Diabetes & Metabolism Journal

Original Articles

Lifestyle and Behavioral Interventions
Association between the Life’s Essential 8 Health Behaviors Score and Mortality Risk in US Adults with Cardiovascular-Kidney-Metabolic Syndrome Stage 0–3: Junlin Zhang, Limei Yin, Yuping Liu, Xiang Xiao, Ping Shuai; Received April 26, 2025 Accepted June 16, 2025 Published online December 12, 2025; DOI: https://doi.org/10.4093/dmj.2025.0366 [Epub ahead of print]

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The American Heart Association’s novel cardiovascular-kidney-metabolic (CKM) syndrome framework underscores the interconnected pathophysiology of metabolic dysfunction, chronic kidney disease, and cardiovascular disease (CVD). While the Life’s Essential 8 (LE8) has demonstrated strong associations with CVD risk in general populations, its prognostic relevance remains unexplored in individuals stratified by CKM syndrome stages.
Methods
This study analyzed longitudinal data from the nationally representative National Health and Nutrition Examination Survey (2005–2018). The eight components of the LE8 metric—diet quality, physical activity, nicotine exposure, sleep health, body mass index, blood lipid profiles, glycemic status, and blood pressure—were systematically evaluated and scored on a 0–100 scale. A Cox proportional hazards regression model was implemented to assess associations between LE8 scores and all-cause mortality risk. Mortality outcomes were prospectively tracked through December 31, 2019, using linked mortality records from the National Center for Health Statistics.
Results
Among 9,152 participants (mean age 45.08±0.29 years; 48.24% male), baseline CKM staging distributed as follows: stage 0 (12.08%, n=916), stage 1 (25.76%, n=2,162), stage 2 (60.02%, n=5,721), and stage 3 (2.14%, n=353). Unexpectedly, during a median follow-up of 7.92 years, the total LE8 score was not related with all-cause mortality in individuals with CKM stage 2–3 (P>0.05). However, fully adjusted analyses revealed a 22% and 13% decreased all-cause mortality risk per 10-points LE8 health behaviors score increment in CKM 0-1 (hazard ratio [HR], 0.78; 95% confidence interval [CI], 0.68 to 0.88) and CKM 2-3 (HR, 0.87; 95% CI, 0.81 to 0.93), respectively. Restricted cubic spline models confirmed a negative linear dose-response relationship between health behaviors score and all-cause mortality across all CKM stages 0–3.
Conclusion
This national cohort study establishes LE8 health behaviors score as a robust, linearly associated predictor of all-cause mortality in CKM syndrome populations, independent of disease stage severity. These findings advocate for integrating LE8 health behaviors score into routine metabolic-cardiovascular risk stratification protocols, particularly for early intervention in CKM stage 0–3 individuals.

Metabolic Risk/Epidemiology
Association of Remnant Cholesterol Inflammation Index with Cardiovascular Risks and All-Cause Mortality in Individuals with Diabetes or Prediabetes: Qi-Lin Ma, Lei-Lei Du, Jia Peng; Received April 8, 2025 Accepted June 27, 2025 Published online October 2, 2025; DOI: https://doi.org/10.4093/dmj.2025.0305 [Epub ahead of print]

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Background
Remnant cholesterol (RC) and low-grade inflammation are established contributors to cardiovascular disease (CVD) risks in diabetes. However, their combined prognostic impact remains unclear in dysglycemia. We evaluated the remnant cholesterol inflammation index (RCII), integrating RC and high-sensitivity C-reactive protein (hsCRP), for predicting mortality and CVD risks in diabetes/prediabetes.
Methods
This study included 2206 United States adults with diabetes/prediabetes from National Health and Nutrition Examination Survey 2015–2018. RCII was calculated as [RC (mg/dL)×hsCRP (mg/L)]/10. All-cause mortality was tracked via National Death Index until 2019; CVD risk was assessed cross-sectionally. Cox proportional hazard regression determined the hazard ratio (HR) and 95% confidence intervals (CIs) of RCII for all-cause mortality. Logistic regression models estimated the odds ratio (OR) and 95% CIs of RCII for CVD risks.
Results
For CVD risks, Q4 vs. Q1 demonstrated increased odds (OR, 2.32; 95% CI, 1.23 to 4.37), though per-standard deviation (SD) increments were non-significant (OR, 1.15; 95% CI, 0.98 to 1.35; P=0.083). During a median of 38 months follow-up, higher RCII quartiles showed graded associations with all-cause mortality (Q4 vs. Q1: HR, 2.45; 95% CI, 1.08 to 5.58; per 1-SD increase: HR, 1.21; 95% CI, 1.08 to 1.35). Restricted cubic splines confirmed dose-dependent relationships for CVD risks and all-cause mortality (all P=0.005 for overall). Subgroup analyses revealed consistent mortality associations but sex-specific CVD interactions (P=0.047 for interaction).
Conclusion
Our study found the RCII as a biomarker for predicting all-cause mortality and CVD risks in individuals with prediabetes or diabetes, highlighting the synergistic effects of RC and low-grade inflammation on adverse outcomes in this population and may facilitate early identification of individuals at heightened risk for CVD.

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Association of remnant cholesterol inflammation index with future cardiovascular disease risk in patients with cardiovascular-kidney-metabolic syndrome stages 0–3
Nanshan Xie, Lihuan Zeng, Xiangming Hu, Zejia Wu, Weiling Lu, Songyuan Luo, Jianfang Luo
Diabetes Research and Clinical Practice.2026; 233: 113146. CrossRef

Metabolic Risk/Epidemiology
Risk Factors and Survival Outcomes of Immune Checkpoint Inhibitor-Induced Type 1 Diabetes Mellitus: A Retrospective Cohort Study: Sang-hyeok Go, Yun Kyung Cho, Eun Hee Koh; Diabetes Metab J. 2026;50(1):115-126. Published online July 22, 2025; DOI: https://doi.org/10.4093/dmj.2024.0455

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Background
Immune checkpoint inhibitors (ICIs) have transformed the treatment of metastatic solid tumors; however, they induce immune-related adverse events, such as ICI-induced type 1 diabetes mellitus (ICI-T1DM), a rare but serious condition requiring lifelong insulin therapy. We aimed to identify the risk factors and survival outcomes associated with ICI-T1DM to optimize screening and mitigate adverse effects.
Methods
This retrospective cohort study analyzed 6,956 patients treated with ICIs at a tertiary care center between January 1, 2017, and February 28, 2023. ICI-T1DM was classified based on the need for persistent insulin therapy post-ICI and a C-peptide level <1.0 ng/mL. Patient demographics, clinical characteristics, treatment details, and survival outcomes were examined.
Results
ICI-T1DM was identified in 32 patients (0.46%) with a median onset time of 41 weeks. Significant risk factors included pre-existing diabetes (hazard ratio [HR], 2.352; 95% confidence interval [CI], 1.140 to 4.854), combination therapy with anti-programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) and anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitors (HR, 3.666; 95% CI, 1.224 to 10.979), prolonged ICI treatment (≥12 weeks; HR, 4.789; 95% CI, 1.806 to 12.701), and thyroid dysfunction (HR, 4.027; 95% CI, 1.847 to 8.779). ICI-T1DM occurrence and thyroid dysfunction were associated with improved survival (HR, 0.224; 95% CI, 0.093 to 0.539; and HR, 0.616; 95% CI, 0.566 to 0.670).
Conclusion
Patients with pre-existing diabetes, combined anti–PD-1/PD-L1 and anti–CTLA-4 therapy, prolonged ICI treatment (≥12 weeks), and thyroid dysfunction are at high risk of developing ICI-T1DM. The observed survival benefits in patients with ICI-T1DM underscore the importance of aggressive glucose monitoring and patient education for early detection and management.

Citations

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Complete response of sinonasal mucosal melanoma to nivolumab and ipilimumab combination therapy : A case report
Ikuya OMIZO, Kazuma HAYAKAWA, Akihiro ISHIGURO, Kenichiro MAE, Shoko FUKAURA, Kaoruko YOSHIDA, Ryokichi IRISAWA, Kazutoshi HARADA
Skin Cancer.2025; 40(3): 172. CrossRef

Complications
Impact of Remnant Cholesterol on the Risk for End-Stage Renal Disease in Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort Study: Eun Roh, Ji Hye Heo, Han Na Jung, Kyung-Do Han, Jun Goo Kang, Seong Jin Lee, Sung-Hee Ihm; Diabetes Metab J. 2025;49(5):1106-1115. Published online May 21, 2025; DOI: https://doi.org/10.4093/dmj.2024.0406

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Background
Remnant cholesterol (remnant-C) has been linked to the risk of various vascular diseases, but the association between remnant-C and end-stage renal disease (ESRD) in patients with type 2 diabetes mellitus (T2DM) remains unclear.
Methods
Using a nationwide cohort, a total of 2,537,149 patients with T2DM without ESRD, who had participated in the national health screening in 2009, were enrolled and followed up until 2020. Low-density lipoprotein cholesterol (LDL-C) levels were assessed by the Martin-Hopkins method, and remnant-C was calculated as total cholesterol–LDL-C–high-density lipoprotein cholesterol.
Results
During a median follow-up period of 10.3 years, 26,246 patients with T2DM (1.03%) developed ESRD. Participants in the upper quartile of remnant-C had a higher risk of ESRD, with hazard ratios of 1.12 (95% confidence interval [CI], 1.08 to 1.17), 1.20 (95% CI, 1.15 to 1.24), and 1.33 (95% CI, 1.26 to 1.41) in the second, third, and fourth quartile, compared with the lowest quartile, in multivariable-adjusted analyses. The positive association between remnant-C and ESRD remained consistent, irrespective of age, sex, presence of pre-existing comorbidities, and use of anti-dyslipidemic medications. The increased risk of ESRD was more pronounced in high-risk subgroups, including those with hypertension, chronic kidney disease, obesity, and a longer duration of diabetes.
Conclusion
These findings suggest that remnant-C profiles in T2DM have a predictive role for future progression of ESRD, independent of traditional risk factors for renal dysfunction.

Citations

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Impact of Remnant Cholesterol on the Risk for End-Stage Renal Disease in Type 2 Diabetes Mellitus: A Nationwide Population-Based Cohort Study (Diabetes Metab J 2025;49:1106-15)
Jun Hwa Hong
Diabetes & Metabolism Journal.2026; 50(1): 190. CrossRef

Metabolic Risk/Epidemiology
Predictive Models for Type 2 Diabetes Mellitus in Han Chinese with Insights into Cross-Population Applicability and Demographic Specific Risk Factors: Ying-Erh Chen, Djeane Debora Onthoni, Shao-Yuan Chuang, Guo-Hung Li, Yong-Sheng Zhuang, Hung-Yi Chiou, Wayne Huey-Herng Sheu, Ren-Hua Chung; Diabetes Metab J. 2025;49(6):1272-1286. Published online May 21, 2025; DOI: https://doi.org/10.4093/dmj.2024.0319

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Background
The rising global incidence of type 2 diabetes mellitus (T2DM) underscores the need for predictive models that enhance early detection and prevention across diverse populations. This study aimed to identify predictors of incident T2DM within a Han Chinese population, assess their impact across various age and sex demographics, and explore their applicability to European populations.
Methods
Using data from about 65,000 participants in the Taiwan Biobank (TWB), we developed a predictive model, achieving an area under the receiver operating characteristic curve of 90.58%. Key predictors were identified through LASSO regression within the TWB cohort and validated using over 4 million records from Taiwan’s Adult Preventive Healthcare Services (APHS) program and the UK Biobank (UKB).
Results
Our analysis highlighted 13 significant predictors, including established factors like glycosylated hemoglobin (HbA1c) and blood glucose levels, and less conventionally considered variables such as peak expiratory flow. Notable differences in the effects of HbA1c levels and polygenic risk scores between the TWB and UKB cohorts were observed. Additionally, age and sex-specific impacts of these predictors, detailed through APHS data, revealed significant variances; for instance, waist circumference and diagnosed mixed hyperlipidemia showed greater impacts in younger females than in males, while effects remained uniform across male age groups.
Conclusion
Our findings offer novel insights into the diagnosis and management of diabetes for the Han Chinese and potentially for broader East Asian populations, highlighting the importance of ethnic and demographic diversity in developing predictive models for early detection and personalized intervention strategies.

