Citations

Citations to this article as recorded by  

• Trends in prescribing sodium‐glucose cotransporter 2 inhibitors for individuals with type 2 diabetes with and without cardiovascular‐renal disease in South Korea, 2015–2021
  Kyoung Hwa Ha, Soyoung Shin, EunJi Na, Dae Jung Kim
  Journal of Diabetes Investigation.2025; 16(2): 215.     CrossRef
• Effects of Black Cumin Seed Extract on Pancreatic Islet β-Cell Proliferation and Hypoglycemic Activity in Streptozotocin-Induced Diabetic Rats
  Jongkyu Kim, Yoon-Seok Chun, Namkyu Yoon, Byungkwon Kim, Kiin Choi, Sae-Kwang Ku, Namju Lee
  Antioxidants.2025; 14(2): 174.     CrossRef

Citations

Citations to this article as recorded by  

• Computed tomography-based intermuscular adipose tissue analysis and its role in predicting post-kidney transplantation diabetes mellitus
  Yang Feng, Yuechen Shi, Kexin Ma, Jiaming Xiao, Ming Liu, Yuqing Yi, Xiaoyu Zhang, Ke Wang, Zhenming Gao
  Asian Journal of Surgery.2025; 48(1): 221.     CrossRef
• Prognostic impact of post-transplant diabetes mellitus in kidney allograft recipients: a meta-analysis
  Mehmet Kanbay, Dimitrie Siriopol, Mustafa Guldan, Lasin Ozbek, Ahmet U Topcu, Ianis Siriopol, Katherine Tuttle
  Nephrology Dialysis Transplantation.2025; 40(3): 554.     CrossRef
• Effect of post-transplant diabetes mellitus on cardiovascular events and mortality: a single‐center retrospective cohort study
  Uğur Ünlütürk, Tolga Yıldırım, Merve Savaş, Seda Hanife Oğuz, Büşra Fırlatan, Deniz Yüce, Nesrin Damla Karakaplan, Cemile Selimova, Rahmi Yılmaz, Yunus Erdem, Miyase Bayraktar
  Endocrine.2024; 85(2): 695.     CrossRef
• Prevalence of new-onset diabetes mellitus after kidney transplantation: a systematic review and meta-analysis
  Qiufeng Du, Tao Li, Xiaodong Yi, Shuang Song, Jing Kang, Yunlan Jiang
  Acta Diabetologica.2024; 61(7): 809.     CrossRef
• Safety and efficacy of semaglutide in post kidney transplant patients with type 2 diabetes or Post-Transplant diabetes
  Moeber Mohammed Mahzari, Omar Buraykan Alluhayyan, Mahdi Hamad Almutairi, Mohammed Abdullah Bayounis, Yazeed Hasan Alrayani, Amir A. Omair, Awad Saad Alshahrani
  Journal of Clinical & Translational Endocrinology.2024; 36: 100343.     CrossRef

Citations

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• 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
• Association between Age at Diagnosis of Type 2 Diabetes and Subsequent Risk of Dementia and Its Major Subtypes
  Da Hea Seo, Mina Kim, Yongin Cho, Seong Hee Ahn, Seongbin Hong, So Hun Kim
  Journal of Clinical Medicine.2024; 13(15): 4386.     CrossRef
• Assessment of cardiovascular risk with sulfonylurea use in type 2 diabetes mellitus: A retrospective cohort study
  Jari Delbaere, Ewoud Deboever, Bert Vaes, Frank Nobels, Pavlos Mamouris, Geert Goderis
  Primary Care Diabetes.2024; 18(6): 599.     CrossRef
• Systematic review and meta-analysis of teneligliptin for treatment of type 2 diabetes
  R. Pelluri, S. Kongara, V. R. Nagasubramanian, S. Mahadevan, J. Chimakurthy
  Journal of Endocrinological Investigation.2023; 46(5): 855.     CrossRef
• Finding the most cost-effective option from commonly used Dipeptidyl peptidase-4 inhibitors in India: a systematic study
  Harmanjit Singh, Ekta Arora, Seerat Narula, Mandeep Singla, Armaan Otaal, Jatin Sharma
  Expert Review of Endocrinology & Metabolism.2023; 18(4): 347.     CrossRef
• Association Between DPP4 Inhibitor Use and the Incidence of Cirrhosis, ESRD, and Some Cancers in Patients With Diabetes
  Yewon Na, Soo Wan Kim, Ie Byung Park, Soo Jung Choi, Seungyoon Nam, Jaehun Jung, Dae Ho Lee
  The Journal of Clinical Endocrinology & Metabolism.2022; 107(11): 3022.     CrossRef

Citations

Citations to this article as recorded by  

• The clinical features and outcomes of diabetes patients infected with COVID-19: a systematic review and meta-analysis comprising 192,693 patients
  Kai Liu, Shu Liu, Ting-ting Xu, Hong Qiao
  Frontiers in Medicine.2025;[Epub]     CrossRef
• Reasons for Hospitalization Among Australians With Type 1 or Type 2 Diabetes and COVID-19
  Dunya Tomic, Jonathan E. Shaw, Dianna J. Magliano
  Canadian Journal of Diabetes.2024; 48(1): 53.     CrossRef
• Factors Associated with Length of Hospitalization in Patients with Diabetes and Mild COVID-19: Experiences from a Tertiary University Center in Serbia
  Vojislav M. Ciric, Natasa Krsto Rancic, Milica M. Pesic, Danijela B. Radojkovic, Nikola Milenkovic
  Medicina.2024; 60(5): 788.     CrossRef
• Predictors of COVID-19 outcome in type 2 diabetes mellitus: a hospital-based study
  Amira M. Elsayed, Mohamad S. Elsayed, Ahmed E. Mansour, Ahmed W. Mahedy, Eman M. Araby, Maha H. Morsy, Rasha O. Abd Elmoniem
  The Egyptian Journal of Internal Medicine.2024;[Epub]     CrossRef
• Diabetes Mellitus and Pneumococcal Pneumonia
  Catia Cilloniz, Antoni Torres
  Diagnostics.2024; 14(8): 859.     CrossRef
• Genomic insight into COVID-19 severity in MAFLD patients: a single-center prospective cohort study
  Mykhailo Buchynskyi, Valentyn Oksenych, Iryna Kamyshna, Olena Budarna, Iryna Halabitska, Pavlo Petakh, Oleksandr Kamyshnyi
  Frontiers in Genetics.2024;[Epub]     CrossRef
• Risk for Newly Diagnosed Type 2 Diabetes Mellitus after COVID-19 among Korean Adults: A Nationwide Matched Cohort Study
  Jong Han Choi, Kyoung Min Kim, Keeho Song, Gi Hyeon Seo
  Endocrinology and Metabolism.2023; 38(2): 245.     CrossRef
• The Intersection of COVID-19 and Metabolic-Associated Fatty Liver Disease: An Overview of the Current Evidence
  Mykhailo Buchynskyi, Iryna Kamyshna, Valentyn Oksenych, Nataliia Zavidniuk, Aleksandr Kamyshnyi
  Viruses.2023; 15(5): 1072.     CrossRef
• Risk phenotypes of diabetes and association with COVID-19 severity and death: an update of a living systematic review and meta-analysis
  Sabrina Schlesinger, Alexander Lang, Nikoletta Christodoulou, Philipp Linnerz, Kalliopi Pafili, Oliver Kuss, Christian Herder, Manuela Neuenschwander, Janett Barbaresko, Michael Roden
  Diabetologia.2023; 66(8): 1395.     CrossRef
• Diabetes and deaths of COVID-19 patients: Systematic review of meta-analyses
  Aakriti Garg, Mahesh Kumar Posa, Anoop Kumar
  Health Sciences Review.2023; 7: 100099.     CrossRef
• Cardiometabolic Risk Factors and COVID-19 Outcomes in the Asia-Pacific Region: A Systematic Review, Meta-analysis and Meta-regression of 84,011 Patients
  Ru Ying Fong, Annie Lee, Fei Gao, Jonathan Jiunn Liang Yap, Khung Keong Yeo
  Journal of Asian Pacific Society of Cardiology.2023;[Epub]     CrossRef
• Pituitary Diseases and COVID-19 Outcomes in South Korea: A Nationwide Cohort Study
  Jeonghoon Ha, Kyoung Min Kim, Dong-Jun Lim, Keeho Song, Gi Hyeon Seo
  Journal of Clinical Medicine.2023; 12(14): 4799.     CrossRef
• Factors influencing the severity of COVID-19 course for patients with diabetes mellitus in tashkent: a retrospective cohort study
  A. V. Alieva, A. A. Djalilov, F. A. Khaydarova, A. V. Alimov, D. Z. Khalilova, V. A. Talenova, N. U. Alimova, M. D. Aripova, A. S. Sadikova
  Obesity and metabolism.2023; 20(2): 92.     CrossRef
• Genetic Predictors of Comorbid Course of COVID-19 and MAFLD: A Comprehensive Analysis
  Mykhailo Buchynskyi, Valentyn Oksenych, Iryna Kamyshna, Sandor G. Vari, Aleksandr Kamyshnyi
  Viruses.2023; 15(8): 1724.     CrossRef
• Anti-SARS-CoV-2 antibody levels predict outcome in COVID-19 patients with type 2 diabetes: a prospective cohort study
  Sylvia Mink, Christoph H. Saely, Andreas Leiherer, Matthias Frick, Thomas Plattner, Heinz Drexel, Peter Fraunberger
  Scientific Reports.2023;[Epub]     CrossRef
• Two years of SARS-CoV-2 infection (2019–2021): structural biology, vaccination, and current global situation
  Waqar Ahmad, Khadija Shabbiri
  The Egyptian Journal of Internal Medicine.2022;[Epub]     CrossRef
• Baseline haemoglobin A1c and the risk of COVID‐19 hospitalization among patients with diabetes in the INSIGHT Clinical Research Network
  Jea Young Min, Nicholas Williams, Will Simmons, Samprit Banerjee, Fei Wang, Yongkang Zhang, April B. Reese, Alvin I. Mushlin, James H. Flory
  Diabetic Medicine.2022;[Epub]     CrossRef
• The Role of Diabetes and Hyperglycemia on COVID-19 Infection Course—A Narrative Review
  Evangelia Tzeravini, Eleftherios Stratigakos, Chris Siafarikas, Anastasios Tentolouris, Nikolaos Tentolouris
  Frontiers in Clinical Diabetes and Healthcare.2022;[Epub]     CrossRef
• Impact of Type 2 Diabetes Mellitus on the Incidence and Outcomes of COVID-19 Needing Hospital Admission According to Sex: Retrospective Cohort Study Using Hospital Discharge Data in Spain, Year 2020
  Jose M. de Miguel-Yanes, Rodrigo Jimenez-Garcia, Javier de Miguel-Diez, Valentin Hernández-Barrera, David Carabantes-Alarcon, Jose J. Zamorano-Leon, Ricardo Omaña-Palanco, Ana Lopez-de-Andres
  Journal of Clinical Medicine.2022; 11(9): 2654.     CrossRef
• The burden and risks of emerging complications of diabetes mellitus
  Dunya Tomic, Jonathan E. Shaw, Dianna J. Magliano
  Nature Reviews Endocrinology.2022; 18(9): 525.     CrossRef
• A Comprehensive Analysis of Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian Screening Scores for Diabetes Risk Assessment and Prediction
  Norma Latif Fitriyani, Muhammad Syafrudin, Siti Maghfirotul Ulyah, Ganjar Alfian, Syifa Latif Qolbiyani, Muhammad Anshari
  Mathematics.2022; 10(21): 4027.     CrossRef
• New-Onset Diabetes Mellitus Presenting As Diabetic Ketoacidosis in Patients With COVID-19: A Case Series
  Aysha Sarwani, Mahmood Al Saeed, Husain Taha, Rawdha M Al Fardan
  Cureus.2021;[Epub]     CrossRef
• The management of type 2 diabetes before, during and after Covid-19 infection: what is the evidence?
  Leszek Czupryniak, Dror Dicker, Roger Lehmann, Martin Prázný, Guntram Schernthaner
  Cardiovascular Diabetology.2021;[Epub]     CrossRef

The Korean Endocrine Society (KES) published clinical practice guidelines for the treatment of acromegaly in 2011. Since then, the number of acromegaly cases, publications on studies addressing medical treatment of acromegaly, and demands for improvements in insurance coverage have been dramatically increasing. In 2017, the KES Committee of Health Insurance decided to publish a position statement regarding the use of somatostatin analogues in acromegaly. Accordingly, consensus opinions for the position statement were collected after intensive review of the relevant literature and discussions among experts affiliated with the KES, and the Korean Neuroendocrine Study Group. This position statement includes the characteristics, indications, dose, interval (including extended dose interval in case of lanreotide autogel), switching and preoperative use of somatostatin analogues in medical treatment of acromegaly. The recommended approach is based on the expert opinions in case of insufficient clinical evidence, and where discrepancies among the expert opinions were found, the experts voted to determine the recommended approach.

