endocrine.2024; 85(3): 965. CrossRef
The Effect of Glycemic Control on Cardiovascular Disease Progression in Adults With Early-Onset Type 2 Diabetes: A Longitudinal Cohort Analysis
Amna Gilani, Khalid Umar, Fatima Gilani, Muhammad Ahmad, Mahnoor S Abbasi, Muhammad Yaseen, Muhammad Zeeshan, Naqeeb Ullah, Aiman Waseem, Fatima Batool, Sundas Safdar
Cureus.2024;[Epub] CrossRef
Complications and Treatment of Early-Onset Type 2 Diabetes
Fahimeh Soheilipour, Naghmeh Abbasi Kasbi, Mahshid Imankhan, Delaram Eskandari
International Journal of Endocrinology and Metabolism.2023;[Epub] CrossRef
Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes (Endocrinol Metab 2022;37:641-51, Han-sang Baek et al.)
Han-sang Baek, Ji-Yeon Park, Jin Yu, Joonyub Lee, Yeoree Yang, Jeonghoon Ha, Seung Hwan Lee, Jae Hyoung Cho, Dong-Jun Lim, Hun-Sung Kim
Endocrinology and Metabolism.2022; 37(6): 945. CrossRef
ISPAD Clinical Practice Consensus Guidelines 2022: Management of the child, adolescent, and young adult with diabetes in limited resource settings
Anju Virmani, Stuart J. Brink, Angela Middlehurst, Fauzia Mohsin, Franco Giraudo, Archana Sarda, Sana Ajmal, Julia E. von Oettingen, Kuben Pillay, Supawadee Likitmaskul, Luis Eduardo Calliari, Maria E. Craig
Pediatric Diabetes.2022; 23(8): 1529. CrossRef
Characteristics of Glycemic Control and Long-Term Complications in Patients with Young-Onset Type 2 Diabetes (Endocrinol Metab 2022;37:641-51, Han-sang Baek et al.)
May Thu Hla Aye, Sajid Adhi Raja, Vui Heng Chong
Endocrinology and Metabolism.2022; 37(6): 943. CrossRef

Diabetes, Obesity and Metabolism
Recent Updates to Clinical Practice Guidelines for Diabetes Mellitus: Jin Yu, Seung-Hwan Lee, Mee Kyoung Kim; Endocrinol Metab. 2022;37(1):26-37. Published online February 28, 2022; DOI: https://doi.org/10.3803/EnM.2022.105

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Guidelines for the management of patients with diabetes have become an important part of clinical practice that improve the quality of care and help establish evidence-based medicine in this field. With rapidly accumulating evidence on various aspects of diabetes care, including landmark clinical trials of treatment agents and newer technologies, timely updates of the guidelines capture the most current state of the field and present a consensus. As a leading academic society, the Korean Diabetes Association publishes practice guidelines biennially and the American Diabetes Association does so annually. In this review, we summarize the key changes suggested in the most recent guidelines. Some of the important updates include treatment algorithms emphasizing comorbid conditions such as atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease in the selection of anti-diabetic agents; wider application of continuous glucose monitoring (CGM), insulin pump technologies and indices derived from CGM such as time in range; more active screening of subjects at high-risk of diabetes; and more detailed individualization in diabetes care. Although there are both similarities and differences among guidelines and some uncertainty remains, these updates provide a good approach for many clinical practitioners who are battling with diabetes.

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Long-term levels of bile acids, fibroblast growth factor-19, and glucagon-like peptide-1 after bariatric surgery
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Asian Journal of Surgery.2025; 48(1): 356. CrossRef
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Optimal Low-Density Lipoprotein Cholesterol Level for Primary Prevention in Koreans with Type 2 Diabetes Mellitus
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The Severity of Diabetes and the Risk of Diabetic Foot Amputation: A National Cohort Study: Jin Yu, Ji-Hyun Kim, Bongseong Kim, Kyungdo Han, Seung Hwan Lee, Mee Kyoung Kim; Received November 28, 2024 Accepted February 4, 2025 Published online April 15, 2025; DOI: https://doi.org/10.3803/EnM.2024.2266 [Epub ahead of print]

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Abstract PDF Supplementary Material PubReader ePub: Background
This study aimed to assess whether markers of diabetes severity could serve as predictors for foot amputation risk among patients with type 2 diabetes mellitus.
Methods
We analyzed data from the nationally representative Korean National Health Insurance System database, tracking 2,544,077 patients with type 2 diabetes mellitus who participated in routine health check-ups between 2009 and 2012, with followup extending through the end of 2018. The parameters used to define the diabetes severity score encompassed diabetes duration, insulin usage, the number of oral glucose-lowering medications, the presence of chronic kidney disease, diabetic retinopathy, and cardiovascular disease. Each factor was assigned one point, yielding a cumulative severity score ranging from 0 to 6.
Results
The risk of diabetic foot amputation was predominantly predicted by insulin therapy, diabetic retinopathy, and a prolonged duration of diabetes. The hazard ratios for foot amputation increased with the severity score as follows: 2.31 (95% confidence interval [CI], 2.15 to 2.47) for a score of 1, 4.73 (95% CI, 4.42 to 5.07) for a score of 2, 8.86 (95% CI, 8.24 to 9.53) for a score of 3, 16.95 (95% CI, 15.60 to 18.4) for a score of 4, 23.98 (95% CI, 21.25 to 27.05) for a score of 5, and 37.87 (95% CI, 28.93 to 49.57) for a score of 6.
Conclusion
Specific markers of advanced diabetes effectively identified patients at an elevated risk for diabetic foot amputation.

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