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The Relationship Between High-Density Lipoprotein (HDL) and Glycated Hemoglobin (HbA1C) in Type 2 Diabetes Mellitus Patients: Implications for Cardiovascular Risk
Setyoadi Setyoadi, Dina Dewi Sartika Lestari Ismail, Annisa Wuri Kartika, Dewi Purnama Sari, Angel Dwi Septian, Adelina Stefanie Lallo, Rara Kurniasari
Journal of Rural Community Nursing Practice.2025; 3(2): 234. CrossRef

Review

Lifestyle
Ultra-Processed Foods and the Impact on Cardiometabolic Health: The Role of Diet Quality: Xiaowen Wang, Qi Sun; Diabetes Metab J. 2024;48(6):1047-1055. Published online November 1, 2024; DOI: https://doi.org/10.4093/dmj.2024.0659

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The consumption of ultra-processed foods (UPFs) has surged globally, raising significant public health concerns due to their associations with a range of adverse health outcomes. This review aims to elucidate potential health impacts of UPF intake and underscore the importance of considering diet quality when interpreting study findings. UPF group, as classified by the Nova system based on the extent of industrial processing, contains numerous individual food items with a wide spectrum of nutrient profiles, as well as differential quality as reflected by their potential health effects. The quality of a given food may well misalign with the processing levels so that a UPF food can be nutritious and healthful whereas a non-UPF food can be of low quality and excess intake of which may lead to adverse health consequences. The current review argues that it is critical to focus on the nutritional content and quality of foods and their role within the overall dietary pattern rather than only the level of processing. Further research should dissect health effects of diet quality and food processing, investigate the health impacts of ingredients that render the UPF categorization, understand roles of metabolomics and the gut microbiome in mediating and modulating the health effects of food processing, and consider environmental sustainability in UPF studies. Emphasizing nutrient-dense healthful foods and dietary patterns shall remain the pivotal strategy for promoting overall health and preventing chronic diseases.

Citations

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Nutrition Label Reading and Understanding, Food Advertising Exposure, and Excess Weight Among Brazilian Adults: A Cross-Sectional Study
Laysa Camila Bueno, Luiz Felipe de Paiva Lourenção, Thaiany Goulart de Souza-Silva, Cristina Garcia Lopes Alves, Marcelo Lacerda Rezende, Eric Batista Ferreira, Denismar Alves Nogueira, António Raposo, Zayed D. Alsharari, Mona N. BinMowyna, Sarah Almutair
Nutrients.2026; 18(4): 559. CrossRef
Social determinants of health and type 2 diabetes in Asia
Kyunghun Sung, Seung‐Hwan Lee
Journal of Diabetes Investigation.2025; 16(6): 971. CrossRef
Are all ultra-processed foods bad? A critical review of the NOVA classification system
Jimmy Chun Yu Louie
Proceedings of the Nutrition Society.2025; : 1. CrossRef
Clinician Guidance on the Benefits of Healthy Nutrition and Increased Physical Activity for People With Type 2 Diabetes Following Glucagon-Like Peptide 1 Receptor Agonist Initiation
Pamela Kushner, Carlos Campos, Aaron King, Davida F. Kruger, Javier Morales
Clinical Diabetes.2025; 43(5): 681. CrossRef

Original Articles

Complications
Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning: Chuan Yun, Fangli Tang, Zhenxiu Gao, Wenjun Wang, Fang Bai, Joshua D. Miller, Huanhuan Liu, Yaujiunn Lee, Qingqing Lou; Diabetes Metab J. 2024;48(4):771-779. Published online April 30, 2024; DOI: https://doi.org/10.4093/dmj.2023.0033

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Background
This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.
Methods
The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance.
Results
The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05).
Conclusion
The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Citations

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Multi-feature integrated machine learning prediction model for early nephropathy in elderly living with type 2 diabetes mellitus
Tingting Fang, Yuanyuan Yang, Feng Zhuo, Xinran Xie, Jialun Song, Linghua Kong
Frontiers in Endocrinology.2026;[Epub] CrossRef
DiffLSTM-MTE: A Hybrid LSTM-Diffusion Framework for Virtual iEEG Reconstruction From MEG
Xiangyu Xue, Liankun Ren, Hongyu Zhou, Anqi Dai, Di Wang, Huaqiang Zhang
IEEE Access.2026; 14: 27444. CrossRef
Trends and analysis of risk factor differences in the global burden of chronic kidney disease due to type 2 diabetes from 1990 to 2021: A population‐based study
Yifei Wang, Ting Lin, Jiale Lu, Wenfang He, Hongbo Chen, Tiancai Wen, Juan Jin, Qiang He
Diabetes, Obesity and Metabolism.2025; 27(4): 1902. CrossRef
Artificial Intelligence for Diabetes Complication Prediction: A Systematic Review of Current Applications and Future Directions
Francesca Pescol, Pietro Bosoni, Stefania Ghilotti, Pasquale De Cata, Lucia Sacchi, Riccardo Bellazzi
Journal of Diabetes Science and Technology.2025;[Epub] CrossRef

Metabolic Risk/Epidemiology
Biologically Informed Polygenic Scores for Brain Insulin Receptor Network Are Associated with Cardiometabolic Risk Markers and Diabetes in Women: Jannica S. Selenius, Patricia P. Silveira, Mikaela von Bonsdorff, Jari Lahti, Hannu Koistinen, Riitta Koistinen, Markku Seppälä, Johan G. Eriksson, Niko S. Wasenius; Diabetes Metab J. 2024;48(5):960-970. Published online March 25, 2024; DOI: https://doi.org/10.4093/dmj.2023.0039

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Background
To investigate associations between variations in the co-expression-based brain insulin receptor polygenic score and cardiometabolic risk factors and diabetes mellitus.
Methods
This cross-sectional study included 1,573 participants from the Helsinki Birth Cohort Study. Biologically informed expression-based polygenic risk scores for the insulin receptor gene network were calculated for the hippocampal (hePRS-IR) and the mesocorticolimbic (mePRS-IR) regions. Cardiometabolic markers included body composition, waist circumference, circulating lipids, insulin-like growth factor 1 (IGF-1), and insulin-like growth factor-binding protein 1 and 3 (IGFBP-1 and -3). Glucose and insulin levels were measured during a standardized 2-hour 75 g oral glucose tolerance test and impaired glucose regulation status was defined by the World Health Organization 2019 criteria. Analyzes were adjusted for population stratification, age, smoking, alcohol consumption, socioeconomic status, chronic diseases, birth weight, and leisure-time physical activity.
Results
Multinomial logistic regression indicated that one standard deviation increase in hePRS-IR was associated with increased risk of diabetes mellitus in all participants (adjusted relative risk ratio, 1.17; 95% confidence interval, 1.01 to 1.35). In women, higher hePRS-IR was associated with greater waist circumference and higher body fat percentage, levels of glucose, insulin, total cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein B, insulin, and IGFBP-1 (all P≤0.02). The mePRS-IR was associated with decreased IGF-1 level in women (P=0.02). No associations were detected in men and studied outcomes.
Conclusion
hePRS-IR is associated with sex-specific differences in cardiometabolic risk factor profiles including impaired glucose regulation, abnormal metabolic markers, and unfavorable body composition in women.

Citations

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A mesocorticolimbic insulin receptor gene co-expression network moderates the association between early life adversity and food approach eating behaviour style in childhood
Angela Marcela Jaramillo-Ospina, Roberta Dalle Molle, Sachin Patel, Shona Kelly, Irina Pokhvisneva, Carolina de Weerth, Patrícia Pelufo Silveira
Appetite.2025; 204: 107762. CrossRef
Early adversity and the comorbidity between metabolic disease and psychopathology
Ameyalli Gómez‐Ilescas, Patricia Pelufo Silveira
The Journal of Physiology.2025;[Epub] CrossRef
Brain insulin receptor gene network shapes risk for metabolic disease after early-life stress in women
Angela Marcela Jaramillo-Ospina, Guillaume Elgbeili, Sachin Patel, Irina Pokhvisneva, Patricia Pelufo Silveira
Communications Biology.2025;[Epub] CrossRef

Complications
The Risk of Shoulder Adhesive Capsulitis in Individuals with Prediabetes and Type 2 Diabetes Mellitus: A Longitudinal Nationwide Population-Based Study: Jong-Ho Kim, Bong-Seoung Kim, Kyung-do Han, Hyuk-Sang Kwon; Diabetes Metab J. 2023;47(6):869-878. Published online August 23, 2023; DOI: https://doi.org/10.4093/dmj.2022.0275

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Background
This study aimed to investigate the association between type 2 diabetes mellitus (T2DM) and shoulder adhesive capsulitis (AC) using a large-scale, nationwide, population-based cohort in the Republic of Korea.
Methods
A total of 3,471,745 subjects aged over 20 years who underwent a National Health Insurance Service medical checkup between 2009 and 2010 were included in this study, and followed from the date of their medical checkup to the end of 2018. Subjects were classified into the following four groups based on the presence of dysglycemia and history of diabetes medication: normal, prediabetes, newly diagnosed T2DM (new-T2DM), and T2DM (claim history for antidiabetic medication). The endpoint was new-onset AC during follow-up. The incidence rates (IRs) in 1,000 person-years and hazard ratios (HRs) of AC for each group were analyzed using Cox proportional hazard regression models.
Results
The IRs of AC were 9.453 (normal), 11.912 (prediabetes), 14.933 (new-T2DM), and 24.3761 (T2DM). The adjusted HRs of AC in the prediabetes, new-T2DM, and T2DM groups were 1.084 (95% confidence interval [CI], 1.075 to 1.094), 1.312 (95% CI, 1.287 to 1.337), and 1.473 (95% CI, 1.452 to 1.494) compared to the normal group, respectively. This secular trend of the HRs of AC according to T2DM status was statistically significant (P<0.0001).
Conclusion
This large-scale, longitudinal, nationwide, population-based cohort study of 3,471,745 subjects confirmed that the risk of AC increases in prediabetic subjects and is associated with T2DM status.

Citations

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The Association Between Type 2 Diabetes Mellitus and Frozen Shoulder: Expert Insights on Developing a Screening Tool
Anirban Majumdar, Voleti S. Nagesh, Rakesh K. Sahay, Nilanjan Sengupta, Debmalya Sanyal, Griddaluru V. Chanukya, Rana Bhattacharjee, Amit Goel, Raman Boddula, Sudhakar R. Pendyala, Amitabh Sur
Indian Journal of Endocrinology and Metabolism.2026; 30(1): 20. CrossRef
Higher body mass index increases the risk of shoulder adhesive capsulitis in young adults: a nationwide cohort study
Jong-Ho Kim, Jae-Yoon Baek, Kyung-Do Han, Bong-Seoung Kim, Hyuk-Sang Kwon
Journal of Shoulder and Elbow Surgery.2025; 34(1): 26. CrossRef
Classification of shoulder diseases in older adult patients: a narrative review
Hyo-Jin Lee, Jong-Ho Kim
The Ewha Medical Journal.2025;[Epub] CrossRef
Type 2 diabetes, metabolic health, and the development of frozen shoulder: a cohort study in UK electronic health records
Brett P. Dyer, Claire Burton, Trishna Rathod-Mistry, Miliça Blagojevic-Bucknall, Danielle A. van der Windt
BMC Musculoskeletal Disorders.2025;[Epub] CrossRef
Clinical Practice Guidelines for Diagnosis and Non-Surgical Treatment of Primary Frozen Shoulder
Byung Chan Lee, Beom Suk Kim, Byeong-Ju Lee, Chang-Won Moon, Chul-Hyun Park, Dong Hwan Kim, Dong Hwan Yun, Donghwi Park, Doo Young Kim, Du Hwan Kim, Gi-Wook Kim, Hyun Jung Kim, Il-Young Jung, In Jong Kim, Jae Hyeon Park, Jae-Hyun Lee, Jaeki Ahn, Jae-Young
Annals of Rehabilitation Medicine.2025; 49(3): 113. CrossRef
Clinical Practice Guidelines for Diagnosis and Non-Surgical Treatment of Primary Frozen Shoulder
Byung Chan Lee, Gi-Wook Kim, Keewon Kim, Nackhwan Kim, Dong Hwan Kim, Doo Young Kim, Du Hwan Kim, Beom Suk Kim, Seong Hun Kim, In Jong Kim, Hyun Jung Kim, Yoonju Na, Kyung Eun Nam, Sung Gyu Moon, Chang-Won Moon, Kyunghoon Min, Donghwi Park, Myung Woo Park
Clinical Pain.2025; 24(1): 1. CrossRef
Association between diabetes mellitus and adhesive capsulitis of shoulder: A 2-sample Mendelian randomization study
Wenqiang Li, Jing Lou, Weizhong Huangfu, Dezhi Han
Medicine.2025; 104(35): e44119. CrossRef
Clinical efficacy of manipulation under brachial plexus block anesthesia for primary adhesive capsulitis of shoulder: a retrospective cohort study
Haiyan Zhou, Liming Cheng
Frontiers in Surgery.2025;[Epub] CrossRef
Impacts of preoperative anxiety and depression on pain and range of motion after arthroscopic frozen shoulder release: a cohort study
Yahia Haroun, Ahmed Saeed Younis, Wessam Fakhery Ebied, Mohamed Amr Hemida, Ahmed H. Khater
International Orthopaedics.2024; 48(8): 2113. CrossRef
Subdiaphragmatic phrenic nerve supply: A systematic review
María Pérez-Montalbán, Encarna García-Domínguez, Ángel Oliva-Pascual-Vaca
Annals of Anatomy - Anatomischer Anzeiger.2024; 254: 152269. CrossRef
Effects of moderate physical activity on diabetic adhesive capsulitis: a randomized clinical trial
Raheela Kanwal Sheikh, Amna Toseef, Aadil Omer, Anam Aftab, Muhammad Manan Haider Khan, Saeed Bin Ayaz, Omar Althomli, Aisha Razzaq, Samra Khokhar, Nazia Jabbar, Waqar Ahmed Awan
PeerJ.2024; 12: e18030. CrossRef
A Narrative Review of Adhesive Capsulitis with Diabetes
Mu-Her Chen, Wen-Shiang Chen
Journal of Clinical Medicine.2024; 13(19): 5696. CrossRef
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Orthopaedic Surgery.2024; 16(12): 2942. CrossRef
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Fabio Vita, Danilo Donati, Roberto Tedeschi, Marco Miceli, Paolo Spinnato, Flavio Origlio, Enrico Guerra, Marco Cavallo, Salvatore Massimo Stella, Luigi Tarallo, Giuseppe Porcellini, Stefano Galletti, Cesare Faldini
European Journal of Orthopaedic Surgery & Traumatology.2024; 34(8): 4113. CrossRef