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• Hydrogel-fiber-mesh-based 3D cell cultures: A new method for studying pituitary tumors
  Wooju Jeong, Sungrok Wang, Yumin Kim, Soohyun Lee, Minhu Huang, Jaeil Park, Myung-Han Yoon, Chang-Myung Oh, Cheol Ryong Ku
  Smart Materials in Medicine.2024; 5(2): 281.     CrossRef
• Differential gene expression and pathway analysis in growth hormone-secreting pituitary tumors according to granulation pattern
  Kyungwon Kim, Yeongmin Kim, Se Hoon Kim, Ju Hyung Moon, Eui Hyun Kim, Eun Jig Lee, Chang-Myung Oh, Cheol Ryong Ku
  Frontiers in Oncology.2024;[Epub]     CrossRef
• Agonists, Antagonists and Receptors of Somatostatin: Pathophysiological and Therapeutical Implications in Neoplasias
  Argyrios Periferakis, Georgios Tsigas, Aristodemos-Theodoros Periferakis, Carla Mihaela Tone, Daria Alexandra Hemes, Konstantinos Periferakis, Lamprini Troumpata, Ioana Anca Badarau, Cristian Scheau, Ana Caruntu, Ilinca Savulescu-Fiedler, Constantin Carun
  Current Issues in Molecular Biology.2024; 46(9): 9721.     CrossRef
• Insulin-Like Growth Factor 1 as a Pillar in Acromegaly: From Diagnosis to Long-Term Management
  Mi Kyung Kim
  Endocrinology and Metabolism.2024; 39(5): 693.     CrossRef
• Diagnosis and Management of Acromegaly: A Consensus Statement of the Pituitary Study Group of the Portuguese Society of Endocrinology, Diabetes and Metabolism
  Luís Miguel Cardoso, Pedro Marques, Maria Teresa Pereira, Ana Agapito, Rui Almeida, Sara Amaral, Maria João Bugalho, Maria Begoña Cattoni, Luísa Cortez, Diana Borges Duarte, João Sequeira Duarte, Fernando Fonseca, Leonor Gomes, Inês Manique, Olinda
  Endocrinology Insights.2024; : 1.     CrossRef
• Acromegaly: Pitfalls in diagnosis and treatment
  Mirjana Doknić
  Galenika Medical Journal.2024; 3(12): 28.     CrossRef
• Evaluation and Management of Bone Health in Patients with Thyroid Diseases: A Position Statement of the Korean Thyroid Association
  A Ram Hong, Ho-Cheol Kang
  Endocrinology and Metabolism.2023; 38(2): 175.     CrossRef
• Growth Hormone Excess: Implications and Management
  Suneela Dhaneshwar, Shrishti Shandily, Vatsalya Tiwari
  Endocrine, Metabolic & Immune Disorders - Drug Targets.2023; 23(6): 748.     CrossRef
• Revisiting the usefulness of the short acute octreotide test to predict treatment outcomes in acromegaly
  Montserrat Marques-Pamies, Joan Gil, Elena Valassi, Marta Hernández, Betina Biagetti, Olga Giménez-Palop, Silvia Martínez, Cristina Carrato, Laura Pons, Rocío Villar-Taibo, Marta Araujo-Castro, Concepción Blanco, Inmaculada Simón, Andreu Simó-Servat, Gemm
  Frontiers in Endocrinology.2023;[Epub]     CrossRef
• Evaluation and Management of Bone Health in Patients with Thyroid Diseases: a Position Statement from the Korean Thyroid Association
  A Ram Hong, Hwa Young Ahn, Bu Kyung Kim, Seong Hee Ahn, So Young Park, Min-Hee Kim, Jeongmin Lee, Sun Wook Cho, Ho-Cheol Kang
  International Journal of Thyroidology.2022; 15(1): 1.     CrossRef
• Octreotide in the treatment of acromegaly – the possibilities of high-dose therapy
  I. A. Ilovayskaya
  Meditsinskiy sovet = Medical Council.2022; (10): 148.     CrossRef
• Approach of Acromegaly during Pregnancy
  Alexandru Dan Popescu, Mara Carsote, Ana Valea, Andreea Gabriela Nicola, Ionela Teodora Dascălu, Tiberiu Tircă, Jaqueline Abdul-Razzak, Mihaela Jana Țuculină
  Diagnostics.2022; 12(11): 2669.     CrossRef
• Left to themselves: Time to target chronic pain in childhood rare diseases
  Christine B. Sieberg, Alyssa Lebel, Erin Silliman, Scott Holmes, David Borsook, Igor Elman
  Neuroscience & Biobehavioral Reviews.2021; 126: 276.     CrossRef
• Severe respiratory failure in a patient with COVID-19 and acromegaly: rapid improvement after adding octreotide
  Jacob Luty, LesleAnn Hayward, Melanie Jackson, P Barton Duell
  BMJ Case Reports.2021; 14(8): e243900.     CrossRef
• Precision Therapy in Acromegaly Caused by Pituitary Tumors: How Close Is It to Reality?
  Cheol Ryong Ku, Vladimir Melnikov, Zhaoyun Zhang, Eun Jig Lee
  Endocrinology and Metabolism.2020; 35(2): 206.     CrossRef
• Medical Treatment with Somatostatin Analogues in Acromegaly: Position Statement
  Sang Ouk Chin, Cheol Ryong Ku, Byung Joon Kim, Sung-Woon Kim, Kyeong Hye Park, Kee Ho Song, Seungjoon Oh, Hyun Koo Yoon, Eun Jig Lee, Jung Min Lee, Jung Soo Lim, Jung Hee Kim, Kwang Joon Kim, Heung Yong Jin, Dae Jung Kim, Kyung Ae Lee, Seong-Su Moon, Dong
  The Korean Journal of Medicine.2019; 94(6): 485.     CrossRef

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• Comparison of growth response and adverse reaction according to growth hormone dosing strategy for children with short stature: LG Growth Study
  Kyungchul Song, Mo Kyung Jung, Jun Suk Oh, Su Jin Kim, Han Saem Choi, Myeongseob Lee, Junghwan Suh, Ahreum Kwon, Hyun Wook Chae, Ho-Seong Kim
  Growth Hormone & IGF Research.2023; 69-70: 101531.     CrossRef
• Systematic estimation of BMI
  Meng-Jie Shan, Yang-Fan Zou, Peng Guo, Jia-Xu Weng, Qing-Qing Wang, Ya-Lun Dai, Hui-Bin Liu, Yuan-Meng Zhang, Guan-Yin Jiang, Qi Xie, Ling-Bing Meng
  Medicine.2019; 98(21): e15810.     CrossRef

Over the past several decades, the prevalence of obesity has increased dramatically worldwide and is increasing not only in developed countries, but also in developing countries. This increase may lead to an increase in the incidence of chronic diseases throughout the lifespan. In Korean children and adolescents, the prevalence of obesity increased from 6.8% in 1998 to 10.0% in 2013. Obesity is a state that more commonly influences children and adolescents of lower socioeconomic status (SES) than those with a higher SES. However, the prevalence of metabolic syndrome in a nationally representative sample of Korean adolescents decreased from 1998 to 2012. According to the Diabetes Fact Sheet of the Korean Diabetes Association, the prevalence of type 2 diabetes among children aged 18 years or younger was 153.5 per 100,000 in 2006 and 205.0 per 100,000 in 2013. Obesity is a complex disease influenced by many interacting factors, such as adipocytokines, lipopolysaccharide-binding protein, adenovirus 36 infection, birth weight, lifestyle, and endocrine-disrupting chemicals. Obesity in youth can adversely impact practically every organ system and lead to serious consequences, such as metabolic, gastrointestinal, pulmonary, cardiovascular, and psychosocial complications. Therefore, coordinated efforts by governments, organizations, communities, and individuals are needed to prevent and treat childhood obesity. In particular, a long-term policy to improve the social environment will also be necessary.

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• Global trends in importance of 24-hour movement behaviors to pediatric health: implications for South Korea
  Eun-Young Lee, Reyana Jayawardena, Seiyeong Park, Justin Y Jeon, Yeon-Soo Kim, Mark S. Tremblay
  Clinical and Experimental Pediatrics.2025; 68(1): 16.     CrossRef
• Factorial validation of the children’s eating behavior questionnaire and the association between the eating behaviors assessed and BMI Z score in Chinese preschoolers aged 2–5 years
  Jinsong Mou, Haishan Zhou, Shiya Huang, Zhangui Feng
  Journal of Health, Population and Nutrition.2024;[Epub]     CrossRef
• Sulfur Metabolism of the Gut Microbiome and Colorectal Cancer: The Threat to the Younger Generation
  Ji-Yeon Moon, Bong-Hyeon Kye, Seung-Hyun Ko, Ri Na Yoo
  Nutrients.2023; 15(8): 1966.     CrossRef
• Association between Obesity and Cardiovascular Disease Risk Factors in Different Age Groups of Adolescents: An Analysis of Data from the Korean National Health and Nutritional Examination Survey
  Joowon Lee, Seul Gi Cha, Jue Seong Lee, Susan Taejung Kim, Young Hwan Song
  Children.2023; 10(5): 827.     CrossRef
• The economic burden of adolescent internet addiction: A Korean health cost case study
  Robert W. Mead, Edward Nall
  The Social Science Journal.2023; : 1.     CrossRef
• Trends in socioeconomic inequalities in obesity among Korean adolescents: the Korea Youth Risk Behavior Web-based Survey (KYRBS) 2006 to 2020
  Eunji Kim, Ga Bin Lee, Dong Keon Yon, Hyeon Chang Kim
  Epidemiology and Health.2023; 45: e2023033.     CrossRef
• Protective Effects of Melatonin in High-Fat Diet-Induced Hepatic Steatosis via Decreased Intestinal Lipid Absorption and Hepatic Cholesterol Synthesis
  Hyungjune Ku, Yeonji Kim, Alvin Lyle Kim, Garam Lee, Youngsik Choi, Bukyung Kim
  Endocrinology and Metabolism.2023; 38(5): 557.     CrossRef
• Time Trends in the Prevalence of Atopic Dermatitis in Korean Children According to Age
  Ji Young Lee, Jihyun Kim, Kangmo Ahn
  Allergy, Asthma & Immunology Research.2022; 14(1): 123.     CrossRef
• Additive Effects of Exercise or Nutrition Intervention in a 24-Month Multidisciplinary Treatment with a Booster Intervention for Children and Adolescents with Overweight or Obesity: The ICAAN Study
  Sarah Woo, Young-Su Ju, Young-Gyun Seo, Yoon-Myung Kim, Hyunjung Lim, Kyung-Hee Park
  Nutrients.2022; 14(2): 387.     CrossRef
• Effectiveness of obesity interventions among South Korean children and adolescents and importance of the type of intervention component: a meta-analysis
  Siyoung Choe, Jaesin Sa, Jean-Philippe Chaput, Deokjin Kim
  Clinical and Experimental Pediatrics.2022; 65(2): 98.     CrossRef
• Effects of a 12-Week Diet versus Diet plus Aerobic and Resistance Exercise Program on Acylated and Desacylated Ghrelin, and Ghrelin O-Acyltransferase in Adolescent Girls with Obesity
  Hyun Jun Kim, Young Jin Tak, Sang Yeoup Lee, Jeong Pyo Seo
  International Journal of Environmental Research and Public Health.2022; 19(3): 1480.     CrossRef
• Trends and Risk Factors of Metabolic Syndrome among Korean Adolescents, 2007 to 2018 (Diabetes Metab J 2021;45:880-9)
  Dae Jung Kim
  Diabetes & Metabolism Journal.2022; 46(2): 349.     CrossRef
• Adenovirus 36 infection and daycare starting age are associated with adiposity in children and adolescents
  Ana Carolina Lobor Cancelier, Nikhil V. Dhurandhar, Swetha Peddibhotla, Richard L. Atkinson, Helena C.G. Silva, Daisson J. Trevisol, Fabiana Schuelter-Trevisol
  Jornal de Pediatria.2021; 97(4): 420.     CrossRef
• The association of obstructive sleep apnea with dyslipidemia in Korean children and adolescents: a single-center, cross-sectional study
  Eun Kyeong Kang, Min Jeong Jang, Ki Duk Kim, Young Min Ahn
  Journal of Clinical Sleep Medicine.2021; 17(8): 1599.     CrossRef
• Trajectories in glycated hemoglobin and body mass index in children and adolescents with diabetes using the common data model
  Yun Jeong Lee, Sooyoung Yoo, Soyoung Yi, Seok Kim, Chunggak Lee, Jihoon Cho, Soyeon Ahn, Sunkyu Choi, Hee Hwang, Young Ah Lee, Choong Ho Shin, Hyung-Jin Yoon, Kwangsoo Kim, Eunhye Song, Jin Ho Choi, Han Wook Yoo, Young-Hak Kim, Ji Seon Oh, Eun-Ae Kang, Ga
  Scientific Reports.2021;[Epub]     CrossRef
• Comparison of eating habits and inappropriate weight control efforts of secondary school students enrolled in a weight control program
  EunKyo Kang, Soojeong Kim, Young Ho Yun
  Nutrition Research and Practice.2021; 15(5): 628.     CrossRef
• Association between childhood obesity and familial salt intake: analysis of data from Korean National Health and Nutrition Examination Survey, 2014–2017
  Byung Min Yoo, Mijin Kim, Min Jae Kang
  Endocrine Journal.2021; 68(9): 1127.     CrossRef
• Regional Adolescent Obesity and Overweight Status in Korea from 2018–2019: Comparison between Two Data Sources
  Dong-Hee Ryu, Su-Jin Lee
  Healthcare.2021; 9(12): 1751.     CrossRef
• Family Factors and Obesity in Relation to Mental Health Among Korean Children and Adolescents
  Hye-Mi Noh, Jane Park, Eun-Ju Sung, Young Soo Ju, Hye-Ja Lee, Yoon-Kyoung Jeong, Kyung Hee Park
  Journal of Child and Family Studies.2020; 29(5): 1284.     CrossRef
• Distribution of Tri-Ponderal Mass Index and its Relation to Body Mass Index in Children and Adolescents Aged 10 to 20 Years
  Hong Kyu Park, Young Suk Shim
  The Journal of Clinical Endocrinology & Metabolism.2020; 105(3): e826.     CrossRef
• The change in prevalence of suspected non-alcoholic fatty liver disease in Korean adolescents from 2001 to 2017
  Seung Ha Park, Yong Eun Park, Jin Lee, Joon Hyuk Choi, Nae Yun Heo, Jongha Park, Tae Oh Kim, Jun Seong Hwang, Eunju Kim, Eun Hye Oh, Hang Jea Jang, Ha Young Park, Hyun Kuk Kim
  Paediatrics and International Child Health.2020; 40(3): 166.     CrossRef
• Effect of inactivated Bifidobacterium longum intake on obese diabetes model mice (TSOD)
  Mahmoud Ben Othman, Kazuichi Sakamoto
  Food Research International.2020; 129: 108792.     CrossRef
• Self and parent-proxy rated health-related quality of life (HRQoL) in youth with obesity: are parents good surrogates?
  Delicia Shu Qin Ooi, Kah Yin Loke, Cindy Wei Li Ho, Yvonne Yijuan Lim, Veronica Tay, Vijaya Karuppiah, Andrew Anjian Sng, Lester Yousheng Lai, Yung Seng Lee, Konstadina Griva
  Quality of Life Research.2020; 29(8): 2171.     CrossRef
• Chinese men living in urban areas of Shijiazhuang, Hebei at higher risk of overweight or obesity
  De-Xian Kong, Xiao-feng Su, Jing-wei Zhao, Lian Chen, Ling-bing Meng, Zhen-xi Zhang, Sen Yang, Lei Zhang, Ya-bin Liu
  Journal of International Medical Research.2020;[Epub]     CrossRef
• Association between Parent’s Metabolic Syndrome and 12- to18-Year-Old Offspring’s Overweight: Results from the Korea National Health and Nutrition Examination Survey (K-NHANES) 2009–2016
  Na Yeong Lee, Kyungdo Han, Yoonji Lee, Seulki Kim, Seonhwa Lee, Yujung Choi, Moon bae Ahn, Shin Hee Kim, Won Kyoung Cho, Kyoung Soon Cho, Min Ho Jung, Yong-Gyu Park, Byung-Kyu Suh, Silvia Monticone
  International Journal of Endocrinology.2020; 2020: 1.     CrossRef
• Incidence and Prevalence of Type 1 Diabetes Mellitus among Korean Children and Adolescents between 2007 and 2017: An Epidemiologic Study Based on a National Database
  Hyun Wook Chae, Gi Hyeon Seo, Kyungchul Song, Han Saem Choi, Junghwan Suh, Ahreum Kwon, Sangmi Ha, Ho-Seong Kim
  Diabetes & Metabolism Journal.2020; 44(6): 866.     CrossRef
• Quick assessment with controlled attenuation parameter for hepatic steatosis in children based on MRI-PDFF as the gold standard
  Jaeseung Shin, Myung-Joon Kim, Hyun Joo Shin, Haesung Yoon, Seung Kim, Hong Koh, Mi-Jung Lee
  BMC Pediatrics.2019;[Epub]     CrossRef
• Changing patterns of multiple sclerosis in Korea: Toward a more baseline MRI lesions and intrathecal humoral immune responses
  Hyun-June Shin, Jae-Won Hyun, Su-Hyun Kim, Min Su Park, Eun Hee Sohn, Seol-Hee Baek, Byung-Jo Kim, Kyomin Choi, Jeeyoung Oh, Joong-Yang Cho, Ohyun Kwon, Woojun Kim, Jee-Eun Kim, Ju-Hong Min, Byoung Joon Kim, Sun-Young Oh, Jong Seok Bae, Kee Hong Park, Jun
  Multiple Sclerosis and Related Disorders.2019; 35: 209.     CrossRef
• Serum osteocalcin levels in overweight children
  Seok Bin Oh, Won Young Lee, Hyo-Kyoung Nam, Young-Jun Rhie, Kee-Hyoung Lee
  Annals of Pediatric Endocrinology & Metabolism.2019; 24(2): 104.     CrossRef
• Associations between lipid profiles of adolescents and their mothers based on a nationwide health and nutrition survey in South Korea
  Ji Hyung Nam, Jaeyong Shin, Sung-In Jang, Ji Hyun Kim, Kyu-Tae Han, Jun Kyu Lee, Yun Jeong Lim, Eun-Cheol Park
  BMJ Open.2019; 9(3): e024731.     CrossRef
• Association of Weight Control Behaviors with Body Mass Index in Korean Adolescents: A Quantile Regression Approach
  Sun-Mi Chae, Mi Ja Kim, Chang Gi Park, Ji-Young Yeo, Ji-Hye Hwang, Insook Kwon, Soo-Yeon Han
  Journal of Pediatric Nursing.2018; 40: e18.     CrossRef
• Associations between birth weight, obesity, fat mass and lean mass in Korean adolescents: the Fifth Korea National Health and Nutrition Examination Survey
  Myunggee Kang, Jung Eun Yoo, Kyuwoong Kim, Seulggie Choi, Sang Min Park
  BMJ Open.2018; 8(2): e018039.     CrossRef
• Thyroid function in obese Korean children and adolescents: Korea National Health and Nutrition Examination Survey 2013–2015
  Young Min An, Soon Jeong Moon, Soon Ki Kim, Young Ju Suh, Ji Eun Lee
  Annals of Pediatric Endocrinology & Metabolism.2018; 23(3): 141.     CrossRef
• Validation of Dietary Reference Intakes for predicting energy requirements in elementary school-age children
  Eun-Kyung Kim, Didace Ndahimana, Kazuko Ishikawa-Takata, Sangjik Lee, Hyungryul Kim, Kiwon Lim, In-Sook Lee, Shigeho Tanaka, Ye-Jin Kim, Yeon-Jung Choi, Mun-Jeong Ju, Jonghoon Park
  Nutrition Research and Practice.2018; 12(4): 336.     CrossRef
• Family-based treatment for obesity in tweens: a three-year longitudinal follow-up study
  Hongsik J. Cheon, Jay R. Fraser, Trang Kieu Nguyen
  International Journal of Advertising.2018; 37(4): 548.     CrossRef
• Anti-obesity effects of Clausena excavata in high-fat diet-induced obese mice
  Young-Rak Cho, Jung A. Lee, Yoon Yeon Kim, Jae-Shin Kang, Jae-Ho Lee, Eun-Kyung Ahn
  Biomedicine & Pharmacotherapy.2018; 99: 253.     CrossRef
• Hypertension Risk of Obesity and Abdominal Obesity in High School Students
  Yu jin Kwak, Ji Hyen Lee, Young Mi Hong, Hae Soon Kim
  The Ewha Medical Journal.2018; 41(1): 13.     CrossRef
• Articles inEndocrinology and Metabolismin 2016
  Won-Young Lee
  Endocrinology and Metabolism.2017; 32(1): 62.     CrossRef
• Management of childhood obesity
  Shin-Hye Kim, Mi-Jung Park
  Journal of the Korean Medical Association.2017; 60(3): 233.     CrossRef
• Prevalences and Management of Diabetes and Pre-diabetes among Korean Teenagers and Young Adults: Results from the Korea National Health and Nutrition Examination Survey 2005–2014
  Eun-Hee Cho, Dayeon Shin, Keun-Hyok Cho, Junguk Hur
  Journal of Korean Medical Science.2017; 32(12): 1984.     CrossRef
• Prevalence and risk factors for type 2 diabetes mellitus with Prader–Willi syndrome: a single center experience
  Aram Yang, Jinsup Kim, Sung Yoon Cho, Dong-Kyu Jin
  Orphanet Journal of Rare Diseases.2017;[Epub]     CrossRef

Citations

Citations to this article as recorded by  

• Changing landscape of diabetes in Asia – What are the unmet needs?
  Andrea OY Luk
  Journal of Diabetes Investigation.2024; 15(4): 402.     CrossRef
• High level of gamma-glutamyltransferase is a possible risk factor for psoriasis: A nationwide population-based cohort study
  Jongwook Oh, Kyungdo Han, Jee Yun Doh, Heon Yung Gee, Ji Hyun Lee
  Indian Journal of Dermatology, Venereology and Leprology.2024; 0: 1.     CrossRef
• Risks of colorectal cancer and biliary cancer according to accompanied primary sclerosing cholangitis in Korean patients with ulcerative colitis: a nationwide population-based study
  Eun Hye Oh, Ye-Jee Kim, Minju Kim, Seung Ha Park, Tae Oh Kim, Sang Hyoung Park
  Intestinal Research.2023; 21(2): 252.     CrossRef
• The role of nutritional status in the relationship between diabetes and health-related quality of life
  Sohyun Park, Sukyoung Jung, Hyunsook Yoon
  Nutrition Research and Practice.2022; 16(4): 505.     CrossRef
• Lifetime risk of developing diabetes in Chinese people with normoglycemia or prediabetes: A modeling study
  Xinge Zhang, Hongjiang Wu, Baoqi Fan, Mai Shi, Eric S. H. Lau, Aimin Yang, Elaine Chow, Alice P. S. Kong, Juliana C. N. Chan, Ronald C. W. Ma, Andrea O. Y. Luk, Claudia Langenberg
  PLOS Medicine.2022; 19(7): e1004045.     CrossRef
• Rising Incidence of Diabetes in Young Adults in South Korea: A National Cohort Study
  Hyun Ho Choi, Giwoong Choi, Hojun Yoon, Kyoung Hwa Ha, Dae Jung Kim
  Diabetes & Metabolism Journal.2022; 46(5): 803.     CrossRef
• Association between Age-Related Macular Degeneration and the Risk of Diabetes Mellitus: A Nationwide Cohort Study
  Wonyoung Jung, Je Moon Yoon, Kyungdo Han, Bongseong Kim, Sungsoon Hwang, Dong Hui Lim, Dong Wook Shin
  Biomedicines.2022; 10(10): 2435.     CrossRef
• Relationship between Dermatitis and Joint Replacement
  Joon Woo Jung, Minkook Son, Soo Hyun Jeong, Kwang Joong Kim, Kwang Ho Kim, Eun Joo Park
  Indian Journal of Dermatology.2022; 67(3): 312.     CrossRef
• Prediction of type 2 diabetes using genome-wide polygenic risk score and metabolic profiles: A machine learning analysis of population-based 10-year prospective cohort study
  Seok-Ju Hahn, Suhyeon Kim, Young Sik Choi, Junghye Lee, Jihun Kang
  eBioMedicine.2022; 86: 104383.     CrossRef
• A Novel User Utility Score for Diabetes Management Using Tailored Mobile Coaching: Secondary Analysis of a Randomized Controlled Trial
  Min-Kyung Lee, Da Young Lee, Hong-Yup Ahn, Cheol-Young Park
  JMIR mHealth and uHealth.2021; 9(2): e17573.     CrossRef
• Estimating the disease burden of Korean type 2 diabetes mellitus patients considering its complications
  Juyoung Kim, Seok-Jun Yoon, Min-Woo Jo, Brecht Devleesschauwer
  PLOS ONE.2021; 16(2): e0246635.     CrossRef
• Positive association between actinic keratosis and internal malignancies: a nationwide population-based cohort study
  Young Bok Lee, Ji Hyun Lee, Yeong Ho Kim, Ji Min Seo, Dong Soo Yu, Yong Gyu Park, Kyung Do Han
  Scientific Reports.2021;[Epub]     CrossRef
• Herpes Zoster and Subsequent Cancer Risk: A Nationwide Population-Based Cohort Study in Korea
  Miri Kim, Kyungdo Han, Seung Ah Yoo, Ji Hyun Lee
  Dermatology.2021; 237(1): 73.     CrossRef
• Identification of herpes zoster high‐risk group using Charlson comorbidity index: A nationwide retrospective cohort study
  Soo Ick Cho, Dong Hun Lee, Young Min Park
  The Journal of Dermatology.2020; 47(1): 47.     CrossRef
• Increased risk of Alzheimer’s disease in patients with psoriasis: a nationwide population-based cohort study
  Miri Kim, Hyo Eun Park, Si-Hyung Lee, Kyungdo Han, Ji Hyun Lee
  Scientific Reports.2020;[Epub]     CrossRef
• The incidence rates and risk factors of Parkinson disease in patients with psoriasis: A nationwide population-based cohort study
  Ji Hyun Lee, Kyungdo Han, Heon Yung Gee
  Journal of the American Academy of Dermatology.2020; 83(6): 1688.     CrossRef
• Site-specific cancer risk in patients with type 2 diabetes: a nationwide population-based cohort study in Korea
  Suk Kyeong Kim, Ju-Young Jang, Dong-Lim Kim, Young A Rhyu, Suh Eun Lee, Seung-Hyun Ko, Kyungdo Han, Kee-Ho Song
  The Korean Journal of Internal Medicine.2020; 35(3): 641.     CrossRef
• Secular trends in incidence of type 1 and type 2 diabetes in Hong Kong: A retrospective cohort study
  Andrea O. Y. Luk, Calvin Ke, Eric S. H. Lau, Hongjiang Wu, William Goggins, Ronald C. W. Ma, Elaine Chow, Alice P. S. Kong, Wing-Yee So, Juliana C. N. Chan, Sanjay Basu
  PLOS Medicine.2020; 17(2): e1003052.     CrossRef
• Long‐term risk of congestive heart failure in younger breast cancer survivors: A nationwide study by the SMARTSHIP group
  Jihyoun Lee, Ho Hur, Jong Won Lee, Hyun Jo Youn, Kyungdo Han, Nam Won Kim, So‐Youn Jung, Zisun Kim, Ku Sang Kim, Min Hyuk Lee, Se‐Hwan Han, Sung Hoo Jung, Il Yong Chung
  Cancer.2020; 126(1): 181.     CrossRef
• The Lancet Commission on diabetes: using data to transform diabetes care and patient lives
  Juliana C N Chan, Lee-Ling Lim, Nicholas J Wareham, Jonathan E Shaw, Trevor J Orchard, Ping Zhang, Eric S H Lau, Björn Eliasson, Alice P S Kong, Majid Ezzati, Carlos A Aguilar-Salinas, Margaret McGill, Naomi S Levitt, Guang Ning, Wing-Yee So, Jean Adams,
  The Lancet.2020; 396(10267): 2019.     CrossRef
• Prognosis of Patients with Colorectal Cancer with Diabetes According to Medication Adherence: A Population-Based Cohort Study
  Sunho Choe, Joonki Lee, Ji Won Park, Seung-Yong Jeong, Young Min Cho, Byung-Joo Park, Aesun Shin
  Cancer Epidemiology, Biomarkers & Prevention.2020; 29(6): 1120.     CrossRef
• Trends in Hyperglycemic Crisis Hospitalizations and in- and out-of-Hospital Mortality in the Last Decade Based on Korean National Health Insurance Claims Data
  Ji Hong You, Sun Ok Song, Se Hee Park, Kyoung Hye Park, Joo Young Nam, Dong Wook Kim, Hyun Min Kim, Dong-Jun Kim, Yong-ho Lee, Byung-Wan Lee
  Endocrinology and Metabolism.2019; 34(3): 275.     CrossRef
• Response: Trends in Hyperglycemic Crisis Hospitalizations and in- and out-of-Hospital Mortality in the Last Decade Based on Korean National Health Insurance Claims Data (Endocrinol Metab 2019;34:275–81, Ji Hong You et al.)
  Ji Hong You, Sun Ok Song
  Endocrinology and Metabolism.2019; 34(4): 424.     CrossRef
• A simple screening score to predict diabetes in cancer patients
  Ji-Su Kim, Sun-Hye Ko, Myong Ki Baeg, Kyung-Do Han
  Medicine.2019; 98(51): e18354.     CrossRef
• Cancer risk in 892 089 patients with psoriasis in Korea: A nationwide population‐based cohort study
  Ji Hyun Lee, Hyo Jung Kim, Kyung Do Han, Ha‐Na Kim, Young Min Park, Jun Young Lee, Yong‐Gyu Park, Young Bok Lee
  The Journal of Dermatology.2019; 46(2): 95.     CrossRef
• Effects of sarpogrelate on microvascular complications with type 2 diabetes
  Hyunju Yoo, Inwhee Park, Dae Jung Kim, Sukhyang Lee
  International Journal of Clinical Pharmacy.2019; 41(2): 563.     CrossRef
• Presence of Metabolic Syndrome Components Is Associated with Tooth Loss in Middle-Aged Adults
  Min-Jeong Cho, Youn-Hee Choi, Hyeon Chang Kim, Jee-Seon Shim, Atsuo Amano, Ji-Young Kim, Keun-Bae Song
  Yonsei Medical Journal.2019; 60(6): 554.     CrossRef
• Ten-Year Mortality Trends for Adults with and without Diabetes Mellitus in South Korea, 2003 to 2013
  Kyeong Jin Kim, Tae Yeon Kwon, Sungwook Yu, Ji A Seo, Nan Hee Kim, Kyung Mook Choi, Sei Hyun Baik, Dong Seop Choi, Sin Gon Kim, Yousung Park, Nam Hoon Kim
  Diabetes & Metabolism Journal.2018; 42(5): 394.     CrossRef
• Cancer risk by the subtype of alopecia
  Ji Hyun Lee, Yumee Song, Kyung Do Han, Young Min Park, Jun Young Lee, Yong-Gyu Park, Young Bok Lee
  Scientific Reports.2018;[Epub]     CrossRef
• Nationwide Analysis of Treatment Patterns for Korean Breast Cancer Survivors Using National Health Insurance Service Data
  Il Yong Chung, Jihyoun Lee, Suyeon Park, Jong Won Lee, Hyun Jo Youn, Jung Hwa Hong, Ho Hur
  Journal of Korean Medical Science.2018;[Epub]     CrossRef
• Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) cohort: study protocol and results of the first 3 years of enrollment
  Jee-Seon Shim, Bo Mi Song, Jung Hyun Lee, Seung Won Lee, Ji Hye Park, Dong Phil Choi, Myung Ha Lee, Kyoung Hwa Ha, Dae Jung Kim, Sungha Park, Won-Woo Lee, Hyeon Chang Kim
  Epidemiology and Health.2017; 39: e2017016.     CrossRef
• Effectiveness of Vildagliptin in Clinical Practice: Pooled Analysis of Three Korean Observational Studies (the VICTORY Study)
  Sunghwan Suh, Sun Ok Song, Jae Hyeon Kim, Hyungjin Cho, Woo Je Lee, Byung-Wan Lee
  Journal of Diabetes Research.2017; 2017: 1.     CrossRef
• Articles inEndocrinology and Metabolismin 2016
  Won-Young Lee
  Endocrinology and Metabolism.2017; 32(1): 62.     CrossRef
• Effects of Lobeglitazone, a Novel Thiazolidinedione, on Bone Mineral Density in Patients with Type 2 Diabetes Mellitus over 52 Weeks
  Soo Lim, Kyoung Min Kim, Sin Gon Kim, Doo Man Kim, Jeong-Taek Woo, Choon Hee Chung, Kyung Soo Ko, Jeong Hyun Park, Yongsoo Park, Sang Jin Kim, Hak Chul Jang, Dong Seop Choi
  Diabetes & Metabolism Journal.2017; 41(5): 377.     CrossRef
• Current status of managing diabetes mellitus in Korea
  Kyoung Hwa Ha, Dae Jung Kim
  The Korean Journal of Internal Medicine.2016; 31(5): 845.     CrossRef