Cardiovascular Risk/Epidemiology
Comparison of on-Statin Lipid and Lipoprotein Levels for the Prediction of First Cardiovascular Event in Type 2 Diabetes Mellitus: Ji Yoon Kim, Jimi Choi, Sin Gon Kim, Nam Hoon Kim; Diabetes Metab J. 2023;47(6):837-845. Published online August 23, 2023; DOI: https://doi.org/10.4093/dmj.2022.0217

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Background
A substantial cardiovascular disease risk remains even after optimal statin therapy. Comparative predictiveness of major lipid and lipoprotein parameters for cardiovascular events in patients with type 2 diabetes mellitus (T2DM) who are treated with statins is not well documented.
Methods
From the Korean Nationwide Cohort, 11,900 patients with T2DM (≥40 years of age) without a history of cardiovascular disease and receiving moderate- or high-intensity statins were included. The primary outcome was the first occurrence of major adverse cardiovascular events (MACE) including ischemic heart disease, ischemic stroke, and cardiovascular death. The risk of MACE was estimated according to on-statin levels of low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), highdensity lipoprotein cholesterol (HDL-C), and non-HDL-C.
Results
MACE occurred in 712 patients during a median follow-up period of 37.9 months (interquartile range, 21.7 to 54.9). Among patients achieving LDL-C levels less than 100 mg/dL, the hazard ratios for MACE per 1-standard deviation change in ontreatment values were 1.25 (95% confidence interval [CI], 1.07 to 1.47) for LDL-C, 1.31 (95% CI, 1.09 to 1.57) for non-HDL-C, 1.05 (95% CI, 0.91 to 1.21) for TG, and 1.16 (95% CI, 0.98 to 1.37) for HDL-C, after adjusting for potential confounders and lipid parameters mutually. The predictive ability of on-statin LDL-C and non-HDL-C for MACE was prominent in patients at high cardiovascular risk or those with LDL-C ≥70 mg/dL.
Conclusion
On-statin LDL-C and non-HDL-C levels are better predictors of the first cardiovascular event than TG or HDL-C in patients with T2DM.

Citations

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Metabolic Risk/Epidemiology
The Risk of Type 2 Diabetes Mellitus according to Changes in Obesity Status in Late Middle-Aged Adults: A Nationwide Cohort Study of Korea: Joon Ho Moon, Yeonhoon Jang, Tae Jung Oh, Se Young Jung; Diabetes Metab J. 2023;47(4):514-522. Published online April 25, 2023; DOI: https://doi.org/10.4093/dmj.2022.0159

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Background
Although obesity is a well-known risk factor of type 2 diabetes mellitus (T2DM), there is scant data on discriminating the contribution of previous obesity and recent weight gain on developing T2DM.
Methods
We analyzed the Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 where Korean residents underwent biennial health checkups. Participants were classified into four groups according to their obesity status (body mass index [BMI] ≥25 kg/m²) before and after turning 50 years old: maintaining normal (MN), becoming obese (BO), becoming normal (BN), and maintaining obese (MO). Cox proportional hazards regression model was used to estimate the risk of T2DM factoring in the covariates age, sex, BMI, presence of impaired fasting glucose or hypertension, family history of diabetes, and smoking status.
Results
A total of 118,438 participants (mean age, 52.5±1.1 years; men, 45.2%) were prospectively evaluated for incident T2DM. A total of 7,339 (6.2%) participants were diagnosed with T2DM during a follow-up period of 4.8±2.6 years. Incidence rates of T2DM per 1,000 person-year were 9.20 in MN, 14.81 in BO, 14.42 in BN, 21.38 in MO. After factoring in covariates, participants in the groups BN (adjusted hazard ratio [aHR], 1.15; 95% confidence interval [CI], 1.04 to 1.27) and MO (aHR, 1.14; 95% CI, 1.06 to 1.24) were at increased risk of developing T2DM compared to MN, whereas BO (hazard ratio, 1.06; 95% CI, 0.96 to 1.17) was not.
Conclusion
Having been obese before 50 years old increased the risk of developing T2DM in the future, but becoming obese after 50 did not. Therefore, it is important to maintain normal weight from early adulthood to prevent future metabolic perturbations.

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Complications
Association of Body Mass Index and Fracture Risk Varied by Affected Bones in Patients with Diabetes: A Nationwide Cohort Study: Se-Won Lee, Kyungdo Han, Hyuk-Sang Kwon; Diabetes Metab J. 2023;47(2):242-254. Published online January 19, 2023; DOI: https://doi.org/10.4093/dmj.2022.0001

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Background
Body mass index (BMI) is a risk factor for the type 2 diabetes (T2DM), and T2DM accompanies various complications, such as fractures. We investigated the effects of BMI and T2DM on fracture risk and analyzed whether the association varied with fracture locations.
Methods
This study is a nationwide population-based cohort study that included all people with T2DM (n=2,746,078) who received the National Screening Program during 2009–2012. According to the anatomical location of the fracture, the incidence rate and hazard ratio (HR) were analyzed by dividing it into four categories: vertebra, hip, limbs, and total fracture.
Results
The total fracture had higher HR in the underweight group (HR, 1.268; 95% CI, 1.228 to 1.309) and lower HR in the obese group (HR, 0.891; 95% CI, 0.882 to 0.901) and the morbidly obese group (HR, 0.873; 95% CI, 0.857 to 0.89), compared to reference (normal BMI group). Similar trends were observed for HR of vertebra fracture. The risk of hip fracture was most prominent, the risk of hip fracture increased in the underweight group (HR, 1.896; 95% CI, 1.178 to 2.021) and decreased in the obesity (HR, 0.643; 95% CI, 0.624 to 0.663) and morbidly obesity group (HR, 0.627; 95% CI, 0.591 to 0.665). Lastly, fracture risk was least affected by BMI for limbs.
Conclusion
In T2DM patients, underweight tends to increase fracture risk, and overweight tends to lower fracture risk, but association between BMI and fracture risk varied depending on the affected bone lesions.

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Review

Guideline/Fact Sheet
Screening for Prediabetes and Diabetes in Korean Nonpregnant Adults: A Position Statement of the Korean Diabetes Association, 2022: Kyung Ae Lee, Dae Jung Kim, Kyungdo Han, Suk Chon, Min Kyong Moon, on Behalf of the Committee of Clinical Practice Guideline of Korean Diabetes Association; Diabetes Metab J. 2022;46(6):819-826. Published online November 24, 2022; DOI: https://doi.org/10.4093/dmj.2022.0364

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Diabetes screening serves to identify individuals at high-risk for diabetes who have not yet developed symptoms and to diagnose diabetes at an early stage. Globally, the prevalence of diabetes is rapidly increasing. Furthermore, obesity and/or abdominal obesity, which are major risk factors for type 2 diabetes mellitus (T2DM), are progressively increasing, particularly among young adults. Many patients with T2DM are asymptomatic and can accompany various complications at the time of diagnosis, as well as chronic complications develop as the duration of diabetes increases. Thus, proper screening and early diagnosis are essential for diabetes care. Based on reports on the changing epidemiology of diabetes and obesity in Korea, as well as growing evidence from new national cohort studies on diabetes screening, the Korean Diabetes Association has updated its clinical practice recommendations regarding T2DM screening. Diabetes screening is now recommended in adults aged ≥35 years regardless of the presence of risk factors, and in all adults (aged ≥19) with any of the risk factors. Abdominal obesity based on waist circumference (men ≥90 cm, women ≥85 cm) was added to the list of risk factors.

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Original Articles

Guideline/Fact Sheet
Diabetes Fact Sheet in Korea 2021: Jae Hyun Bae, Kyung-Do Han, Seung-Hyun Ko, Ye Seul Yang, Jong Han Choi, Kyung Mook Choi, Hyuk-Sang Kwon, Kyu Chang Won, on Behalf of the Committee of Media-Public Relation of the Korean Diabetes Association; Diabetes Metab J. 2022;46(3):417-426. Published online May 25, 2022; DOI: https://doi.org/10.4093/dmj.2022.0106

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Background
This study aimed to investigate the prevalence and management of diabetes mellitus, risk-factor control, and comorbidities among Korean adults.
Methods
We conducted a cross-sectional analysis of data from the Korea National Health and Nutrition Examination Survey to assess the prevalence, treatment, risk factors, comorbidities, and self-management behaviors of diabetes mellitus from 2019 to 2020. We also analyzed data from the Korean National Health Insurance Service to evaluate the use of antidiabetic medications in people with diabetes mellitus from 2002 through 2018.
Results
Among Korean adults aged 30 years or older, the estimated prevalence of diabetes mellitus was 16.7% in 2020. From 2019 through 2020, 65.8% of adults with diabetes mellitus were aware of the disease and treated with antidiabetic medications. The percentage of adults with diabetes mellitus who achieved glycosylated hemoglobin (HbA1c) <6.5% was 24.5% despite the increased use of new antidiabetic medications. We found that adults with diabetes mellitus who achieved all three goals of HbA1c <6.5%, blood pressure (BP) <140/85 mm Hg, and low-density lipoprotein cholesterol <100 mg/dL were 9.7%. The percentage of self-management behaviors was lower in men than women. Excess energy intake was observed in 16.7% of adults with diabetes mellitus.
Conclusion
The prevalence of diabetes mellitus among Korean adults remained high. Only 9.7% of adults with diabetes mellitus achieved all glycemic, BP, and lipid controls from 2019 to 2020. Continuous evaluation of national diabetes statistics and a national effort to increase awareness of diabetes mellitus and improve comprehensive diabetes care are needed.