A clinical prediction model can be applied to several challenging clinical scenarios: screening high-risk individuals for asymptomatic disease, predicting future events such as disease or death, and assisting medical decision-making and health education. Despite the impact of clinical prediction models on practice, prediction modeling is a complex process requiring careful statistical analyses and sound clinical judgement. Although there is no definite consensus on the best methodology for model development and validation, a few recommendations and checklists have been proposed. In this review, we summarize five steps for developing and validating a clinical prediction model: preparation for establishing clinical prediction models; dataset selection; handling variables; model generation; and model evaluation and validation. We also review several studies that detail methods for developing clinical prediction models with comparable examples from real practice. After model development and vigorous validation in relevant settings, possibly with evaluation of utility/usability and fine-tuning, good models can be ready for the use in practice. We anticipate that this framework will revitalize the use of predictive or prognostic research in endocrinology, leading to active applications in real clinical practice.

Citations

Citations to this article as recorded by  

• Exploring the role of health-related quality of life measures in predictive modelling for oncology: a systematic review
  T. G. W. van der Heijden, K. M. de Ligt, N. J. Hubel, S. van der Mierden, B. Holzner, L. V. van de Poll-Franse, B. H. de Rooij
  Quality of Life Research.2025; 34(2): 305.     CrossRef
• Development and internal validation of a nomogram for predicting recurrent respiratory tract infections in children
  Fei Xia, Xi Zhou, Yan Xiong, Chenghui Yin, Minhua Wang, Ling Li
  Respiratory Medicine.2025; 238: 107961.     CrossRef
• Systematic review of 99 extremity bone malignancy survival prediction models
  Cheng-Yo Lai, Hung-Kuan Yen, Hao-Chen Lin, Olivier Quinten Groot, Wei-Hsin Lin, Hao-Ping Hsu
  Journal of Orthopaedics and Traumatology.2025;[Epub]     CrossRef
• Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review
  Yihun Mulugeta Alemu, Sisay Mulugeta Alemu, Nasser Bagheri, Kinley Wangdi, Dan Chateau
  Open Heart.2025; 12(1): e003147.     CrossRef
• The Limitation of HLA Diversity as a Risk Factor for Pediatric-Onset Autoimmune Rheumatic Disease
  Ioannis Kalampokis, Craig S. Wong, Jihyun Ma, Lynette M. Smith, Barbara J. Masten, Devon Chabot-Richards, David S. Pisetsky
  Journal of Clinical Medicine.2025; 14(3): 916.     CrossRef
• Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models
  Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar
  BMC Medical Informatics and Decision Making.2025;[Epub]     CrossRef
• Models to predict length of stay in the emergency department: a systematic literature review and appraisal
  Raheleh Mahboub Farimani, Hesam Karim, Alireza Atashi, Fariba Tohidinezhad, Kambiz Bahaadini, Ameen Abu-Hanna, Saeid Eslami
  BMC Emergency Medicine.2024;[Epub]     CrossRef
• The MISOPRED score: Development and validation of a clinical scoring system to predict the effectiveness of Misoprostol treatment for early pregnancy loss
  Tomer Bar-Noy, Ofer Limonad, Erika Gandelsman, Alon Shrim, Hila Sharabi, Raphy Zarecki, Mordechai Hallak, Ilan Bruchim, Federico Ferrari
  PLOS ONE.2024; 19(5): e0303607.     CrossRef
• The Brilliance, Attitude, Leadership and Materials (BALM) framework of clinical excellence: an adoptable model for sub-Saharan Africa
  Taoreed Azeez
  Academic Medicine & Surgery.2024;[Epub]     CrossRef
• Risk prediction models for diabetic nephropathy among type 2 diabetes patients in China: a systematic review and meta-analysis
  Wenbin Xu, Yanfei Zhou, Qian Jiang, Yiqian Fang, Qian Yang
  Frontiers in Endocrinology.2024;[Epub]     CrossRef
• Risk Assessment Tool in Predicting the Therapeutic Outcomes of Antiseizure Medication in Adults with Epilepsy
  Rose Aniza Rusli, Mohd Makmor Bakry, Noraida Mohamed Shah, Xin Ling Loo, Stefanie Kar Yan Hung
  Therapeutics and Clinical Risk Management.2024; Volume 20: 529.     CrossRef
• Development of an IVF prediction model for donor oocytes: a retrospective analysis of 10 877 embryo transfers
  Oisin Fitzgerald, Jade Newman, Luk Rombauts, Alex Polyakov, Georgina M Chambers
  Human Reproduction.2024; 39(10): 2274.     CrossRef
• Ambulation recovery prediction after hip fracture surgery using the Hip Fracture Short-Term Ambulation Prediction tool
  Nath Adulkasem, Pojchong Chotiyarnwong, Ekasame Vanitcharoenkul, Aasis Unnanuntana
  Journal of Rehabilitation Medicine.2024; 56: jrm40780.     CrossRef
• Separating Risk Prediction: Myocardial Infarction vs. Ischemic Stroke in 6.2M Screenings
  Wonyoung Jung, Sang Hyun Park, Kyungdo Han, Su-Min Jeong, In Young Cho, Kihyung Kim, Yerim Kim, Sung Eun Kim, Dong Wook Shin
  Healthcare.2024; 12(20): 2080.     CrossRef
• Predicting mid- and late-life dementia risk in primary care: A prognostic study from a national health screening cohort
  Wonyoung Jung, Sang Hyun Park, SangYun Kim, Jinkook Lee, Junhee Park, Su-Min Jeong, Seung-Yeon Lee, Kyungdo Han, Dong Wook Shin
  Psychiatry Research.2024; 342: 116237.     CrossRef
• A new prediction diagnosis model of incomplete Kawasaki disease based on data mining with big data
  Zhen Yang, Bo Pan, Jia Liu, Haolin Wang, Jie Tian
  Pediatric Discovery.2024;[Epub]     CrossRef
• Development and Validation of a Prognostic Model to Predict Hearing Recovery for Patients With Chronic Otitis Media
  Fengyang Xie, Xiaoyue Zhen, Haiyuan Zhu, Yan Kou, Changle Li, Ling Guo, Li Shi, Jie Han, Xuanchen Zhou
  Ear, Nose & Throat Journal.2023; 102(7): NP327.     CrossRef
• The reporting of prognostic prediction models for obstetric care was poor: a cross-sectional survey of 10-year publications
  Chunrong Liu, Yana Qi, Xinghui Liu, Meng Chen, Yiquan Xiong, Shiyao Huang, Kang Zou, Jing Tan, Xin Sun
  BMC Medical Research Methodology.2023;[Epub]     CrossRef
• Severity of Illness Scores and Biomarkers for Prognosis of Patients with Coronavirus Disease 2019
  Rodrigo Cavallazzi, James Bradley, Thomas Chandler, Stephen Furmanek, Julio A. Ramirez
  Seminars in Respiratory and Critical Care Medicine.2023; 44(01): 075.     CrossRef
• Prognostic risk factor of major salivary gland carcinomas and survival prediction model based on random survival forests
  Yufan Chen, Guoli Li, Wenmei Jiang, Rong Cheng Nie, Honghao Deng, Yingle Chen, Hao Li, Yanfeng Chen
  Cancer Medicine.2023; 12(9): 10899.     CrossRef
• Semantic Visualization in Functional Recovery Prediction of Intravenous Thrombolysis following Acute Ischemic Stroke in Patients by Using Biostatistics: An Exploratory Study
  Chih-Chun Hsiao, Chun-Gu Cheng, Cheng-Chueh Chen, Hung-Wen Chiu, Hui-Chen Lin, Chun-An Cheng
  Journal of Personalized Medicine.2023; 13(4): 624.     CrossRef
• Clinical index to quantify the 1-year risk for common postpartum mental disorders at the time of delivery (PMH CAREPLAN): development and internal validation
  Simone N. Vigod, Natalie Urbach, Andrew Calzavara, Cindy-Lee Dennis, Andrea Gruneir, Brett D. Thombs, Mark Walker, Hilary K. Brown
  The British Journal of Psychiatry.2023; 223(3): 422.     CrossRef
• Prediction of Foot Ulcers Using Artificial Intelligence for Diabetic Patients at Cairo University Hospital, Egypt
  Khadraa Mohamed Mousa, Farid Ali Mousa, Helalia Shalabi Mohamed, Manal Mohamed Elsawy
  SAGE Open Nursing.2023;[Epub]     CrossRef
• Genetic Studies Investigating Susceptibility to Psoriatic Arthritis: A Narrative Review
  Mehreen Soomro, Ryan Hum, Anne Barton, John Bowes
  Clinical Therapeutics.2023; 45(9): 810.     CrossRef
• Scope, design, and reporting of prediction models for antineoplastic drugs‐related adverse drug events: A systematic review of machine learning and traditional modeling
  Dan Jiang, Zaiwei Song, Yang Hu, Xinya Li, Rongsheng Zhao
  Journal of Evidence-Based Medicine.2023; 16(4): 420.     CrossRef
• Using the Weibull Accelerated Failure Time Regression Model to Predict Time to Health Events
  Enwu Liu, Ryan Yan Liu, Karen Lim
  Applied Sciences.2023; 13(24): 13041.     CrossRef
• Development and validation of a nomogram for predicting low birth weight among pregnant women who had antenatal care visits at Debre Markos Comprehensive and Specialized Hospital, Ethiopia
  Bezawit Melak Fente, Getayeneh Antehunegn Tesema, Temesgen Worku Gudayu, Mengstu Melkamu Asaye
  Frontiers in Medicine.2023;[Epub]     CrossRef
• Prediction of psychosis: model development and internal validation of a personalized risk calculator
  Tae Young Lee, Wu Jeong Hwang, Nahrie S. Kim, Inkyung Park, Silvia Kyungjin Lho, Sun-Young Moon, Sanghoon Oh, Junhee Lee, Minah Kim, Choong-Wan Woo, Jun Soo Kwon
  Psychological Medicine.2022; 52(13): 2632.     CrossRef
• Designing a Predictive Model for Colorectal Neoplasia Diagnosis Based on Clinical and Laboratory Findings in Colonoscopy Candidate Patients
  H. Ghajari, A. Sadeghi, S. Khodakarim, M. Zali, S. S. Hashemi Nazari
  Journal of Gastrointestinal Cancer.2022; 53(4): 880.     CrossRef
• Avoiding immediate whole-body trauma CT: a prospective observational study in stable trauma patients
  Elisa Reitano, Stefano Granieri, Fabrizio Sammartano, Stefania Cimbanassi, Miriam Galati, Shailvi Gupta, Angelo Vanzulli, Osvaldo Chiara
  Updates in Surgery.2022; 74(1): 343.     CrossRef
• Survival Estimation, Prognostic Factors Evaluation, and Prognostic Prediction Nomogram Construction of Breast Cancer Patients with Bone Metastasis in the Department of Bone and Soft Tissue Tumor: A Single Center Experience of 8 Years in Tianjin, China
  Yao Xu, Haixiao Wu, Guijun Xu, Zhuming Yin, Xin Wang, Vladimir P. Chekhonin, Karl Peltzer, Shu Li, Huiyang Li, Jin Zhang, Wenjuan Ma, Chao Zhang, Sharad Goyal
  The Breast Journal.2022; 2022: 1.     CrossRef
• Machine Learning Model-Based Simple Clinical Information to Predict Decreased Left Atrial Appendage Flow Velocity
  Chao Li, Guanhua Dou, Yipu Ding, Ran Xin, Jing Wang, Jun Guo, Yundai Chen, Junjie Yang
  Journal of Personalized Medicine.2022; 12(3): 437.     CrossRef
• Performance of Diabetes and Kidney Disease Screening Scores in Contemporary United States and Korean Populations
  Liela Meng, Keun-Sang Kwon, Dae Jung Kim, Yong-ho Lee, Jeehyoung Kim, Abhijit V. Kshirsagar, Heejung Bang
  Diabetes & Metabolism Journal.2022; 46(2): 273.     CrossRef
• The Prediction of Diabetes
  Lalit Kumar, Prashant Johri
  International Journal of Reliable and Quality E-Healthcare.2022; 11(1): 1.     CrossRef
• Endoscopic detection of esophageallow‐gradesquamous dysplasia: How to predict pathologic upgrades before treatment?
  Han Chen, Xiao Ying Zhou, Shuo Li, Liu Qin Jiang, Jie Hua, Xin Min Si, Guo Xin Zhang
  Journal of Digestive Diseases.2022; 23(4): 209.     CrossRef
• Predicting outcomes after traumatic brain injury: A novel hospital prediction model for a patient reported outcome
  Rachel S. Morris, Juan F. Figueroa, Courtney J. Pokrzywa, Jason K. Barber, Nancy R. Temkin, Carisa Bergner, Basil S. Karam, Patrick Murphy, Lindsay D. Nelson, Purushottam Laud, Zara Cooper, Marc de Moya, Colleen Trevino, Christopher J. Tignanelli, Terri A
  The American Journal of Surgery.2022; 224(4): 1150.     CrossRef
• Investigating factors affecting musculoskeletal disorders: Predictive models for identifying caregivers at risk
  Abdulrahman M. Khamaj, Abdulelah M. Ali, Mohd Mukhtar Alam
  Work.2022; 72(4): 1311.     CrossRef
• A scoping review of complication prediction models in spinal surgery: An analysis of model development, validation and impact
  Toros C. Canturk, Daniel Czikk, Eugene K. Wai, Philippe Phan, Alexandra Stratton, Wojtek Michalowski, Stephen Kingwell
  North American Spine Society Journal (NASSJ).2022; 11: 100142.     CrossRef
• Dynamic Predictive Models With Visualized Machine Learning for Assessing Chondrosarcoma Overall Survival
  Wenle Li, Gui Wang, Rilige Wu, Shengtao Dong, Haosheng Wang, Chan Xu, Bing Wang, Wanying Li, Zhaohui Hu, Qi Chen, Chengliang Yin
  Frontiers in Oncology.2022;[Epub]     CrossRef
• Prognostic Nomogram of Osteocarcinoma after Surgical Treatment
  Qiuli Wu, Canchun Yang, Haolin Yan, Zheyu Wang, Zhilei Zhang, Qiwei Wang, Renyuan Huang, Xumin Hu, Bo Li, Xueliang Wu
  Journal of Oncology.2022; 2022: 1.     CrossRef
• External validation and clinical application of the predictive model for severe hypoglycemia
  Jae-Seung Yun, Kyungdo Han, Soo-Yeon Choi, Seon-Ah Cha, Yu-Bae Ahn, Seung-Hyun Ko
  Frontiers in Endocrinology.2022;[Epub]     CrossRef
• Clustering of trauma patients based on longitudinal data and the application of machine learning to predict recovery
  Kostas Stoitsas, Saurabh Bahulikar, Leonie de Munter, Mariska A. C. de Jongh, Maria A. C. Jansen, Merel M. Jung, Marijn van Wingerden, Katrijn Van Deun
  Scientific Reports.2022;[Epub]     CrossRef
• Clinical predictors of antipsychotic treatment resistance: Development and internal validation of a prognostic prediction model by the STRATA-G consortium
  Sophie E. Smart, Deborah Agbedjro, Antonio F. Pardiñas, Olesya Ajnakina, Luis Alameda, Ole A. Andreassen, Thomas R.E. Barnes, Domenico Berardi, Sara Camporesi, Martine Cleusix, Philippe Conus, Benedicto Crespo-Facorro, Giuseppe D'Andrea, Arsime Demjaha, M
  Schizophrenia Research.2022; 250: 1.     CrossRef
• Factors associated with low-compliance bladder in end-stage renal disease patients and development of a clinical prediction model for urodynamic evaluation: the DUDi score
  Teerayut Tangpaitoon, Valeerat Swatesutipun
  International Urology and Nephrology.2022; 55(1): 75.     CrossRef
• Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness
  Juyoung Shin, Joonyub Lee, Taehoon Ko, Kanghyuck Lee, Yera Choi, Hun-Sung Kim
  Journal of Personalized Medicine.2022; 12(11): 1899.     CrossRef
• Assessment of Simple Bedside Wound Characteristics for a Prediction Model for Diabetic Foot Ulcer Outcomes
  Clara Bender, Simon Lebech Cichosz, Louise Pape-Haugaard, Merete Hartun Jensen, Susan Bermark, Anders Christian Laursen, Ole Hejlesen
  Journal of Diabetes Science and Technology.2021; 15(5): 1161.     CrossRef
• A Risk Score for Predicting the Incidence of Hemorrhage in Critically Ill Neonates: Development and Validation Study
  Rozeta Sokou, Daniele Piovani, Aikaterini Konstantinidi, Andreas G. Tsantes, Stavroula Parastatidou, Maria Lampridou, Georgios Ioakeimidis, Antonis Gounaris, Nicoletta Iacovidou, Anastasios G. Kriebardis, Marianna Politou, Petros Kopterides, Stefanos Bono
  Thrombosis and Haemostasis.2021; 121(02): 131.     CrossRef
• Development and validation of a risk assessment nomogram for venous thromboembolism associated with hospitalized postoperative Chinese breast cancer patients
  Jing Li, Wan‐Min Qiang, Yan Wang, Xiao‐Yuan Wang
  Journal of Advanced Nursing.2021; 77(1): 473.     CrossRef
• The role of behaviour problems in screening for mental ill-health in adults with intellectual disability
  F. Westlake, A. Hassiotis, G. Unwin, V. Totsika
  The European Journal of Psychiatry.2021; 35(2): 122.     CrossRef
• Deep learning model for classifying endometrial lesions
  YunZheng Zhang, ZiHao Wang, Jin Zhang, CuiCui Wang, YuShan Wang, Hao Chen, LuHe Shan, JiaNing Huo, JiaHui Gu, Xiaoxin Ma
  Journal of Translational Medicine.2021;[Epub]     CrossRef
• Exploration and Development of a Simpler Respiratory Distress Observation Scale (modRDOS-4) as a Dyspnea Screening Tool: A Prospective Bedside Study
  Ru Xin Wong, Ho Shirlynn, Yen Sin Koh, Stella Goh Seow Lin, Daniel Quah, Qingyuan Zhuang
  Palliative Medicine Reports.2021; 2(1): 9.     CrossRef
• Impact of CT convolution kernel on robustness of radiomic features for different lung diseases and tissue types
  Sarah Denzler, Diem Vuong, Marta Bogowicz, Matea Pavic, Thomas Frauenfelder, Sandra Thierstein, Eric Innocents Eboulet, Britta Maurer, Janine Schniering, Hubert Szymon Gabryś, Isabelle Schmitt-Opitz, Miklos Pless, Robert Foerster, Matthias Guckenberger, S
  The British Journal of Radiology.2021;[Epub]     CrossRef
• An empirical analysis of dealing with patients who are lost to follow-up when developing prognostic models using a cohort design
  Jenna M. Reps, Peter Rijnbeek, Alana Cuthbert, Patrick B. Ryan, Nicole Pratt, Martijn Schuemie
  BMC Medical Informatics and Decision Making.2021;[Epub]     CrossRef
• Predictive Value of Active Sacroiliitis in MRI for Flare Among Chinese Patients with Axial Spondyloarthritis in Remission
  Qing Zheng, Wen Liu, Yu Huang, Zhenyu Gao, Yuanhui Wu, Xiaohong Wang, Meimei Cai, Yan He, Shiju Chen, Bin Wang, Lingyu Liu, Shuqiang Chen, Hongjie Huang, Ling Zheng, Rihui Kang, Xiaohong Zeng, Jing Chen, Huaning Chen, Junmin Chen, Zhibin Li, Guixiu Shi
  Rheumatology and Therapy.2021; 8(1): 411.     CrossRef
• Development of a model for predicting the 4-year risk of symptomatic knee osteoarthritis in China: a longitudinal cohort study
  Limin Wang, Han Lu, Hongbo Chen, Shida Jin, Mengqi Wang, Shaomei Shang
  Arthritis Research & Therapy.2021;[Epub]     CrossRef
• Digital Communication Biomarkers of Mood and Diagnosis in Borderline Personality Disorder, Bipolar Disorder, and Healthy Control Populations
  George Gillett, Niall M. McGowan, Niclas Palmius, Amy C. Bilderbeck, Guy M. Goodwin, Kate E. A. Saunders
  Frontiers in Psychiatry.2021;[Epub]     CrossRef
• Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study
  Fumin Xu, Xiao Chen, Chenwenya Li, Jing Liu, Qiu Qiu, Mi He, Jingjing Xiao, Zhihui Liu, Bingjun Ji, Dongfeng Chen, Kaijun Liu, Mirella Giovarelli
  Mediators of Inflammation.2021; 2021: 1.     CrossRef
• Comparison of multiple statistical models for the development of clinical prediction scores to detect advanced colorectal neoplasms in asymptomatic Thai patients
  Kamonwan Soonklang, Boonying Siribumrungwong, Bunchorn Siripongpreeda, Chirayu Auewarakul
  Medicine.2021; 100(20): e26065.     CrossRef
• European Childhood Obesity Risk Evaluation (CORE) index based on perinatal factors and maternal sociodemographic characteristics: the Feel4Diabetes-study
  Christina Mavrogianni, George Moschonis, Eva Karaglani, Greet Cardon, Violeta Iotova, Pilar De Miguel-Etayo, Esther M. González-Gil, Κaloyan Tsochev, Tsvetalina Tankova, Imre Rurik, Patrick Timpel, Emese Antal, Stavros Liatis, Konstantinos Makrilakis, Geo
  European Journal of Pediatrics.2021; 180(8): 2549.     CrossRef
• A prognostic nomogram based on competing endogenous RNA network for clear‐cell renal cell carcinoma
  Yun Peng, Shangrong Wu, Zihan Xu, Dingkun Hou, Nan Li, Zheyu Zhang, Lili Wang, Haitao Wang
  Cancer Medicine.2021; 10(16): 5499.     CrossRef
• Individual 5-Year Lung Cancer Risk Prediction Model in Korea Using a Nationwide Representative Database
  Yohwan Yeo, Dong Wook Shin, Kyungdo Han, Sang Hyun Park, Keun-Hye Jeon, Jungkwon Lee, Junghyun Kim, Aesun Shin
  Cancers.2021; 13(14): 3496.     CrossRef
• Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort
  Sang Youl Rhee, Ji Min Sung, Sunhee Kim, In-Jeong Cho, Sang-Eun Lee, Hyuk-Jae Chang
  Diabetes & Metabolism Journal.2021; 45(4): 515.     CrossRef
• A nomogram for predicting lymph node metastasis in superficial esophageal squamous cell carcinoma
  Weifeng Zhang, Han Chen, Guoxin Zhang, Guangfu Jin
  The Journal of Biomedical Research.2021; 35(5): 361.     CrossRef
• Relationship Between Sensibility Tests and Functional Outcomes in Patients With Traumatic Upper Limb Nerve Injuries: A Systematic Review
  Liheng Chen, Emmanuel Ogalo, Chloe Haldane, Sean G. Bristol, Michael J. Berger
  Archives of Rehabilitation Research and Clinical Translation.2021; 3(4): 100159.     CrossRef
• Personalized 5-Year Prostate Cancer Risk Prediction Model in Korea Based on Nationwide Representative Data
  Yohwan Yeo, Dong Wook Shin, Jungkwon Lee, Kyungdo Han, Sang Hyun Park, Keun Hye Jeon, Jungeun Shin, Aesun Shin, Jinsung Park
  Journal of Personalized Medicine.2021; 12(1): 2.     CrossRef
• Utility of prediction model score: a proposed tool to standardize the performance and generalizability of clinical predictive models based on systematic review
  Jeff Ehresman, Daniel Lubelski, Zach Pennington, Bethany Hung, A. Karim Ahmed, Tej D. Azad, Kurt Lehner, James Feghali, Zorica Buser, James Harrop, Jefferson Wilson, Shekar Kurpad, Zoher Ghogawala, Daniel M. Sciubba
  Journal of Neurosurgery: Spine.2021; 34(5): 779.     CrossRef
• Prodromal clinical, demographic, and socio-ecological correlates of asthma in adults: a 10-year statewide big data multi-domain analysis
  Jennifer N. Fishe, Jiang Bian, Zhaoyi Chen, Hui Hu, Jae Min, Francois Modave, Mattia Prosperi
  Journal of Asthma.2020; 57(11): 1155.     CrossRef
• Clinical risk prediction with random forests for survival, longitudinal, and multivariate (RF-SLAM) data analysis
  Shannon Wongvibulsin, Katherine C. Wu, Scott L. Zeger
  BMC Medical Research Methodology.2020;[Epub]     CrossRef
• Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review
  M. Pinart, F. Kunath, V. Lieb, I. Tsaur, B. Wullich, Stefanie Schmidt
  World Journal of Urology.2020; 38(3): 613.     CrossRef
• Peripheral Nerve Field Stimulation for Chronic Back Pain: Therapy Outcome Predictive Factors
  Eric‐Jan van Gorp, Sam Eldabe, Konstantin V. Slavin, Philippe Rigoard, Stefaan Goossens, Dorothee Mielke, Giancarlo Barolat, Christ Declerck, Chris Gilmore, Ismaïl Gültuna, Kris C.P. Vissers, Jennifer Tinsley, Rudolf Likar, Pierre‐Philippe Luyet
  Pain Practice.2020; 20(5): 522.     CrossRef
• Biomarker Score in Risk Prediction: Beyond Scientific Evidence and Statistical Performance
  Heejung Bang
  Diabetes & Metabolism Journal.2020; 44(2): 245.     CrossRef
• Variable selection strategies and its importance in clinical prediction modelling
  Mohammad Ziaul Islam Chowdhury, Tanvir C Turin
  Family Medicine and Community Health.2020; 8(1): e000262.     CrossRef
• Reply to the Letter to the Editor: Derivation and Internal Validation of a Clinical Prediction Tool to Predict Nonalcoholic Fatty Liver Disease in Patients With Crohn’s Disease
  Scott McHenry, Matthew A Ciorba, Parakkal Deepak
  Inflammatory Bowel Diseases.2020; 26(6): e46.     CrossRef
• The application of unsupervised deep learning in predictive models using electronic health records
  Lei Wang, Liping Tong, Darcy Davis, Tim Arnold, Tina Esposito
  BMC Medical Research Methodology.2020;[Epub]     CrossRef
• Development and evaluation of an osteoarthritis risk model for integration into primary care health information technology
  Jason E. Black, Amanda L. Terry, Daniel J. Lizotte
  International Journal of Medical Informatics.2020; 141: 104160.     CrossRef
• An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population
  Wenjia Chen, Don D. Sin, J. Mark FitzGerald, Abdollah Safari, Amin Adibi, Mohsen Sadatsafavi
  Chest.2020; 157(3): 547.     CrossRef
• Optimization of the management of pregnant women at high risk of miscarriage and premature birth