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Teodora-Gabriela Alexescu, Antonia Nechita, Paula Alexander, Mirela-Georgiana Perné, Mircea-Vasile Milaciu, George Ciulei, Ioana Para, Vasile Negrean, Ana-Florica Chiș, Doina-Adina Todea, Dan Vălean, Simina-Felicia Țărmure, Olga-Hilda Orășan
Journal of Mind and Medical Sciences.2025; 12(1): 14. CrossRef
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Results in Chemistry.2025; 15: 102237. CrossRef
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The Journal of Internal Korean Medicine.2025; 46(1): 1. CrossRef
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Sustainable Chemistry and Pharmacy.2025; 45: 102039. CrossRef
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Korean Circulation Journal.2025; 55(8): 736. CrossRef
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Korean Journal of Family Practice.2025; 15(2): 96. CrossRef
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Calcified Tissue International.2025;[Epub] CrossRef
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Diabetes, Obesity and Metabolism.2025; 27(9): 5019. CrossRef
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Scientific Reports.2025;[Epub] CrossRef
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Scientific Reports.2025;[Epub] CrossRef
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Endocrinology and Metabolism.2025; 40(3): 421. CrossRef
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Diabetes & Metabolism Journal.2025; 49(4): 582. CrossRef
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Djoko Priyono, Sanghee Kim
Science Progress.2025;[Epub] CrossRef
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Bin Hong, Hyesung Lee, Jae Hyun Bae, Young Min Cho, Ju-Young Shin
The Journal of Allergy and Clinical Immunology: In Practice.2025; 13(8): 2025. CrossRef
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Woo-Ri Lee, Sungyoun Chun, Noorhee Son, Yehrhee Son, Ki-Bong Yoo
BMC Public Health.2025;[Epub] CrossRef
Transfer learning prediction of type 2 diabetes with unpaired clinical and genetic data
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Scientific Reports.2025;[Epub] CrossRef
Efficacy and safety of lobeglitazone added to metformin and sitagliptin combination therapy in patients with type 2 diabetes: A 52‐week, multicentre, randomized, placebo‐controlled, phase III clinical trial
Eun‐Gyoung Hong, Kyung‐Wan Min, SungWan Chun, Choon Hee Chung, Seungjoon Oh, Chang Beom Lee, Dong‐Jun Kim, Hye Soon Kim, Ji Oh Mok, Tae Seo Sohn, Jeong Hyun Park, Sung Hee Choi, Sungrae Kim, Sang Soo Kim, Kyu Yeon Hur, Chong Hwa Kim, Young Min Cho, Byung‐
Diabetes, Obesity and Metabolism.2025; 27(10): 5727. CrossRef
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Soomin Lee, Younghwan Choi, Yeon Soo Kim
Journal of Diabetes & Metabolic Disorders.2025;[Epub] CrossRef
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Cancer Research and Treatment.2025; 57(4): 1178. CrossRef
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Diabetes Research and Clinical Practice.2025; 227: 112401. CrossRef
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Hwa Young Kim, Eunjeong Ji, Jaehyun Kim
Journal of Korean Medical Science.2025;[Epub] CrossRef
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PLOS One.2025; 20(8): e0329003. CrossRef
Physical activity for prevention of cardiovascular disease: consensus statement of Korean Society of Cardio-cerebrovascular Disease Prevention
Ye Seul Yang, Eu Jeong Ku, Seung-Hyun Ko, Eun-Jung Rhee, Sang-Hyun Ihm, Sung Hee Choi, Won-Young Lee
The Korean Journal of Internal Medicine.2025; 40(5): 696. CrossRef
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Journal of Internal Medicine.2025; 298(4): 336. CrossRef
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Cardiovascular Diabetology – Endocrinology Reports.2025;[Epub] CrossRef
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Korean Journal of Adult Nursing.2025; 37(3): 287. CrossRef
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Drug Design, Development and Therapy.2025; Volume 19: 7825. CrossRef
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Nahyun Cho, Chul-woo Ahn, Hyungsun Jun, Hyun-jong Jung, Dasol Park, Jungtae Leem
The Journal of Internal Korean Medicine.2025; 46(3): 511. CrossRef
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Ae-Seul Lee, Seong Woo Choi, So Yeon Ryu
Journal of Health Informatics and Statistics.2025; 50(3): 249. CrossRef
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Diabetes, Obesity and Metabolism.2025; 27(12): 7110. CrossRef
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Endocrinology and Metabolism.2025; 40(5): 727. CrossRef
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Ye Seul Yang, Eu Jeong Ku, Seung-Hyun Ko, Eun-Jung Rhee, Sang-Hyun Ihm, Sung Hee Choi, Won-Young Lee
Cardiovascular Prevention and Pharmacotherapy.2025; 7(4): 120. CrossRef
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Seohyun Kim, Mira Kang, Dohyun Park, Gyuri Kim, Jae Hyeon Kim
BMC Public Health.2025;[Epub] CrossRef
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Jung-Yeon Choi, Cheol-Ho Kim, Kwang-il Kim
Cardiovascular Prevention and Pharmacotherapy.2025; 7(4): 135. CrossRef
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Da Woon Kim, Eun Young Seong, Sang Heon Song
Acta Diabetologica.2025;[Epub] CrossRef
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Hyeon-Jin Yu, Doyoun Hong, Kyuho Kim, Ji Hye Heo, Dong-Hyeok Cho, Yoshitaka Hashimoto, Jae-Seung Yun
Diabetes & Metabolism Journal.2025; 49(6): 1178. CrossRef
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Jeongmin Lee, Kwang Joon Kim, Yang Sun Park, Yong-ho Lee, Kyeong Hye Park, Hee-Won Jung, Bong-Soo Cha, Hun-Sung Kim, Chang Oh Kim
The Korean Journal of Internal Medicine.2025; 40(6): 1017. CrossRef
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Ha Yeong Choi, Yeo Jin Kim, Dae-Soon Son, Moo Eob Ahn, Sang-Kyu Lee
Scientific Reports.2025;[Epub] CrossRef
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Scientific Reports.2025;[Epub] CrossRef
Trends in Prevalence of Obesity and Related Cardiometabolic and Renal Complications in Korea: A Nationwide Study 2007 to 2022
Eugene Han, Byung-Wan Lee, Eun Seok Kang, Bong-Soo Cha, Jangho Lee, Yong-ho Lee
Journal of Obesity & Metabolic Syndrome.2025; 34(4): 414. CrossRef
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Hyunsoo Yoo, Yoon-Seok Choi, Young-Mo Yang
Diabetology & Metabolic Syndrome.2025;[Epub] CrossRef
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Eun-Kyeong Yun, Jae-Yong Shim, Sang-Jun Shin, Hee-Taik Kang
Nutrition, Metabolism and Cardiovascular Diseases.2025; : 104527. CrossRef
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Endocrinology and Metabolism.2025; 40(6): 991. CrossRef
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Diabetes, Obesity and Metabolism.2024; 26(2): 567. CrossRef
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Kye-Yeung Park, Hwan-Sik Hwang, Kyungdo Han, Hoon-Ki Park
American Journal of Preventive Medicine.2024; 66(4): 717. CrossRef
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I. Hwang, S.Y. Kim, Y.Y. Kim, J.H. Park
Public Health.2024; 226: 173. CrossRef
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Ji In Park, Sang-Wook Kim, Il Sung Nam-Goong, Kee-Ho Song, Ji Hee Yu, Ji Yun Jeong, Eun-Hee Cho
Yonsei Medical Journal.2024; 65(1): 42. CrossRef
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Yeong Jun Ju, Woorim Kim, Kyujin Chang, Tae Hoon Lee, Soon Young Lee
Preventive Medicine.2024; 178: 107793. CrossRef
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Tae Kyung Yoo, Kyung‐Do Han, Eun‐Jung Rhee, Won‐Young Lee
Journal of Cachexia, Sarcopenia and Muscle.2024; 15(2): 671. CrossRef
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BMC Gastroenterology.2024;[Epub] CrossRef
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Byeong Yun Ahn, Bokyung Kim, Sanghyun Park, Sang Gyun Kim, Kyungdo Han, Soo‐Jeong Cho
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Byung-Wan Lee, Young Min Cho, Sin Gon Kim, Seung-Hyun Ko, Soo Lim, Amine Dahaoui, Jin Sook Jeong, Hyo Jin Lim, Jae Myung Yu
Diabetes Therapy.2024; 15(2): 547. CrossRef
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Weiwei Dong, Xiaobai Liu, Lu Ma, Zhiyong Yang, Chunyan Ma
Food & Function.2024; 15(3): 1575. CrossRef
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Min-Kyung Lee, Kyungdo Han, Bongsung Kim, Jong-Dai Kim, Moon Jung Kim, Byungpyo Kim, Jung Heo, Jiyeon Ahn, Seo-Young Sohn, Jae-Hyuk Lee
Diabetes Research and Clinical Practice.2024; 208: 111109. CrossRef
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Hack-Lyoung Kim
Cardiovascular Prevention and Pharmacotherapy.2024; 6(1): 17. CrossRef
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Kidney Research and Clinical Practice.2024; 43(1): 20. CrossRef
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Jung Lim Lee, Youngji Kim
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Seo Yeon Baik, Kyoung Min Kim, Hakyoung Park, Jiwon Shinn, Hun-Sung Kim
Cardiovascular Prevention and Pharmacotherapy.2024; 6(1): 33. CrossRef
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Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
BMJ.2024; 384: e076388. CrossRef
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Hee Joo Yang, Mi Young Lee, Jeong Hyeon Lee, Chang Jin Jung, Woo Jin Lee, Chong Hyun Won, Mi Woo Lee, Joon Min Jung, Sung Eun Chang
Scientific Reports.2024;[Epub] CrossRef
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Thi Minh Thu Khong, Thi Tra Bui, Hee-Yeon Kang, Jinhee Lee, Eunjung Park, Jin-Kyoung Oh
BMJ Open Diabetes Research & Care.2024; 12(1): e003696. CrossRef
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Mihwan Kim, Haejung Lee, Gaeun Park, Ah Reum Khang
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Journal of Personalized Medicine.2024; 14(3): 280. CrossRef
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Na Yeon Kim, Haekyung Lee, Sehee Kim, Ye-Jee Kim, Hyunsuk Lee, Junhyeong Lee, Soo Heon Kwak, Seunggeun Lee
Scientific Reports.2024;[Epub] CrossRef
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So Yon Jun, Sooyoung Cho, Min Jung Kim, Ji Won Park, Seung‐Bum Ryoo, Seung Yong Jeong, Kyu Joo Park, Aesun Shin
Cancer Medicine.2024;[Epub] CrossRef
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Diabetes & Metabolism Journal.2024; 48(2): 279. CrossRef
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Min Jin Lee, Ji Hyun Bae, Ah Reum Khang, Dongwon Yi, Mi Sook Yun, Yang Ho Kang
Diabetes Research and Clinical Practice.2024; 210: 111640. CrossRef
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Eun-Gyoung Hong, Kyung-Wan Min, Jung Soo Lim, Kyu-Jeung Ahn, Chul Woo Ahn, Jae-Myung Yu, Hye Soon Kim, Hyun Jin Kim, Won Kim, Dong Han Kim, Hak Chul Jang
Advances in Therapy.2024; 41(5): 1967. CrossRef
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Kyung Hoon Kim, Hyung Woo Kim, Yong Hyun Kim, Yeonhee Park, Sung Soo Jung, Jin Woo Kim, Jee Youn Oh, Heayon Lee, Sung Kyoung Kim, Sun‐Hyung Kim, Jiwon Lyu, Yousang Ko, Sun Jung Kwon, Yun‐Jeong Jeong, Do Jin Kim, Hyeon‐Kyoung Koo, Yangjin Jegal, Sun Young
Respirology.2024; 29(7): 624. CrossRef
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Jin-Ah Seok, Yeon-Kyung Lee
Nutrition Research and Practice.2024; 18(2): 239. CrossRef
Management of Early-Onset Type 2 Diabetes
Jin Hwa Kim
The Journal of Korean Diabetes.2024; 25(1): 4. CrossRef
Efficacy and tolerability of initial triple combination therapy with metformin, dapagliflozin and saxagliptin compared with stepwise add‐on therapy in drug‐naïve patients with type 2 diabetes (TRIPLE‐AXEL study): A multicentre, randomized, 104‐week, open‐
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Diabetes, Obesity and Metabolism.2024; 26(9): 3642. CrossRef
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Kang-Su Shin, Min-Seung Park, Mi Yeon Lee, Eun Hye Cho, Hee-Yeon Woo, Hyosoon Park, Min-Jung Kwon
Scandinavian Journal of Clinical and Laboratory Investigation.2024; 84(3): 168. CrossRef
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Eun Yeong Ha, Il Rae Park, Seung Min Chung, Young Nam Roh, Chul Hyun Park, Tae-Gon Kim, Woong Kim, Jun Sung Moon
Journal of Clinical Medicine.2024; 13(8): 2311. CrossRef
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Incheol Seo, Jin-Mo Park
Neurological Sciences.2024; 45(9): 4573. CrossRef
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Diabetes, Obesity and Metabolism.2024; 26(7): 2567. CrossRef
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Endocrinology and Metabolism.2024; 39(2): 344. CrossRef
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Wonseok Jeong, Seungju Kim
Epidemiology and Health.2024; 46: e2024029. CrossRef
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International Urology and Nephrology.2024; 56(10): 3307. CrossRef
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Jung-Hwan Kim, Yaeji Lee, Chung-Mo Nam, Yu-Jin Kwon, Ji-Won Lee
Endocrine.2024; 86(2): 528. CrossRef
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Yebin Park, Kyungdo Han
Korean Journal of Family Practice.2024; 14(2): 105. CrossRef
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Endocrinology and Metabolism.2024; 39(3): 479. CrossRef
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Journal of Korean Medical Science.2024;[Epub] CrossRef
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Frontiers in Endocrinology.2024;[Epub] CrossRef
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Biomedicines.2024; 12(7): 1572. CrossRef
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Diabetes & Metabolism Journal.2024; 48(4): 518. CrossRef
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Yu-Na Kim, Sung Won Lee, Sangwook Park
Biomedical Science Letters.2024; 30(2): 65. CrossRef
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Eun‐Jung Shim, Sang Jin Park, Gyu Hyeong Im, Ruth A. Hackett, Paola Zaninotto, Andrew Steptoe
British Journal of Health Psychology.2024; 29(4): 1000. CrossRef
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Diabetes & Metabolism Journal.2024; 48(4): 790. CrossRef
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Youngji Han, Yuri Jeong, Jin Hyup Lee, Seung Pil Pack
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Drug/Regimen
Comparison of Serum Ketone Levels and Cardiometabolic Efficacy of Dapagliflozin versus Sitagliptin among Insulin-Treated Chinese Patients with Type 2 Diabetes Mellitus: Chi-Ho Lee, Mei-Zhen Wu, David Tak-Wai Lui, Darren Shing-Hei Chan, Carol Ho-Yi Fong, Sammy Wing-Ming Shiu, Ying Wong, Alan Chun-Hong Lee, Joanne King-Yan Lam, Yu-Cho Woo, Karen Siu-Ling Lam, Kelvin Kai-Hang Yiu, Kathryn Choon-Beng Tan; Diabetes Metab J. 2022;46(6):843-854. Published online April 28, 2022; DOI: https://doi.org/10.4093/dmj.2021.0319

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Abstract PDF Supplementary Material PubReader ePub

Background
Insulin-treated patients with long duration of type 2 diabetes mellitus (T2DM) are at increased risk of ketoacidosis related to sodium-glucose co-transporter 2 inhibitor (SGLT2i). The extent of circulating ketone elevation in these patients remains unknown. We conducted this study to compare the serum ketone response between dapagliflozin, an SGLT2i, and sitagliptin, a dipeptidyl peptidase-4 inhibitor, among insulin-treated T2DM patients.
Methods
This was a randomized, open-label, active comparator-controlled study involving 60 insulin-treated T2DM patients. Participants were randomized 1:1 for 24-week of dapagliflozin 10 mg daily or sitagliptin 100 mg daily. Serum β-hydroxybutyrate (BHB) levels were measured at baseline, 12 and 24 weeks after intervention. Comprehensive cardiometabolic assessments were performed with measurements of high-density lipoprotein cholesterol (HDL-C) cholesterol efflux capacity (CEC), vibration-controlled transient elastography and echocardiography.
Results
Among these 60 insulin-treated participants (mean age 58.8 years, diabetes duration 18.2 years, glycosylated hemoglobin 8.87%), as compared with sitagliptin, serum BHB levels increased significantly after 24 weeks of dapagliflozin (P=0.045), with a median of 27% increase from baseline. Change in serum BHB levels correlated significantly with change in free fatty acid levels. Despite similar glucose lowering, dapagliflozin led to significant improvements in body weight (P=0.006), waist circumference (P=0.028), HDL-C (P=0.041), CEC (P=0.045), controlled attenuation parameter (P=0.007), and liver stiffness (P=0.022). Average E/e’, an echocardiographic index of left ventricular diastolic dysfunction, was also significantly lower at 24 weeks in participants treated with dapagliflozin (P=0.037).
Conclusion
Among insulin-treated T2DM patients with long diabetes duration, compared to sitagliptin, dapagliflozin modestly increased ketone levels and was associated with cardiometabolic benefits.

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Ketosis and ketoacidosis in hospitalized patients receiving SGLT2 inhibitor therapy
Frank M. Gao, Kartik Kishore, Dinesh Pandey, Hossein Jahanabadi, Meg Stevens, Ashani Lecamwasam, Rinaldo Bellomo, Leonid Churilov, Elif I. Ekinci
Diabetes, Obesity and Metabolism.2025; 27(11): 6367. CrossRef
Monitoring Ketonemia in People with Diabetes: Preliminary Findings from Real-World Studies
Richard M. Bergenstal, Naunihal Virdi, Farhan Quadri, Shridhara Alva
Diabetes Technology & Therapeutics.2025; 27(S4): S25. CrossRef
Dipeptidyl Peptidase-4 Inhibitors Improved Lipid Levels in Patients With Type 2 Diabetes: A Meta-analysis of Randomized Clinical Trials
Lijia Zhao, Jie Meng, Jingjing Li, Hengri Cong, Changbin Liu, Yu Yang, Yangfeng Wu, Xin Liu
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Jimmy Ho Cheung Mak, David Tak‐Wai Lui, Carol Ho‐Yi Fong, Chloe Yu‐Yan Cheung, Ying Wong, Alan Chun‐Hong Lee, Ruby Lai‐Chong Hoo, Aimin Xu, Kathryn Choon‐Beng Tan, Karen Siu‐Ling Lam, Chi‐Ho Lee
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Exogenous Ketones in Cardiovascular Disease and Diabetes: From Bench to Bedside
Urna Kansakar, Crystal Nieves Garcia, Gaetano Santulli, Jessica Gambardella, Pasquale Mone, Stanislovas S. Jankauskas, Angela Lombardi
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Yao Wang, Yujie Zhong, Zhehao Zhang, Shuhao Yang, Qianying Zhang, Bingyang Chu, Xulin Hu
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Effects of SGLT2 inhibitors on hepatic fibrosis and steatosis: A systematic review and meta-analysis
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The impact of sodium-glucose Cotransporter-2 inhibitors on lipid profile: A meta-analysis of 28 randomized controlled trials
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Type 1 Diabetes
Abnormal Responses in Cognitive Impulsivity Circuits Are Associated with Glycosylated Hemoglobin Trajectories in Type 1 Diabetes Mellitus and Impaired Metabolic Control: Helena Jorge, Isabel C. Duarte, Sandra Paiva, Ana Paula Relvas, Miguel Castelo-Branco; Diabetes Metab J. 2022;46(6):866-878. Published online March 22, 2022; DOI: https://doi.org/10.4093/dmj.2021.0307

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Background
Risky health decisions and impulse control profiles may impact on metabolic control in type 1 diabetes mellitus (T1DM). We hypothesize that the neural correlates of cognitive impulsivity and decision-making in T1DM relate to metabolic control trajectories.
Methods
We combined functional magnetic resonance imaging (fMRI), measures of metabolic trajectories (glycosylated hemoglobin [HbA1c] over multiple time points) and behavioral assessment using a cognitive impulsivity paradigm, the Balloon Analogue Risk Task (BART), in 50 participants (25 T1DM and 25 controls).
Results
Behavioral results showed that T1DM participants followed a rigid conservative risk strategy along the iterative game. Imaging group comparisons showed that patients showed larger activation of reward related, limbic regions (nucleus accumbens, amygdala) and insula (interoceptive saliency network) in initial game stages. Upon game completion differences emerged in relation to error monitoring (anterior cingulate cortex [ACC]) and inhibitory control (inferior frontal gyrus). Importantly, activity in the saliency network (ACC and insula), which monitors interoceptive states, was related with metabolic trajectories, which was also found for limbic/reward networks. Parietal and posterior cingulate regions activated both in controls and patients with adaptive decision-making, and positively associated with metabolic trajectories.
Conclusion
We found triple converging evidence when comparing metabolic trajectories, patients versus controls or risk averse (non-learners) versus patients who learned by trial and error. Dopaminergic reward and saliency (interoceptive and error monitoring) circuits show a tight link with impaired metabolic trajectories and cognitive impulsivity in T1DM. Activity in parietal and posterior cingulate are associated with adaptive trajectories. This link between reward-saliency-inhibition circuits suggests novel strategies for patient management.

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Editorial: Translational neuroeconomic approach: from economic decision making to neuropsychological disorders
Mrinalini Srivastava, S. Senthil Kumaran, Achal Kumar Srivastava, Sanjay Singh
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Neuroeconomically dissociable forms of mental accounting are altered in a mouse model of diabetes
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Isabel Catarina Duarte, Bruno Ribeiro, Helena Jorge, Bruno Direito, Miguel Castelo‐Branco
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Glycated hemoglobin, type 2 diabetes, and poor diabetes control are positively associated with impulsivity changes in aged individuals with overweight or obesity and metabolic syndrome
Carlos Gómez‐Martínez, Nancy Babio, Lucía Camacho‐Barcia, Jordi Júlvez, Stephanie K. Nishi, Zenaida Vázquez, Laura Forcano, Andrea Álvarez‐Sala, Aida Cuenca‐Royo, Rafael de la Torre, Marta Fanlo‐Maresma, Susanna Tello, Dolores Corella, Alejandro Arias Vás
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Cristina Vintró‐Alcaraz, Núria Mallorquí‐Bagué, María Lozano‐Madrid, Giulia Testa, Roser Granero, Isabel Sánchez, Janet Treasure, Susana Jiménez‐Murcia, Fernando Fernández‐Aranda
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Charline Compagne, Juliana Teti Mayer, Damien Gabriel, Alexandre Comte, Eloi Magnin, Djamila Bennabi, Thomas Tannou
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Trust-based health decision-making recruits the neural interoceptive saliency network which relates to temporal trajectories of Hemoglobin A1C in Diabetes Type 1
Helena Jorge, Isabel C. Duarte, Miguel Melo, Ana Paula Relvas, Miguel Castelo-Branco
Brain Imaging and Behavior.2023; 18(1): 171. CrossRef

COVID-19
Association of Metabolic Syndrome with COVID-19 in the Republic of Korea: Woo-Hwi Jeon, Jeong-Yeon Seon, So-Youn Park, In-Hwan Oh; Diabetes Metab J. 2022;46(3):427-438. Published online November 26, 2021; DOI: https://doi.org/10.4093/dmj.2021.0105

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Background
Metabolic syndrome (MetS) is reportedly a crucial risk factor for coronavirus disease 2019 (COVID-19). Since the epidemiological studies that examine this association are few and include small samples, we investigated the relationship between MetS and COVID-19 severity and death using a larger sample in the Republic of Korea.
Methods
We analyzed 66,321 patients, 4,066 of whom had COVID-19. We used chi-square tests to examine patients’ characteristics. We performed logistic regression analysis to analyze differences in COVID-19 infection and clinical outcomes according to the presence of MetS.
Results
Although MetS was not significantly associated with COVID-19 risk, acquiring MetS was significantly associated with the risk of severe COVID-19 outcomes (odds ratio [OR], 1.97; 95% confidence interval [CI], 1.34 to 2.91; P=0.001). The mortality risk was significantly higher in COVID-19 patients with MetS (OR, 1.74; 95% CI, 1.17 to 2.59; P=0.006). Patients with abnormal waist circumference were approximately 2.07 times more likely to develop severe COVID-19 (P<0.001), and high-density lipoprotein cholesterol (HDL-C) levels were significantly associated with COVID-19; the mortality risk due to COVID-19 was 1.74 times higher in men with an HDL-C level of <40 mg/dL and in women with an HDL-C level of <50 mg/dL (P=0.012).
Conclusion
COVID-19 is likely associated with severity and death in patients with MetS or in patients with MetS risk factors. Therefore, patients with MetS or those with abnormal waist circumference and HDL-C levels need to be treated with caution.