  Yu. A. Semenov, V. F. Dolgushina, M. G. Moscvicheva, V. S. Chulkov
  Rossiiskii vestnik akushera-ginekologa.2020; 20(1): 54.     CrossRef
• Developing a triage tool for use in identifying people living with HIV who are at risk for non-retention in HIV care
  Merhawi T Gebrezgi, Kristopher P Fennie, Diana M Sheehan, Boubakari Ibrahimou, Sandra G Jones, Petra Brock, Robert A Ladner, Mary Jo Trepka
  International Journal of STD & AIDS.2020; 31(3): 244.     CrossRef
• The impact of age and comorbidity on the postoperative outcomes after emergency surgical management of complicated intra-abdominal infections
  Carmen Payá-Llorente, Elías Martínez-López, Juan Carlos Sebastián-Tomás, Sandra Santarrufina-Martínez, Nicola de’Angelis, Aleix Martínez-Pérez
  Scientific Reports.2020;[Epub]     CrossRef
• Precision health through prediction modelling: factors to consider before implementing a prediction model in clinical practice
  Mohammad Z. I. Chowdhury, Tanvir C. Turin
  Journal of Primary Health Care.2020; 12(1): 3.     CrossRef
• Demystifying artificial intelligence in pharmacy
  Scott D Nelson, Colin G Walsh, Casey A Olsen, Andrew J McLaughlin, Joseph R LeGrand, Nick Schutz, Thomas A Lasko
  American Journal of Health-System Pharmacy.2020; 77(19): 1556.     CrossRef
• Association does not imply prediction: the accuracy of birthweight in predicting child mortality and anthropometric failure
  Akshay Swaminathan, Rockli Kim, S.V. Subramanian
  Annals of Epidemiology.2020; 50: 7.     CrossRef
• Who's at Risk? A Prognostic Model for Severity Prediction in Pediatric Acute Pancreatitis
  Peter R. Farrell, Lindsey Hornung, Peter Farmer, Angelica W. DesPain, Esther Kim, Ryan Pearman, Beemnet Neway, Ashley Serrette, Sona Sehgal, James E. Heubi, Tom K. Lin, Jaimie D. Nathan, David S. Vitale, Maisam Abu‐El‐Haija
  Journal of Pediatric Gastroenterology and Nutrition.2020; 71(4): 536.     CrossRef
• Biomarkers of Fabry Nephropathy: Review and Future Perspective
  Tina Levstek, Bojan Vujkovac, Katarina Trebusak Podkrajsek
  Genes.2020; 11(9): 1091.     CrossRef
• Coledocolitiasis y pancreatitis: las dificultades de la predicción
  David Benigno Páramo Hernández
  Revista Colombiana de Gastroenterología.2020; 35(3): 266.     CrossRef
• Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar
  Yan Li, Matthew Sperrin, Darren M Ashcroft, Tjeerd Pieter van Staa
  BMJ.2020; : m3919.     CrossRef
• Outcome prediction with serial neuron-specific enolase and machine learning in anoxic-ischaemic disorders of consciousness
  Emily Muller, Jonathan P. Shock, Andreas Bender, Julian Kleeberger, Tobias Högen, Martin Rosenfelder, Bubacarr Bah, Alex Lopez-Rolon
  Computers in Biology and Medicine.2019; 107: 145.     CrossRef
• Machine learning models to predict disease progression among veterans with hepatitis C virus
  Monica A. Konerman, Lauren A. Beste, Tony Van, Boang Liu, Xuefei Zhang, Ji Zhu, Sameer D. Saini, Grace L. Su, Brahmajee K. Nallamothu, George N. Ioannou, Akbar K. Waljee, Davide Bacciu
  PLOS ONE.2019; 14(1): e0208141.     CrossRef
• A novel risk calculator to predict outcome after surgery for symptomatic spinal metastases; use of a large prospective patient database to personalise surgical management
  David Choi, Menelaos Pavlou, Rumana Omar, Mark Arts, Laurent Balabaud, Jacob Maciej Buchowski, Cody Bunger, Chun Kee Chung, Maarten Hubert Coppes, Bart Depreitere, Michael George Fehlings, Norio Kawahara, Chong-Suh Lee, YeeLing Leung, Juan Antonio Martin-
  European Journal of Cancer.2019; 107: 28.     CrossRef
• Big Data Research in Neuro-Ophthalmology: Promises and Pitfalls
  Heather E. Moss, Charlotte E. Joslin, Daniel S. Rubin, Steven Roth
  Journal of Neuro-Ophthalmology.2019; 39(4): 480.     CrossRef
• Nonalcoholic Fatty Liver Disease in Diabetes. Part I: Epidemiology and Diagnosis
  Yong-ho Lee, Yongin Cho, Byung-Wan Lee, Cheol-Young Park, Dae Ho Lee, Bong-Soo Cha, Eun-Jung Rhee
  Diabetes & Metabolism Journal.2019; 43(1): 31.     CrossRef
• The use of rigorous methods was strongly warranted among prognostic prediction models for obstetric care
  Jing Tan, Yana Qi, Chunrong Liu, Yiquan Xiong, Qiao He, Guiting Zhang, Meng Chen, Guolin He, Wen Wang, Xinghui Liu, Xin Sun
  Journal of Clinical Epidemiology.2019; 115: 98.     CrossRef
• Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes
  Edsel Ing, Wanhua Su, Matthias Schonlau, Nurhan Torun
  Canadian Journal of Ophthalmology.2019; 54(1): 116.     CrossRef
• Identifying a risk score for childhood obesity based on predictors identified in pregnant women and 1-year-old infants: An analysis of the data of the Hokkaido Study on Environment and Children’s Health
  Yasuaki Saijo, Yoshiya Ito, Eiji Yoshioka, Yukihiro Sato, Machiko Minatoya, Atsuko Araki, Chihiro Miyashita, Reiko Kishi
  Clinical Pediatric Endocrinology.2019; 28(3): 81.     CrossRef
• Development and performance evaluation of the Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists’ input to prevent medication-related problems
  Cathy Geeson, Li Wei, Bryony Dean Franklin
  BMJ Quality & Safety.2019; 28(8): 645.     CrossRef
• Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures
  Robert K. Merrill, Rocco M. Ferrandino, Ryan Hoffman, Gene W. Shaffer, Anthony Ndu
  The Journal of Foot and Ankle Surgery.2019; 58(3): 410.     CrossRef
• Multidimensional screening for predicting pain problems in adults: a systematic review of screening tools and validation studies
  Elke Veirman, Dimitri M. L. Van Ryckeghem, Annick De Paepe, Olivia J. Kirtley, Geert Crombez
  PAIN Reports.2019; 4(5): e775.     CrossRef
• iHealthcare: Predictive Model Analysis Concerning Big Data Applications for Interactive Healthcare Systems †
  Md. Ataur Rahman Bhuiyan, Md. Rifat Ullah, Amit Kumar Das
  Applied Sciences.2019; 9(16): 3365.     CrossRef
• Development of personalized mobile assistant for chronic disease patients: diabetes mellitus case study
  M.V. Kabyshev, S.V. Kovalchuk
  Procedia Computer Science.2019; 156: 123.     CrossRef
• Validation of childhood asthma predictive tools: A systematic review
  Silvia Colicino, Daniel Munblit, Cosetta Minelli, Adnan Custovic, Paul Cullinan
  Clinical & Experimental Allergy.2019; 49(4): 410.     CrossRef
• Predicting intradialytic hypotension using heart rate variability
  Samel Park, Wook-Joon Kim, Nam-Jun Cho, Chi-Young Choi, Nam Hun Heo, Hyo-Wook Gil, Eun Young Lee
  Scientific Reports.2019;[Epub]     CrossRef
• Predicting treatment response using pharmacy register in migraine
  Thomas Folkmann Hansen, Mona Ameri Chalmer, Thilde Marie Haspang, Lisette Kogelman, Jes Olesen
  The Journal of Headache and Pain.2019;[Epub]     CrossRef
• Development and Evaluation of Electronic Health Record Data-Driven Predictive Models for Pressure Ulcers
  Seul Ki Park, Hyeoun-Ae Park, Hee Hwang
  Journal of Korean Academy of Nursing.2019; 49(5): 575.     CrossRef
• Characteristics and outcome of acute heart failure patients according to the severity of peripheral oedema
  Ahmad Shoaib, Mamas A. Mamas, Qazi S. Ahmad, Theresa M. McDonagh, Suzanna M.C. Hardman, Muhammad Rashid, Robert Butler, Simon Duckett, Duwarakan Satchithananda, James Nolan, Henry J. Dargie, Andrew L. Clark, John G.F. Cleland
  International Journal of Cardiology.2019; 285: 40.     CrossRef
• Methodological standards for the development and evaluation of clinical prediction rules: a review of the literature
  Laura E. Cowley, Daniel M. Farewell, Sabine Maguire, Alison M. Kemp
  Diagnostic and Prognostic Research.2019;[Epub]     CrossRef
• Development and validation of a nomogram to predict the prognosis of patients with squamous cell carcinoma of the bladder
  Mei-Di Hu, Si-Hai Chen, Yuan Liu, Ling-Hua Jia
  Bioscience Reports.2019;[Epub]     CrossRef
• Assessing surgical difficulty in locally advanced mid–low rectal cancer: the accuracy of two MRI‐based predictive scores
  N. de'Angelis, F. Pigneur, A. Martínez‐Pérez, G. C. Vitali, F. Landi, S. A. Gómez‐Abril, M. Assalino, E. Espin, F. Ris, A. Luciani, F. Brunetti
  Colorectal Disease.2019; 21(3): 277.     CrossRef
• External Validation of START nomogram to predict 3-Month unfavorable outcome in Chinese acute stroke patients
  BaiLi Song, XiangLiang Chen, Dan Tang, Mako Ibrahim, YuKai Liu, Linda Nyame, Teng Jiang, Wei Wang, Xiang Li, Chao Sun, Zheng Zhao, Jie Yang, JunShan Zhou, JianJun Zou
  Journal of Stroke and Cerebrovascular Diseases.2019; 28(6): 1618.     CrossRef
• Development and Validation of the Korean Diabetes Risk Score: A 10-Year National Cohort Study
  Kyoung Hwa Ha, Yong-ho Lee, Sun Ok Song, Jae-woo Lee, Dong Wook Kim, Kyung-hee Cho, Dae Jung Kim
  Diabetes & Metabolism Journal.2018; 42(5): 402.     CrossRef
• Clinical relevance and validity of tools to predict infant, childhood and adulthood obesity: a systematic review
  Oliver J Canfell, Robyn Littlewood, Olivia RL Wright, Jacqueline L Walker
  Public Health Nutrition.2018; 21(17): 3135.     CrossRef
• Letter to Editor
  Laura E Cowley, Sabine A Maguire, Daniel M Farewell, Alison M Kemp
  Law, Probability and Risk.2018; 17(3): 275.     CrossRef
• Self‐report assessment of severe periodontitis: Periodontal screening score development
  Maria Clotilde Carra, Alice Gueguen, Frédérique Thomas, Bruno Pannier, Giuseppina Caligiuri, Philippe Gabriel Steg, Marie Zins, Philippe Bouchard
  Journal of Clinical Periodontology.2018; 45(7): 818.     CrossRef
• Predictive validity of the CriSTAL tool for short-term mortality in older people presenting at Emergency Departments: a prospective study
  Magnolia Cardona, Ebony T. Lewis, Mette R. Kristensen, Helene Skjøt-Arkil, Anette Addy Ekmann, Hanne H. Nygaard, Jonas J. Jensen, Rune O. Jensen, Jonas L. Pedersen, Robin M. Turner, Frances Garden, Hatem Alkhouri, Stephen Asha, John Mackenzie, Margaret Pe
  European Geriatric Medicine.2018; 9(6): 891.     CrossRef
• Prediction of Drug-Related Risks Using Clinical Context Information in Longitudinal Claims Data
  Andreas D. Meid, Andreas Groll, Dirk Heider, Sarah Mächler, Jürgen-Bernhard Adler, Christian Günster, Hans-Helmut König, Walter E. Haefeli
  Value in Health.2018; 21(12): 1390.     CrossRef
• Articles inEndocrinology and Metabolismin 2016
  Won-Young Lee
  Endocrinology and Metabolism.2017; 32(1): 62.     CrossRef
• Development of Clinical Data Mart of HMG-CoA Reductase Inhibitor for Varied Clinical Research
  Hun-Sung Kim, Hyunah Kim, Yoo Jin Jeong, Tong Min Kim, So Jung Yang, Sun Jung Baik, Seung-Hwan Lee, Jae Hyoung Cho, In Young Choi, Kun-Ho Yoon
  Endocrinology and Metabolism.2017; 32(1): 90.     CrossRef
• Response to Comment by Ayubi and Safiri. Insulin Resistance Predicts Cognitive Decline: An 11-Year Follow-up of a Nationally Representative Adult Population Sample. Diabetes Care 2017;40:751–758
  Laura L. Ekblad, Juha O. Rinne, Pauli Puukka, Hanna Laine, Satu Ahtiluoto, Raimo Sulkava, Matti Viitanen, Antti Jula
  Diabetes Care.2017; 40(9): e136.     CrossRef
• Encrypted prediction: A hacker's perspective
  Tara Karamlou, Daniel A. Velez, John J. Nigro
  The Journal of Thoracic and Cardiovascular Surgery.2017; 154(6): 2038.     CrossRef
• Personalized medicine. Closing the gap between knowledge and clinical practice
  Juan-Manuel Anaya, Carolina Duarte-Rey, Juan C. Sarmiento-Monroy, David Bardey, John Castiblanco, Adriana Rojas-Villarraga
  Autoimmunity Reviews.2016; 15(8): 833.     CrossRef
• Comparison of screening scores for diabetes and prediabetes
  Eduard Poltavskiy, Dae Jung Kim, Heejung Bang
  Diabetes Research and Clinical Practice.2016; 118: 146.     CrossRef

Diabetes mellitus is a leading cause of mortality and increased disability-adjusted life years worldwide. In Korea, the prevalence of diabetes increased from 8.6% to 11.0% in 2001 to 2013 and the prevalence of adult obesity, which is the most important risk factor of diabetes, increased from 29.2% to 31.8% during the same period. There has been a dramatic increase in the number of obese Koreans with diabetes in recent decades and the prevalence of diabetes in people aged 40 years and older also increased in 2001 to 2013. Nevertheless, the mean age at the first diagnosis of diabetes was very similar for men in 2005 and 2013, while the mean age for women decreased slightly. There is an inverse linear relationship between body mass index and age at the diagnosis of diabetes among those who are newly diagnosed. Accordingly, the prevalence of diabetes is increasingly shifting to younger individuals and those who are obese. Therefore, public efforts should focus on healthy lifestyle changes, primary prevention measures, screening for the early detection of diabetes, and long-term management.

Citations

Citations to this article as recorded by  

• Cluster analysis based on fasting and postprandial plasma glucose and insulin concentrations
  Miguel Altuve, Erika Severeyn
  International Journal of Diabetes in Developing Countries.2024;[Epub]     CrossRef
• Variations in health-related quality of life (EQ-5D) associated with cardiovascular health: a cross-sectional study of adults with diabetes in the Korean general population
  Hyejin Jung
  BMJ Open.2024; 14(5): e081789.     CrossRef
• Smoking behavior change and the risk of pneumonia hospitalization among smokers with diabetes mellitus
  Dong-Woo Han, Wonyoung Jung, Kyu Na Lee, Kyungdo Han, Sei Won Lee, Dong Wook Shin
  Scientific Reports.2023;[Epub]     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
• Rising Incidence of Diabetes in Young Adults in South Korea: A National Cohort Study
  Hyun Ho Choi, Giwoong Choi, Hojun Yoon, Kyoung Hwa Ha, Dae Jung Kim
  Diabetes & Metabolism Journal.2022; 46(5): 803.     CrossRef
• Differences in health behavior and nutrient intake status between diabetes-aware and unaware Korean adults based on the Korea national health and nutrition examination survey 2016–18 data: A cross-sectional study
  Anshul Sharma, Chen Lulu, Kee-Ho Song, Hae-Jeung Lee
  Frontiers in Public Health.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
• Did Sejong the Great have ankylosing spondylitis? The oldest documented case of ankylosing spondylitis
  JiHwan Lee
  International Journal of Rheumatic Diseases.2021; 24(2): 203.     CrossRef
• Diabetes Fact Sheets in Korea, 2020: An Appraisal of Current Status
  Chan-Hee Jung, Jang Won Son, Shinae Kang, Won Jun Kim, Hun-Sung Kim, Hae Soon Kim, Mihae Seo, Hye-Jung Shin, Seong-Su Lee, Su Jin Jeong, Yongin Cho, Seung Jin Han, Hyang Mi Jang, Mira Rho, Shinbi Lee, Mihyun Koo, Been Yoo, Jung-Wha Moon, Hye Young Lee, Ja
  Diabetes & Metabolism Journal.2021; 45(1): 1.     CrossRef
• Association between living alone and incident type 2 diabetes among middle-aged individuals in Korea: a nationwide cohort study
  Ga Eun Nam, Wonsock Kim, Kyungdo Han, Jin-Hyung Jung, Byoungduck Han, Jinwook Kim, Nan Hee Kim, Kyung Mook Choi, Kyung Hwan Cho, Yong Gyu Park, Seon Mee Kim
  Scientific Reports.2021;[Epub]     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
• A 9-Year Comparison of Dementia Prevalence in Korea: Results of NaSDEK 2008 and 2017
  Seung Wan Suh, You Joung Kim, Kyung Phil Kwak, Kiwon Kim, Moon-Doo Kim, Byung-Soo Kim, Bong Jo Kim, Shin Gyeom Kim, Jeong Lan Kim, Tae Hui Kim, Seok Woo Moon, Kyung Won Park, Jong-Il Park, Joon Hyuk Park, Jae Nam Bae, Jiyeong Seo, Su Jeong Seong, Sang Joo
  Journal of Alzheimer's Disease.2021; 81(2): 821.     CrossRef
• Trends of Diabetes and Prediabetes Prevalence among Korean Adolescents From 2007 to 2018
  Ji Hyun Kim, Jung Sub Lim
  Journal of Korean Medical Science.2021;[Epub]     CrossRef
• Breast Cancer Statistics in Korea, 2018
  Sang Yull Kang, Sae Byul Lee, Yoo Seok Kim, Zisun Kim, Hyun Yul Kim, Hee Jeong Kim, Sungmin Park, Soo Youn Bae, Kwanghyun Yoon, Se Kyung Lee, Kyu-Won Jung, Jaihong Han, Hyun Jo Youn
  Journal of Breast Cancer.2021; 24(2): 123.     CrossRef
• Longitudinal Changes in Clinical Features, Management, and Outcomes of Idiopathic Pulmonary Fibrosis. A Nationwide Cohort Study
  Sung Woo Moon, Song Yee Kim, Man Pyo Chung, Hongseok Yoo, Sung Hwan Jeong, Dong Soon Kim, Jin Woo Song, Hong Lyeol Lee, Sun Mi Choi, Young Whan Kim, Yong Hyun Kim, Choon-Sik Park, Sung-Woo Park, Jong Sun Park, Yangjin Jegal, Jongmin Lee, Soo-Taek Uh, Tae-
  Annals of the American Thoracic Society.2021; 18(5): 780.     CrossRef
• Association between Inflammatory Markers and Glycemic Control in Korean Diabetic Patients
  Min Kang, Seok-Joon Sohn
  Journal of Health Informatics and Statistics.2021; 46(3): 247.     CrossRef
• Associations between obesity, weight change and decreased renal function in Korean type 2 diabetic patients: a longitudinal follow-up study
  Bo-Yeon Kim, Dug-Hyun Choi, Chan-Hee Jung, Ji-Oh Mok, Chul-Hee Kim
  BMC Endocrine Disorders.2021;[Epub]     CrossRef
• Role of Estrogen in Type 1 and Type 2 Diabetes Mellitus: A Review of Clinical and Preclinical Data
  Monica De Paoli, Geoff H. Werstuck
  Canadian Journal of Diabetes.2020; 44(5): 448.     CrossRef
• Site-specific cancer risk in patients with type 2 diabetes: a nationwide population-based cohort study in Korea
  Suk Kyeong Kim, Ju-Young Jang, Dong-Lim Kim, Young A Rhyu, Suh Eun Lee, Seung-Hyun Ko, Kyungdo Han, Kee-Ho Song
  The Korean Journal of Internal Medicine.2020; 35(3): 641.     CrossRef
• Alteration of Microbiome Profile by D-Allulose in Amelioration of High-Fat-Diet-Induced Obesity in Mice
  Youngji Han, Haryung Park, Bo-Ra Choi, Yosep Ji, Eun-Young Kwon, Myung-Sook Choi
  Nutrients.2020; 12(2): 352.     CrossRef
• Type 2 diabetes: epidemiological changes at Instituto Mexicano del Seguro Social—associated with complications in Mexico
  Jessie N. Zurita-Cruz, Leticia Manuel-Apolinar, María Luisa Arellano-Flores, Alejandro Gutierrez-Gonzalez, Aleida de Jesús Rivera-Hernández, Rosa Angélica Carranza-Muleiro, Víctor Hugo Borja-Aburto, Nelly Cisneros-González
  International Journal of Diabetes in Developing Countries.2020; 40(2): 178.     CrossRef
• Effects of Particulate Respirator Use on Cardiopulmonary Function in Elderly Women: a Quasi-Experimental Study
  Youn-Hee Lim, Woosung Kim, Yumi Choi, Hwan-Cheol Kim, Geunjoo Na, Hyoung-Ryoul Kim, Yun-Chul Hong
  Journal of Korean Medical Science.2020;[Epub]     CrossRef
• GLP‑1 receptor agonist on cardiovascular complications of diabetes mellitus
  Fengjun Liu, Yanhua Kong
  Experimental and Therapeutic Medicine.2020;[Epub]     CrossRef
• Plasma sphingomyelins increase in pre-diabetic Korean men with abdominal obesity
  Seung-Soon Im, Hyeon Young Park, Jong Cheol Shon, In-Sung Chung, Ho Chan Cho, Kwang-Hyeon Liu, Dae-Kyu Song, Kyoung Heon Kim
  PLOS ONE.2019; 14(3): e0213285.     CrossRef
• Diabetes Fact Sheets in Korea, 2018: An Appraisal of Current Status
  Bo-Yeon Kim, Jong Chul Won, Jae Hyuk Lee, Hun-Sung Kim, Jung Hwan Park, Kyoung Hwa Ha, Kyu Chang Won, Dae Jung Kim, Kyong Soo Park
  Diabetes & Metabolism Journal.2019; 43(4): 487.     CrossRef
• Analysis of diabetes quality assessment findings and future directions for the appropriate management of diabetes in Korea
  Yu Jin Kim, Suk Chon, Seungjoon Oh, Jeong-taek Woo, Sung Woon Kim, Sang Youl Rhee
  The Korean Journal of Internal Medicine.2019; 34(1): 125.     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
• Age-specific diabetes risk by the number of metabolic syndrome components: a Korean nationwide cohort study
  Min-Kyung Lee, Kyungdo Han, Hyuk-Sang Kwon
  Diabetology & Metabolic Syndrome.2019;[Epub]     CrossRef
• Changes in real-life practice for hepatocellular carcinoma patients in the Republic of Korea over a 12-year period: A nationwide random sample study
  Beom Kyung Kim, Do Young Kim, Kwang-Hyub Han, Jinsil Seong, Jung Weon Lee
  PLOS ONE.2019; 14(10): e0223678.     CrossRef
• Association between continuity of care and type 2 diabetes development among patients with thyroid disorder
  Sang Ah Lee, Dong-Woo Choi, Junhyun Kwon, Doo Woong Lee, Eun-Cheol Park
  Medicine.2019; 98(52): e18537.     CrossRef
• Association of C-Reactive Protein with Risk of Developing Type 2 Diabetes Mellitus, and Role of Obesity and Hypertension: A Large Population-Based Korean Cohort Study
  Suganya Kanmani, Minji Kwon, Moon-Kyung Shin, Mi Kyung Kim
  Scientific Reports.2019;[Epub]     CrossRef
• Egg consumption is associated with a lower risk of type 2 diabetes in middle-aged and older men
  Jieul Lee, Jihye Kim
  Nutrition Research and Practice.2018; 12(5): 396.     CrossRef
• Diabetes, Frequency of Exercise, and Mortality Over 12 Years: Analysis of the National Health Insurance Service-Health Screening (NHIS-HEALS) Database
  Woo Young Shin, Taehee Lee, Da-Hye Jeon, Hyeon Chang Kim
  Journal of Korean Medical Science.2018;[Epub]     CrossRef
• Epidemiology of liver cancer in South Korea
  Bo Hyun Kim, Joong-Won Park
  Clinical and Molecular Hepatology.2018; 24(1): 1.     CrossRef
• Letter: Clinical Characteristics of People with Newly Diagnosed Type 2 Diabetes between 2015 and 2016: Difference by Age and Body Mass Index (Diabetes Metab J 2018;42:137-46)
  Ah Reum Khang
  Diabetes & Metabolism Journal.2018; 42(3): 249.     CrossRef
• Efficacy and safety of Panax ginseng berry extract on glycemic control: A 12-wk randomized, double-blind, and placebo-controlled clinical trial
  Han Seok Choi, Sunmi Kim, Min Jung Kim, Myung-Sunny Kim, Juewon Kim, Chan-Woong Park, Daebang Seo, Song Seok Shin, Sang Woo Oh
  Journal of Ginseng Research.2018; 42(1): 90.     CrossRef
• Response: Clinical Characteristics of People with Newly Diagnosed Type 2 Diabetes between 2015 and 2016: Difference by Age and Body Mass Index (Diabetes Metab J2018;42:137-46)
  Kyoung Hwa Ha, Dae Jung Kim, Sungrae Kim
  Diabetes & Metabolism Journal.2018; 42(3): 251.     CrossRef
• Prediction of Type 2 Diabetes Remission after Bariatric or Metabolic Surgery
  Ji Yeon Park
  Journal of Obesity & Metabolic Syndrome.2018; 27(4): 213.     CrossRef
• Waist‐to‐calf circumstance ratio is an independent predictor of hepatic steatosis and fibrosis in patients with type 2 diabetes
  Eun Yeong Choe, Yong‐ho Lee, Young Ju Choi, Byung Wook Huh, Byung‐Wan Lee, Soo‐Kyung Kim, Eun Seok Kang, Bong‐Soo Cha, Eun Jig Lee, Kap Bum Huh, Zobair M Younossi
  Journal of Gastroenterology and Hepatology.2018; 33(5): 1082.     CrossRef
• Prevalence of Comorbidities among Patients with Diabetes
  Suyoung Kim, Eun-Hee Nah, Seon Cho
  Journal of Health Informatics and Statistics.2018; 43(3): 237.     CrossRef
• Risk of new-onset diabetes among patients treated with statins according to hypertension and gender: Results from a nationwide health-screening cohort