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Russian Journal of Genetics.2025; 61(4): 460. CrossRef
Heterogeneity in familial clustering of metabolic syndrome components in the multiethnic GENNID study
Jia Y. Wan, Deborah Goodman, Sukh Makhnoon, Trina M. Norden‐Krichmar, Baolin Wu, Karen L. Edwards
Obesity.2024; 32(1): 176. CrossRef
Identification of shared genetic risks underlying metabolic syndrome and its related traits in the Korean population
Jun Young Kim, Yoon Shin Cho
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Metabolic health is more strongly associated with the severity and mortality of coronavirus disease 2019 than obesity
Hye Yeon Koo, Jae-Ryun Lee, Jin Yong Lee, Hyejin Lee
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Associated Factors with Changes of Metabolic Abnormalities among General Population in COVID-19 Pandemic
Eunjoo Kwon, Eun-Hee Nah, Suyoung Kim, Seon Cho, Hyeran Park
Korean Journal of Health Promotion.2023; 23(2): 55. CrossRef
Association between metabolic syndrome and mortality in patients with COVID-19: A nationwide cohort study
Hyo Jin Park, Jin-Hyung Jung, Kyungdo Han, Jean Shin, Yoojeong Lee, Yujin Chang, Kyeyeung Park, Yoon Jeong Cho, Youn Seon Choi, Seon Mee Kim, Ga Eun Nam
Obesity Research & Clinical Practice.2022; 16(6): 484. CrossRef

Cardiovascular Risk/Epidemiology
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 Metab J. 2022;46(2):273-285. Published online September 9, 2021; DOI: https://doi.org/10.4093/dmj.2021.0054

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Background
Risk assessment tools have been actively studied, and they summarize key predictors with relative weights/importance for a disease. Currently, standardized screening scores for type 2 diabetes mellitus (DM) and chronic kidney disease (CKD)—two key global health problems—are available in United States and Korea. We aimed to compare and evaluate screening scores for DM (or combined with prediabetes) and CKD, and assess the risk in contemporary United States and Korean populations.
Methods
Four (2×2) models were evaluated in the United States-National Health and Nutrition Examination Survey (NHANES 2015–2018) and Korea-NHANES (2016–2018)—8,928 and 16,209 adults. Weighted statistics were used to describe population characteristics. We used logistic regression for predictors in the models to assess associations with study outcomes (undiagnosed DM and CKD) and diagnostic measures for temporal and cross-validation.
Results
Korean adult population (mean age 47.5 years) appeared to be healthier than United States counterpart, in terms of DM and CKD risks and associated factors, with exceptions of undiagnosed DM, prediabetes and prehypertension. Models performed well in own country and external populations regarding predictor-outcome association and discrimination. Risk tests (high vs. low) showed area under the curve >0.75, sensitivity >84%, specificity >45%, positive predictive value >8%, and negative predictive value >99%. Discrimination was better for DM, compared to the combined outcome of DM and prediabetes, and excellent for CKD due to age.
Conclusion
Four easy-to-use screening scores for DM and CKD are well-validated in contemporary United States and Korean populations. Prevention of DM and CKD may serve as first-step in public health, with these self-assessment tools as basic tools to help health education and disparity.

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Yu Cao, Huiting Chen, Hui Liu, Hao Wu, Wei Gao
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Diabetes, Obesity and Metabolism.2024; 26(5): 1593. CrossRef
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Review

Cardiovascular Risk/Epidemiology
Management of Cardiovascular Risk in Perimenopausal Women with Diabetes: Catherine Kim; Diabetes Metab J. 2021;45(4):492-501. Published online July 30, 2021; DOI: https://doi.org/10.4093/dmj.2020.0262

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Cardiovascular disease is the primary cause of mortality in women and men with diabetes. Due to age and worsening of risk factors over the menopausal transition, risk of coronary heart disease events increases in postmenopausal women with diabetes. Randomized studies have conflicted regarding the beneficial impact of estrogen therapy upon intermediate cardiovascular disease markers and events. Therefore, estrogen therapy is not currently recommended for indications other than symptom management. However, for women at low risk of adverse events, estrogen therapy can be used to minimize menopausal symptoms. The risk of adverse events can be estimated using risk engines for the calculation of cardiovascular risk and breast cancer risk in conjunction with screening tools such as mammography. Use of estrogen therapy, statins, and anti-platelet agents can be guided by such calculators particularly for younger women with diabetes. Risk management remains focused upon lifestyle behaviors and achieving optimal levels of cardiovascular risk factors, including lipids, glucose, and blood pressure. Use of pharmacologic therapies to address these risk factors, particularly specific hypoglycemic agents, may provide some additional benefit for risk prevention. The minimal benefit for women with limited life expectancy and risk of complications with intensive therapy should also be considered.

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Sex hormones correlate with heart rate variability in healthy women and this correlation is conserved in women with well-controlled type 2 diabetes mellitus
Adriana Robles-Cabrera, Claudia Lerma, Silvia Ruiz-Velasco Acosta, Iván Pérez-Díaz, Ruben Fossion, Nejka Potocnik
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Original Article

Complications
Screening Tools Based on Nomogram for Diabetic Kidney Diseases in Chinese Type 2 Diabetes Mellitus Patients: Ganyi Wang, Biyao Wang, Gaoxing Qiao, Hao Lou, Fei Xu, Zhan Chen, Shiwei Chen; Diabetes Metab J. 2021;45(5):708-718. Published online April 13, 2021; DOI: https://doi.org/10.4093/dmj.2020.0117

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Background
The influencing factors of diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes mellitus (T2DM) were explored to develop and validate a DKD diagnostic tool based on nomogram approach for patients with T2DM.
Methods
A total of 2,163 in-hospital patients with diabetes diagnosed from March 2015 to March 2017 were enrolled. Specified logistic regression models were used to screen the factors and establish four different diagnostic tools based on nomogram according to the final included variables. Discrimination and calibration were used to assess the performance of screening tools.
Results
Among the 2,163 participants with diabetes (1,227 men and 949 women), 313 patients (194 men and 120 women) were diagnosed with DKD. Four different screening equations (full model, laboratory-based model 1 [LBM1], laboratory-based model 2 [LBM2], and simplified model) showed good discriminations and calibrations. The C-indexes were 0.8450 (95% confidence interval [CI], 0.8202 to 0.8690) for full model, 0.8149 (95% CI, 0.7892 to 0.8405) for LBM1, 0.8171 (95% CI, 0.7912 to 0.8430) for LBM2, and 0.8083 (95% CI, 0.7824 to 0.8342) for simplified model. According to Hosmer-Lemeshow goodness-of-fit test, good agreement between the predicted and observed DKD events in patients with diabetes was observed for full model (χ²=3.2756, P=0.9159), LBM1 (χ²=7.749, P=0.4584), LBM2 (χ²=10.023, P=0.2634), and simplified model (χ²=12.294, P=0.1387).
Conclusion
LBM1, LBM2, and simplified model exhibited excellent predictive performance and availability and could be recommended for screening DKD cases among Chinese patients with diabetes.

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Multi-feature integrated machine learning prediction model for early nephropathy in elderly living with type 2 diabetes mellitus
Tingting Fang, Yuanyuan Yang, Feng Zhuo, Xinran Xie, Jialun Song, Linghua Kong
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Machine learning-based risk predictive models for diabetic kidney disease in type 2 diabetes mellitus patients: a systematic review and meta-analysis
Yihan Li, Nan Jin, Qiuzhong Zhan, Yue Huang, Aochuan Sun, Fen Yin, Zhuangzhuang Li, Jiayu Hu, Zhengtang Liu
Frontiers in Endocrinology.2025;[Epub] CrossRef
Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach
Md Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, María Liz Crespo, Shamim Ahmad, Ghassan Maan Salim, Fahmida Haque, Luis Guillermo García Ordóñez, Md. Johirul Islam, Taher Muhammad Mahdee, Kh Shahriya Zaman, Md Shahriar Khan Hemel, Moham
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Predictive model combining blood pressure, glycemic and renal markers for diabetic nephropathy in elderly hypertensive patients with type 2 diabetes
Fengnian Guo, Li Qin, Baoguang Chen, Hongliang Xu, Jinxia Wang, Ran An, Qiuju Zhang
Clinical and Experimental Hypertension.2025;[Epub] CrossRef
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Xu Cao, Xiaomei Pei
Technology and Health Care.2024; 32(3): 1807. CrossRef
Development of Serum Lactate Level-Based Nomograms for Predicting Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients
Chunxia Jiang, Xiumei Ma, Jiao Chen, Yan Zeng, Man Guo, Xiaozhen Tan, Yuping Wang, Peng Wang, Pijun Yan, Yi Lei, Yang Long, Betty Yuen Kwan Law, Yong Xu
Diabetes, Metabolic Syndrome and Obesity.2024; Volume 17: 1051. CrossRef
Two-Dimensional Ultrasound-Based Radiomics Nomogram for Diabetic Kidney Disease: A Pilot Study
Xingyue Huang, Yugang Hu, Yao Zhang, Qing Zhou
International Journal of General Medicine.2024; Volume 17: 1877. CrossRef
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Wenbin Xu, Yanfei Zhou, Qian Jiang, Yiqian Fang, Qian Yang
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Changes in urinary exosomal protein CALM1 may serve as an early noninvasive biomarker for diagnosing diabetic kidney disease
Tao Li, Tian ci Liu, Na Liu, Man Zhang
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Hui Zhuan Tan, Jason Chon Jun Choo, Stephanie Fook-Chong, Yok Mooi Chin, Choong Meng Chan, Chieh Suai Tan, Keng Thye Woo, Jia Liang Kwek
International Urology and Nephrology.2022; 55(1): 191. CrossRef
Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data
Nakib Hayat Chowdhury, Mamun Bin Ibne Reaz, Sawal Hamid Md Ali, Shamim Ahmad, María Liz Crespo, Andrés Cicuttin, Fahmida Haque, Ahmad Ashrif A. Bakar, Mohammad Arif Sobhan Bhuiyan
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Review

Cardiovascular Risk/Epidemiology
Diabetes Management in Patients with Heart Failure: Jia Shen, Barry H. Greenberg; Diabetes Metab J. 2021;45(2):158-172. Published online March 25, 2021; DOI: https://doi.org/10.4093/dmj.2020.0296

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Diabetes and heart failure (HF) are common diseases, each affecting large segments of the world population. Moreover, prevalence rates for both are expected to rise dramatically over coming decades. The high prevalence rates of both diseases and wellrecognized association of diabetes as a risk factor for HF make it inevitable that both diseases co-exist in a large number of patients, complicating their management and increasing the risk of a poor outcome. Management of diabetes has been shown to impact clinical events in patients with HF and there is emerging evidence that agents used to treat diabetes can reduce HF events, even in non-diabetic patients. In this review we summarize the clinical course and treatment of patients with type 2 diabetes mellitus (T2DM) and HF and review the efficacy and safety of pharmacological agents in patients with T2DM at risk for HF and those with established disease.

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Original Articles

Complications
High Incidence of Chronic Kidney Disease among Iranian Diabetic Adults: Using CKD-EPI and MDRD Equations for Estimated Glomerular Filtration Rate: Seyyed Saeed Moazzeni, Reyhane Hizomi Arani, Mitra Hasheminia, Maryam Tohidi, Fereidoun Azizi, Farzad Hadaegh; Diabetes Metab J. 2021;45(5):684-697. Published online March 16, 2021; DOI: https://doi.org/10.4093/dmj.2020.0109

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Background
To investigate the population based incidence rate of chronic kidney disease (CKD) and its potential risk factors among Iranian diabetic adults during over 14 years of follow-up.
Methods
Two different equations (Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] and Modification of Diet in Renal Disease [MDRD]) were applied for the calculating the estimated glomerular filtration rate (eGFR). Among a total of 1,374 diabetic Tehranian adults, 797 and 680 individuals were eligible for CKD-EPI and MDRD analyses, respectively. CKD was defined as eGFR lower than 60 mL/min/1.73 m². Multivariable Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CI) for all potential risk factors.
Results
The incidence rates (95% CI) of CKD per 1,000 person-years were 43.84 (39.49 to 48.66) and 55.80 (50.29 to 61.91) based on CKD-EPI and MDRD equations, respectively. Being older, a history of cardiovascular disease, and having lower levels of eGFR were significant risk factors in both equations. Moreover, in CKD-EPI, using glucose-lowering medications and hypertension, and in MDRD, female sex and fasting plasma glucose ≥10 mmol/L were also independent risk factors. Regarding the discrimination index, CKD-EPI equation showed a higher range of C-index for the predicted probability of incident CKD in the full-adjusted model, compared to MDRD equation (0.75 [0.72 to 0.77] vs. 0.69 [0.66 to 0.72]).
Conclusion
We found an incidence rate of more than 4%/year for CKD development among our Iranian diabetic population. Compared to MDRD, it can be suggested that CKD-EPI equation can be a better choice to use for prediction models of incident CKD among the Iranian diabetic populations.

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Metabolic Risk/Epidemiology
Dose-Dependent Effect of Smoking on Risk of Diabetes Remains after Smoking Cessation: A Nationwide Population-Based Cohort Study in Korea: Se Eun Park, Mi Hae Seo, Jung-Hwan Cho, Hyemi Kwon, Yang-Hyun Kim, Kyung-Do Han, Jin-Hyung Jung, Yong-Gyu Park, Eun-Jung Rhee, Won-Young Lee; Diabetes Metab J. 2021;45(4):539-546. Published online March 4, 2021; DOI: https://doi.org/10.4093/dmj.2020.0061

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Background
This study aimed to evaluate the dose-dependent effects of smoking on risk of diabetes among those quitting smoking.
Methods
We analyzed clinical data from a total of 5,198,792 individuals age 20 years or older who received health care check-up arranged by the national insurance program of Korea between 2009 and 2016 using the Korean National Health Insurance Service database. Cumulative smoking was estimated by pack-years. Smokers were classified into four categories according to the amount of smoking: light smokers (0.025 to 5 smoking pack-years), medium smokers (5 to 14 smoking pack-years), heavy smokers (14 to 26 smoking pack-years), and extreme smokers (more than 26 smoking pack-years).
Results
During the study period, 164,335 individuals (3.2% of the total population) developed diabetes. Compared to sustained smokers, the risk of diabetes was significantly reduced in both quitters (hazard ratio [HR], 0.858; 95% confidence interval [CI], 0.838 to 0.878) and nonsmokers (HR, 0.616; 95% CI, 0.606 to 0.625) after adjustment for multiple risk factors. The risk of diabetes gradually increased with amount of smoking in both quitters and current smokers. The risk of diabetes in heavy (HR, 1.119; 95% CI, 1.057 to 1.185) and extreme smokers (HR, 1.348; 95% CI, 1.275 to 1.425) among quitters was much higher compared to light smokers among current smokers.
Conclusion
Smoking cessation was effective in reducing the risk of diabetes regardless of weight change. However, there was a potential dose-dependent association between smoking amount and the development of diabetes. Diabetes risk still remained in heavy and extreme smokers even after smoking cessation.

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COVID-19
Independent Impact of Diabetes on the Severity of Coronavirus Disease 2019 in 5,307 Patients in South Korea: A Nationwide Cohort Study: Sun Joon Moon, Eun-Jung Rhee, Jin-Hyung Jung, Kyung-Do Han, Sung-Rae Kim, Won-Young Lee, Kun-Ho Yoon; Diabetes Metab J. 2020;44(5):737-746. Published online October 21, 2020; DOI: https://doi.org/10.4093/dmj.2020.0141

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Background
Inconsistent results have been observed regarding the independent effect of diabetes on the severity of coronavirus disease 2019 (COVID-19). We conducted a nationwide population-based cohort study to evaluate the relationship between diabetes and COVID-19 severity in South Korea.
Methods
Patients with laboratory-confirmed COVID-19 aged ≥30 years were enrolled and medical claims data were obtained from the Korean Health Insurance Review and Assessment Service. Hospitalization, oxygen treatment, ventilator application, and mortality were assessed as severity outcomes. Multivariate logistic regression analyses were performed after adjusting for age, sex, and comorbidities.
Results
Of 5,307 COVID-19 patients, the mean age was 56.0±14.4 years, 2,043 (38.5%) were male, and 770 (14.5%) had diabetes. The number of patients who were hospitalized, who received oxygen, who required ventilator support, and who died was 4,986 (94.0%), 884 (16.7%), 121 (2.3%), and 211 (4.0%), respectively. The proportion of patients with diabetes in the abovementioned outcome groups was 14.7%, 28.1%, 41.3%, 44.6%, showing an increasing trend according to outcome severity. In multivariate analyses, diabetes was associated with worse outcomes, with an adjusted odds ratio (aOR) of 1.349 (95% confidence interval [CI], 1.099 to 1.656; P=0.004) for oxygen treatment, an aOR of 1.930 (95% CI, 1.276 to 2.915; P<0.001) for ventilator use, and an aOR of 2.659 (95% CI, 1.896 to 3.729; P<0.001) for mortality.
Conclusion
Diabetes was associated with worse clinical outcomes in Korean patients with COVID-19, independent of other comorbidities. Therefore, patients with diabetes and COVID-19 should be treated with caution.

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Complications
The Risk of Diabetes on Clinical Outcomes in Patients with Coronavirus Disease 2019: A Retrospective Cohort Study: Seung Min Chung, Yin Young Lee, Eunyeong Ha, Ji Sung Yoon, Kyu Chang Won, Hyoung Woo Lee, Jian Hur, Kyung Soo Hong, Jong Geol Jang, Hyun Jung Jin, Eun Young Choi, Kyeong-Cheol Shin, Jin Hong Chung, Kwan Ho Lee, June Hong Ahn, Jun Sung Moon; Diabetes Metab J. 2020;44(3):405-413. Published online May 21, 2020; DOI: https://doi.org/10.4093/dmj.2020.0105

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Background

To determine the role of diabetes mellitus (DM) in the coronavirus disease 2019 (COVID-19), we explored the clinical characteristics of patients with DM and compared risk factors such as age, glycemic control, and medications to those without DM.

Methods

This was a retrospective cohort study of 117 confirmed patients with COVID-19 which conducted at a tertiary hospital in Daegu, South Korea. The primary outcome was defined as the severe and critical outcome (SCO), of which the composite outcomes of acute respiratory distress syndrome, septic shock, intensive care unit care, and 28-day mortality. We analyzed what clinical features and glycemic control-related factors affect the prognosis of COVID-19 in the DM group.

Results

After exclusion, 110 participants were finally included. DM patients (n=29) was older, and showed higher blood pressure compared to non-DM patients. DM group showed higher levels of inflammation-related biomarkers and severity score, and highly progressed to SCO. After adjustment with other risk factors, DM increased the risk of SCO (odds ratio [OR], 10.771; P<0.001). Among the DM patients, SCO was more prevalent in elderly patients of ≥70 years old and age was an independent risk factor for SCO in patients with DM (OR, 1.175; P=0.014), while glycemic control was not. The use of medication did not affect the SCO, but the renin-angiotensin system inhibitors showed protective effects against acute cardiac injury (OR, 0.048; P=0.045).

Conclusion

The COVID-19 patients with DM had higher severity and resulted in SCO. Intensive and aggressive monitoring of COVID-19 clinical outcomes in DM group, especially in elderly patients is warranted.

Citations

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Diabetologia.2023; 66(8): 1395. CrossRef
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Impact of diabetes on COVID‐19 mortality and hospital outcomes from a global perspective: An umbrella systematic review and meta‐analysis
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Journal of Clinical Medicine.2022; 11(9): 2327. CrossRef
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Acta Diabetologica.2021; 58(8): 1101. CrossRef
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Cardiovascular Risk/Epidemiology
Validation of Risk Prediction Models for Atherosclerotic Cardiovascular Disease in a Prospective Korean Community-Based Cohort: Jae Hyun Bae, Min Kyong Moon, Sohee Oh, Bo Kyung Koo, Nam Han Cho, Moon-Kyu Lee; Diabetes Metab J. 2020;44(3):458-469. Published online January 13, 2020; DOI: https://doi.org/10.4093/dmj.2019.0061

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Abstract PDF Supplementary Material PubReader ePub

Background

To investigate the performance of the 2013 American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) in a large, prospective, community-based cohort in Korea and to compare it with that of the Framingham Global Cardiovascular Disease Risk Score (FRS-CVD) and the Korean Risk Prediction Model (KRPM).

Methods

In the Korean Genome and Epidemiology Study (KOGES)-Ansan and Ansung study, we evaluated calibration and discrimination of the PCE for non-Hispanic whites (PCE-WH) and for African Americans (PCE-AA) and compared their predictive abilities with the FRS-CVD and the KRPM.

Results

The present study included 7,932 individuals (3,778 men and 4,154 women). The PCE-WH and PCE-AA moderately overestimated the risk of atherosclerotic cardiovascular disease (ASCVD) for men (6% and 13%, respectively) but underestimated the risk for women (−49% and −25%, respectively). The FRS-CVD overestimated ASCVD risk for men (91%) but provided a good risk prediction for women (3%). The KRPM underestimated ASCVD risk for men (−31%) and women (−31%). All the risk prediction models showed good discrimination in both men (C-statistic 0.730 to 0.735) and women (C-statistic 0.726 to 0.732). Recalibration of the PCE using data from the KOGES-Ansan and Ansung study substantially improved the predictive accuracy in men.

Conclusion

In the KOGES-Ansan and Ansung study, the PCE overestimated ASCVD risk for men and underestimated the risk for women. The PCE-WH and the FRS-CVD provided an accurate prediction of ASCVD in men and women, respectively.

Citations

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Clinical Complications
Incidence and Risk Factors for Dementia in Type 2 Diabetes Mellitus: A Nationwide Population-Based Study in Korea: Ji Hee Yu, Kyungdo Han, Sanghyun Park, Hanna Cho, Da Young Lee, Jin-Wook Kim, Ji A Seo, Sin Gon Kim, Sei Hyun Baik, Yong Gyu Park, Kyung Mook Choi, Seon Mee Kim, Nan Hee Kim; Diabetes Metab J. 2020;44(1):113-124. Published online November 12, 2019; DOI: https://doi.org/10.4093/dmj.2018.0216

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Background

Diabetes mellitus is associated with an increased risk of dementia. We aimed to comprehensively analyze the incidence and risk factors for dementia and young-onset dementia (YOD) in diabetic patients in Korea using the National Health Insurance Service data.

Methods

Between January 1, 2009 and December 31, 2012, a total of 1,917,702 participants with diabetes were included and followed until the date of dementia diagnosis or until December 31, 2015. We evaluated the incidence and risk factors for all dementia, Alzheimer's disease (AD), and vascular dementia (VaD) by Cox proportional hazards analyses. We also compared the impact of risk factors on the occurrence of YOD and late-onset dementia (LOD).

Results

During an average of 5.1 years of follow-up, the incidence of all types of dementia, AD, or VaD was 9.5, 6.8, and 1.3/1,000 person-years, respectively, in participants with diabetes. YOD comprised 4.8% of all dementia occurrence, and the ratio of AD/VaD was 2.1 for YOD compared with 5.5 for LOD. Current smokers and subjects with lower income, plasma glucose levels, body mass index (BMI), and subjects with hypertension, dyslipidemia, vascular complications, depression, and insulin treatment developed dementia more frequently. Vascular risk factors such as smoking, hypertension, and previous cardiovascular diseases were more strongly associated with the development of VaD than AD. Low BMI and a history of stroke or depression had a stronger influence on the development of YOD than LOD.

Conclusion

The optimal management of modifiable risk factors may be important for preventing dementia in subjects with diabetes mellitus.