  Sang-Eun Lee, Ji Min Sung, In-Jeong Cho, Hyeon Chang Kim, Hyuk-Jae Chang, Lamberto Manzoli
  PLOS ONE.2018; 13(4): e0195459.     CrossRef
• Outcomes of living donor kidney transplantation in diabetic patients: age and sex matched comparison with non-diabetic patients
  Chung Hee Baek, Hyosang Kim, Seung Don Baek, Mun Jang, Wonhak Kim, Won Seok Yang, Duck Jong Han, Su-Kil Park
  The Korean Journal of Internal Medicine.2018; 33(2): 356.     CrossRef
• An Analysis of The Morbidity and Mortality of Diabetes Mellitus in a Forensic Context
  Chong Zhou, Roger W. Byard
  Journal of Forensic Sciences.2018; 63(4): 1149.     CrossRef
• Favorable glycemic response after pancreatoduodenectomy in both patients with pancreatic cancer and patients with non-pancreatic cancer
  Seo Young Sohn, Eun Kyung Lee, Sung-Sik Han, You Jin Lee, Yul Hwangbo, Young Hwa Kang, Seung Duk Lee, Seong Hoon Kim, Sang Myung Woo, Woo Jin Lee, Eun Kyung Hong, Sang-Jae Park
  Medicine.2018; 97(18): e0590.     CrossRef
• Comparison of Open and Laparoscopic Gastrectomy in Elderly Patients
  Su Mi Kim, Ho Geun Youn, Ji Yeong An, Yoon Young Choi, Sung Hoon Noh, Seung Jong Oh, Tae Sung Sohn, Sung Kim
  Journal of Gastrointestinal Surgery.2018; 22(5): 785.     CrossRef
• Development and Validation of the Korean Diabetes Risk Score: A 10-Year National Cohort Study
  Kyoung Hwa Ha, Yong-ho Lee, Sun Ok Song, Jae-woo Lee, Dong Wook Kim, Kyung-hee Cho, Dae Jung Kim
  Diabetes & Metabolism Journal.2018; 42(5): 402.     CrossRef
• Trends in diabetes prevalence among Korean adults based on Korean National Health and Nutrition Examination Surveys III–VI
  Jae-woo Lee, Hee-Taik Kang, Hyoung-Ji Lim, Byoungjin Park
  Diabetes Research and Clinical Practice.2018; 138: 57.     CrossRef
• Clinical Characteristics of People with Newly Diagnosed Type 2 Diabetes between 2015 and 2016: Difference by Age and Body Mass Index
  Kyoung Hwa Ha, Cheol Young Park, In Kyung Jeong, Hyun Jin Kim, Sang-Yong Kim, Won Jun Kim, Ji Sung Yoon, In Joo Kim, Dae Jung Kim, Sungrae Kim
  Diabetes & Metabolism Journal.2018; 42(2): 137.     CrossRef
• Nonalcoholic fatty liver disease-associated hepatocellular carcinoma in a hepatitis B virus-endemic area
  Chang Hwi Yoon, Young-Joo Jin, Jin Woo Lee
  European Journal of Gastroenterology & Hepatology.2018; 30(9): 1090.     CrossRef
• Prediction of Diabetes Remission after Bariatric or Metabolic Surgery
  Ji Yeon Park
  Journal of Metabolic and Bariatric Surgery.2018; 7(1): 22.     CrossRef
• Incidence and predictors of type 2 diabetes among Koreans: A 12-year follow up of the Korean Genome and Epidemiology Study
  Seung Jin Han, Hae Jin Kim, Dae Jung Kim, Kwan Woo Lee, Nam H. Cho
  Diabetes Research and Clinical Practice.2017; 123: 173.     CrossRef
• Glycated Hemoglobin and All-Cause Mortality in Korean Type 2 Diabetes
  Mi Suk An, Sun A Kim, Jun-Ho Lee, Seong-Woo Choi, Min-Ho Shin
  Chonnam Medical Journal.2017; 53(3): 223.     CrossRef
• Analysis and comparison of the cost-effectiveness of statins according to the baseline low-density lipoprotein cholesterol level in Korea
  Y. J. Jeong, H. Kim, S. J. Baik, T. M. Kim, S. J. Yang, S.-H. Lee, J.-H. Cho, H. Lee, H. W. Yim, I. Y. Choi, K.-H. Yoon, H.-S. Kim
  Journal of Clinical Pharmacy and Therapeutics.2017; 42(3): 292.     CrossRef
• Governmental or Social Support of Bariatric Surgery in the Asia-Pacific Region
  Jisun Lim, Young Hye Cho, Hiroshi Yamamoto, Alvin Eng, Tania Markovic, Kyoung Kon Kim
  Journal of Obesity & Metabolic Syndrome.2017; 26(1): 10.     CrossRef
• Application of the 2013 American College of Cardiology/American Heart Association Cholesterol Guideline to the Korean National Health and Nutrition Examination Surveys from 1998 to 2012
  Young Shin Song, Tae Jung Oh, Kyoung Min Kim, Jae Hoon Moon, Sung Hee Choi, Hak Chul Jang, Kyong Soo Park, Soo Lim
  Diabetes & Metabolism Journal.2017; 41(1): 38.     CrossRef
• The differences in the incidence of diabetes mellitus and prediabetes according to the type of HMG‐CoA reductase inhibitors prescribed in Korean patients
  Tong Min Kim, Hyunah Kim, Yoo Jin Jeong, Sun Jung Baik, So Jung Yang, Seung‐Hwan Lee, Jae‐Hyoung Cho, Hyunyong Lee, Hyeon Woo Yim, In Young Choi, Kun‐Ho Yoon, Hun‐Sung Kim
  Pharmacoepidemiology and Drug Safety.2017; 26(10): 1156.     CrossRef
• The Effect and Safety of Dapagliflozin in Patients with Type 2 Diabetes: A Single-Institution Pharmacovigilance Review
  Hyung Woo Lee, Sun Joon Moon, Hee Sim Han, Eun Jeong Shin, Jin Hee Baek, Hyun-Joo Han, Young Min Cho, Kwi Suk Kim
  The Journal of Korean Diabetes.2017; 18(4): 275.     CrossRef
• Optimal glycemic target level for colon cancer patients with diabetes
  Shin Jun Lee, Jae Hyun Kim, Seun Ja Park, So Young Ock, Su Kyoung Kwon, Young Sik Choi, Bu Kyung Kim
  Diabetes Research and Clinical Practice.2017; 124: 66.     CrossRef
• Physician-Directed Diabetes Education without a Medication Change and Associated Patient Outcomes
  Hun-Sung Kim, Hyunah Kim, Hae-Kyung Yang, Eun Young Lee, Yoo Jin Jeong, Tong Min Kim, So Jung Yang, Seo Yeon Baik, Seung-Hwan Lee, Jae Hyoung Cho, In Young Choi, Hyeon Woo Yim, Bong-Yun Cha
  Diabetes & Metabolism Journal.2017; 41(3): 187.     CrossRef
• Does Weight Gain Associated with Thiazolidinedione Use Negatively Affect Cardiometabolic Health?
  Ki Dong Ko, Kyoung Kon Kim, Kyu Rae Lee
  Journal of Obesity & Metabolic Syndrome.2017; 26(2): 102.     CrossRef
• Clinical Characteristics and Outcome of Acute Heart Failure in Korea: Results from the Korean Acute Heart Failure Registry (KorAHF)
  Sang Eun Lee, Hae-Young Lee, Hyun-Jai Cho, Won-Seok Choe, Hokon Kim, Jin Oh Choi, Eun-Seok Jeon, Min-Seok Kim, Jae-Joong Kim, Kyung-Kuk Hwang, Shung Chull Chae, Sang Hong Baek, Seok-Min Kang, Dong-Ju Choi, Byung-Su Yoo, Kye Hun Kim, Hyun-Young Park, Myeon
  Korean Circulation Journal.2017; 47(3): 341.     CrossRef
• Factors that could explain the increasing prevalence of type 2 diabetes among adults in a Canadian province: a critical review and analysis
  Véronique Thibault, Mathieu Bélanger, Emilie LeBlanc, Lise Babin, Stuart Halpine, Beverly Greene, Michelina Mancuso
  Diabetology & Metabolic Syndrome.2016;[Epub]     CrossRef
• Association of Waist-Height Ratio with Diabetes Risk: A 4-Year Longitudinal Retrospective Study
  Yoon Jeong Son, Jihyun Kim, Hye-Jeong Park, Se Eun Park, Cheol-Young Park, Won-Young Lee, Ki-Won Oh, Sung-Woo Park, Eun-Jung Rhee
  Endocrinology and Metabolism.2016; 31(1): 127.     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
• Relative and combined effects of socioeconomic status and diabetes on mortality
  Nam Hoon Kim, Tae Joon Kim, Nan Hee Kim, Kyung Mook Choi, Sei Hyun Baik, Dong Seop Choi, Yousung Park, Sin Gon Kim
  Medicine.2016; 95(30): e4403.     CrossRef
• Recent Advances in Diagnostic Strategies for Diabetic Peripheral Neuropathy
  Jong Chul Won, Tae Sun Park
  Endocrinology and Metabolism.2016; 31(2): 230.     CrossRef
• Patterns of Diagnosis and Risk Factors for Type 2 Diabetes in Women with a History of Gestational Diabetes Mellitus
  Mi Jin Choi, Chae Weon Chung
  Perspectives in Nursing Science.2016; 13(1): 17.     CrossRef
• Mortality and causes of death in a national sample of type 2 diabetic patients in Korea from 2002 to 2013
  Yu Mi Kang, Ye-Jee Kim, Joong-Yeol Park, Woo Je Lee, Chang Hee Jung
  Cardiovascular Diabetology.2016;[Epub]     CrossRef
• Health Performance and Challenges in Korea: a Review of the Global Burden of Disease Study 2013
  Yo Han Lee, Seok-Jun Yoon, Arim Kim, Hyeyoung Seo, Seulki Ko
  Journal of Korean Medical Science.2016; 31(Suppl 2): S114.     CrossRef
• Pharmacological Management of Obesity in Patients with Type 2 Diabetes: An Update
  Eun Ju Lee, Tae Nyun Kim
  The Korean Journal of Obesity.2016; 25(3): 121.     CrossRef
• Current status of managing diabetes mellitus in Korea
  Kyoung Hwa Ha, Dae Jung Kim
  The Korean Journal of Internal Medicine.2016; 31(5): 845.     CrossRef
• Hyperglycemia at presentation is associated with in hospital mortality in non-diabetic patient with organophosphate poisoning
  Jeong Mi Moon, Byeong Jo Chun, Yong Soo Cho
  Clinical Toxicology.2016; 54(3): 252.     CrossRef
• Effectiveness of Web-Based Interventions for Managing Diabetes in Korea
  Jee Young Joo
  CIN: Computers, Informatics, Nursing.2016; 34(12): 587.     CrossRef
• Hypoglycemia and Health Costs
  Yong-ho Lee, Gyuri Kim, Eun Seok Kang
  The Journal of Korean Diabetes.2016; 17(1): 11.     CrossRef
• Letter: Characterization of Patients with Type 2 Diabetes according to Body Mass Index: Korea National Health and Nutrition Examination Survey from 2007 to 2011 (Endocrinol Metab 2015;30:514-21, Dong-Hwa Lee et al.)
  Eun-Hee Cho
  Endocrinology and Metabolism.2016; 31(2): 345.     CrossRef
• Gender-Specific Associations between Socioeconomic Status and Psychological Factors and Metabolic Syndrome in the Korean Population: Findings from the 2013 Korean National Health and Nutrition Examination Survey
  Kyoung Im Cho, Bo Hyun Kim, Hyung Gon Je, Jae Sik Jang, Yong Hyun Park
  BioMed Research International.2016; 2016: 1.     CrossRef
• Need for Diabetes Prevention Study
  Ja Young Jeon, Dae Jung Kim
  The Journal of Korean Diabetes.2015; 16(3): 161.     CrossRef
• Diabetes in Asians
  Eun-Jung Rhee
  Endocrinology and Metabolism.2015; 30(3): 263.     CrossRef
• Epidemiologic Characteristics of Dyslipidemia in Korea
  Kyoung Hwa Ha, Hyuk-Sang Kwon, Dae Jung Kim
  Journal of Lipid and Atherosclerosis.2015; 4(2): 93.     CrossRef

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• Bone Mineral Density Reference of 10-20 year-old Korean Children and Adolescents - Based on Hologic DXA from the Korean National Health and Nutrition Examination Surveys -
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  Journal of Korean Society of Pediatric Endocrinology.2011; 16(2): 92.     CrossRef

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  Journal of Korean Medical Science.2010; 25(9): 1368.     CrossRef

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• Risk factor for pituitary dysfunction in children and adolescents with Rathke's cleft cysts
  Han Hyuk Lim, Sei Won Yang
  Korean Journal of Pediatrics.2010; 53(7): 759.     CrossRef

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  Yoon Jung Chung, Sena Hwang, Jong Ju Jeong, Sun Yong Song, Se Hoon Kim, Yumie Rhee
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  Korean Journal of Pediatrics.2008; 51(7): 742.     CrossRef
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  Journal of Human Genetics.2014; 59(9): 488.     CrossRef
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  Journal of Korean Endocrine Society.2006; 21(3): 239.     CrossRef

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  Journal of Korean Endocrine Society.2007; 22(6): 453.     CrossRef

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