Citations

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Journal of Diabetes and its Complications.2026; 40(3): 109271. CrossRef
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Hee‐Cheol Kim
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Wonseok Jeong, Wonjeong Jeong, Seungju Kim
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Development of machine learning models for prediction of current and future dementia
Wonseok Jeong, Wankyo Chung, Jenna Scaramanga
PLOS One.2025; 20(12): e0330213. CrossRef
Association between multimorbidity and young-onset dementia: a prospective study
Durong Chen, Meiling Zhang, Yalu Wen, Hongjuan Han, Yao Qin, Rong Zhang, Hongyan Cao, Hongmei Yu
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Aging and disease.2024; 15(5): 2255. CrossRef
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Journal of Clinical Medicine.2024; 13(1): 260. CrossRef
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Francisco I. Pinheiro, Irami Araújo-Filho, Amália C.M. do Rego, Eduardo P. de Azevedo, Ricardo N. Cobucci, Fausto P. Guzen
Ageing Research Reviews.2024; 96: 102250. CrossRef
Sex Differences in the Trajectories of Cognitive Decline and Affected Cognitive Domains Among Older Adults With Controlled and Uncontrolled Glycemia
Natália Cochar-Soares, Dayane C de Oliveira, Mariane M Luiz, Márlon J R Aliberti, Claudia K Suemoto, Andrew Steptoe, Cesar de Oliveira, Tiago S Alexandre, Jay Magaziner
The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences.2024;[Epub] CrossRef
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Alzheimer's & Dementia.2024; 20(12): 8527. CrossRef
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Diabetes Research and Clinical Practice.2023; 201: 110721. CrossRef
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Journal of Diabetes Research.2023; 2023: 1. CrossRef
Sarcopenia and diabetes-induced dementia risk
Mingyang Sun, Zhongyuan Lu, Wan-Ming Chen, Szu-Yuan Wu, Jiaqiang Zhang
Brain Communications.2023;[Epub] CrossRef
Association of periodontitis with microvascular complications of diabetes mellitus: A nationwide cohort study
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Journal of Hypertension.2022; 40(2): 374. CrossRef
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Acta Diabetologica.2022; 59(4): 443. CrossRef
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Diabetes Research and Clinical Practice.2022; 185: 109227. CrossRef
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Biomedicines.2022; 10(4): 778. CrossRef
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Aging Clinical and Experimental Research.2021; 33(9): 2573. CrossRef
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Epidemiology
Oral Glucose Tolerance Testing Allows Better Prediction of Diabetes in Women with a History of Gestational Diabetes Mellitus: Tae Jung Oh, Yeong Gi Kim, Sunyoung Kang, Joon Ho Moon, Soo Heon Kwak, Sung Hee Choi, Soo Lim, Kyong Soo Park, Hak C. Jang, Joon-Seok Hong, Nam H. Cho; Diabetes Metab J. 2019;43(3):342-349. Published online December 7, 2018; DOI: https://doi.org/10.4093/dmj.2018.0086

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Background

We aimed to identify the postpartum metabolic factors that were associated with the development of diabetes in women with a history of gestational diabetes mellitus (GDM). In addition, we examined the role of the oral glucose tolerance test (OGTT) in the prediction of future diabetes.

Methods

We conducted a prospective study of 179 subjects who previously had GDM but did not have diabetes at 2 months postpartum. The initial postpartum examination including a 75-g OGTT and the frequently sampled intravenous glucose tolerance test (FSIVGTT) was performed 12 months after delivery, and annual follow-up visits were made thereafter.

Results

The insulinogenic index (IGI30) obtained from the OGTT was significantly correlated with the acute insulin response to glucose (AIRg) obtained from the FSIVGTT. The disposition indices obtained from the OGTT and FSIVGTT were also significantly correlated. Women who progressed to diabetes had a lower insulin secretory capacity including IGI30, AIRg, and disposition indices obtained from the FSIVGTT and OGTT compared with those who did not. However, the insulin sensitivity indices obtained from the OGTT and FSIVGTT did not differ between the two groups. Multivariate logistic regression analysis showed that the 2-hour glucose and disposition index obtained from the FSIVGTT were significant postpartum metabolic risk factors for the development of diabetes.

Conclusion

We identified a crucial role of β-cell dysfunction in the development of diabetes in Korean women with previous GDM. The 2-hour glucose result from the OGTT is an independent predictor of future diabetes. Therefore, the OGTT is crucial for better prediction of future diabetes in Korean women with previous GDM.

Citations

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Experimental & Molecular Medicine.2026; 58(1): 272. CrossRef
Gestational Diabetes Mellitus: Mechanisms Underlying Maternal and Fetal Complications
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Endocrinology and Metabolism.2025; 40(1): 10. CrossRef
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The problem of diabetes mellitus in obstetrics
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2023 Clinical Practice Guidelines for Diabetes Management in Korea: Full Version Recommendation of the Korean Diabetes Association
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Endocrinology and Metabolism.2021; 36(3): 628. CrossRef
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Endocrine Journal.2021; 68(8): 919. CrossRef
Risk factors during the early postpartum period for type 2 diabetes mellitus in women with gestational diabetes
Maki Kawasaki, Naoko Arata, Naoko Sakamoto, Anna Osamura, Siori Sato, Yoshihiro Ogawa, Ichiro Yasuhi, Masako Waguri, Yuji Hiramatsu
Endocrine Journal.2020; 67(4): 427. CrossRef
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Journal of Diabetes Research.2019; 2019: 1. CrossRef

Epidemiology
Projection of Diabetes Prevalence in Korean Adults for the Year 2030 Using Risk Factors Identified from National Data: Inkyung Baik; Diabetes Metab J. 2019;43(1):90-96. Published online October 31, 2018; DOI: https://doi.org/10.4093/dmj.2018.0043

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Background

A number of studies have reported future prevalence estimates for diabetes mellitus (DM), but these studies have been limited for the Korean population. The present study aimed to construct a forecasting model that includes risk factors for type 2 DM using individual- and national-level data for Korean adults to produce prevalence estimates for the year 2030.

Methods

Time series data from the Korea National Health and Nutrition Examination Survey and national statistics from 2005 to 2013 were used. The study subjects were 13,908 male and 18,697 female adults aged 30 years or older who were free of liver cirrhosis. Stepwise logistic regression analysis was used to select significant factors associated with DM prevalence.

Results

The results showed that survey year, age, sex, marital, educational, or occupational status, the presence of obesity or hypertension, smoking status, alcohol consumption, sleep duration, psychological distress or depression, and fertility rate significantly contributed to the 8-year trend in DM prevalence (P<0.05). Based on sex-specific forecasting models that included the above factors, DM prevalence for the year 2030 was predicted to be 29.2% (95% confidence interval [CI], 27.6% to 30.8%) in men and 19.7% (95% CI, 18.2% to 21.2%) in women.

Conclusion

The present study projected a two-fold increase in the prevalence of DM in 2030 compared with that for the years 2013 and 2014 in Korean adults. Modifiable factors contributing to this increase in DM prevalence, such as obesity, smoking, and psychological factors, may require attention in order to reduce national and individual costs associated with DM.

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Short Communication

Complications
The Prevalence and Risk Factors for Diabetic Retinopathy in Shiraz, Southern Iran: Haleh Ghaem, Nima Daneshi, Shirin Riahi, Mostafa Dianatinasab; Diabetes Metab J. 2018;42(6):538-543. Published online August 9, 2018; DOI: https://doi.org/10.4093/dmj.2018.0047

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Globally, diabetic retinopathy (DR) is one of the leading causes of blindness, that diminishes quality of life. This study aimed to describe the prevalence of DR, and its associated risk factors. This cross-sectional study was carried out among 478 diabetic patients in a referral center in Fars province, Iran. The mean±standard deviation age of the participants was 56.64±12.45 years old and DR prevalence was 32.8%. In multivariable analysis, lower education levels (adjusted odds ratio [aOR], 0.43; 95% confidence interval [CI], 0.24 to 0.76), being overweight (aOR, 1.70; 95% CI, 1.02 to 2.83) or obese (aOR, 1.88; 95% CI, 1.09 to 3.26), diabetes duration of 10 to 20 years (aOR, 2.35; 95% CI, 1.48 to 3.73) and over 20 years (aOR, 5.63; 95% CI, 2.97 to 10.68), receiving insulin (aOR, 1.99; 95% CI, 1.27 to 3.10), and having chronic diseases (aOR, 1.71; 95% CI, 1.02 to 2.85) were significantly associated with DR. In conclusion, longer diabetes duration and obesity or having chronic diseases are strongly associated with DR suggesting that control of these risk factors may reduce both the prevalence and impact of retinopathy in Iran.

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Original Articles

Epidemiology
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 Metab J. 2018;42(5):402-414. Published online July 6, 2018; DOI: https://doi.org/10.4093/dmj.2018.0014

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Background

A diabetes risk score in Korean adults was developed and validated.

Methods

This study used the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) of 359,349 people without diabetes at baseline to derive an equation for predicting the risk of developing diabetes, using Cox proportional hazards regression models. External validation was conducted using data from the Korean Genome and Epidemiology Study. Calibration and discrimination analyses were performed separately for men and women in the development and validation datasets.

Results

During a median follow-up of 10.8 years, 37,678 cases (event rate=10.4 per 1,000 person-years) of diabetes were identified in the development cohort. The risk score included age, family history of diabetes, alcohol intake (only in men), smoking status, physical activity, use of antihypertensive therapy, use of statin therapy, body mass index, systolic blood pressure, total cholesterol, fasting glucose, and γ glutamyl transferase (only in women). The C-statistics for the models for risk at 10 years were 0.71 (95% confidence interval [CI], 0.70 to 0.73) for the men and 0.76 (95% CI, 0.75 to 0.78) for the women in the development dataset. In the validation dataset, the C-statistics were 0.63 (95% CI, 0.53 to 0.73) for men and 0.66 (95% CI, 0.55 to 0.76) for women.

Conclusion

The Korean Diabetes Risk Score may identify people at high risk of developing diabetes and may be an effective tool for delaying or preventing the onset of condition as risk management strategies involving modifiable risk factors can be recommended to those identified as at high risk.

Citations

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Complications
Clinical Course and Risk Factors of Diabetic Retinopathy in Patients with Type 2 Diabetes Mellitus in Korea: Jae-Seung Yun, Tae-Seok Lim, Seon-Ah Cha, Yu-Bae Ahn, Ki-Ho Song, Jin A Choi, Jinwoo Kwon, Donghyun Jee, Yang Kyung Cho, Yong-Moon Park, Seung-Hyun Ko; Diabetes Metab J. 2016;40(6):482-493. Published online October 5, 2016; DOI: https://doi.org/10.4093/dmj.2016.40.6.482

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Background

We investigated clinical course and risk factors for diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM).

Methods

A total of 759 patients with T2DM without DR were included from January 2001 to December 2004. Retinopathy evaluation was performed at least annually by ophthalmologists. The severity of the DR was classified into five categories according to the International Clinical Diabetic Retinopathy Severity Scales.

Results

Of the 759 patients, 523 patients (68.9%) completed the follow-up evaluation. During the follow-up period, 235 patients (44.9%) developed DR, and 32 patients (13.6%) progressed to severe nonproliferative DR (NPDR) or proliferative DR (PDR). The mean duration of diabetes at the first diagnosis of mild NPDR, moderate NPDR, and severe NPDR or PDR were 14.8, 16.7, and 17.3 years, respectively. After adjusting multiple confounding factors, the significant risk factors for the incidence of DR risk in patients with T2DM were old age, longer duration of diabetes, higher mean glycosylated hemoglobin (HbA1c), and albuminuria. Even in the patients who had been diagnosed with diabetes for longer than 10 years at baseline, a decrease in HbA1c led to a significant reduction in the risk of developing DR (hazard ratio, 0.73 per 1% HbA1c decrement; 95% confidence interval, 0.58 to 0.91; P=0.005).

Conclusion

This prospective cohort study demonstrates that glycemic control, diabetes duration, age, and albuminuria are important risk factors for the development of DR. More aggressive retinal screening for T2DM patients diagnosed with DR should be required in order to not miss rapid progression of DR.

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Annals of the National Academy of Medical Sciences (India).2020; 53: 156. CrossRef
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Sang Youl Rhee, Jeong-Taek Woo
Diabetes & Metabolism Journal.2017; 41(6): 494. CrossRef
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Diabetes & Metabolism Journal.2017; 41(1): 77. CrossRef
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Jae-Seung Yun
Diabetes & Metabolism Journal.2017; 41(6): 492. CrossRef

Review

Complications
Risk Factors and Adverse Outcomes of Severe Hypoglycemia in Type 2 Diabetes Mellitus: Jae-Seung Yun, Seung-Hyun Ko; Diabetes Metab J. 2016;40(6):423-432. Published online October 5, 2016; DOI: https://doi.org/10.4093/dmj.2016.40.6.423

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Hypoglycemia has been considered as a major barrier to achieving the proper glycemic target in type 2 diabetes mellitus patients. In particular, severe hypoglycemia (SH), which is defined as a hypoglycemic episode requiring the assistance of another person to raise the patient's glucose level, is a serious complication of diabetes because of its possible fatal outcomes. Recently, the recommendations for diabetes care have emphasized a patient-centered approach, considering the individualized patient factors including hypoglycemia. Many studies have been performed which analyzed the risk factors and clinical outcomes for SH. From the studies, researchers recommend that targeting a less stringent glycosylated hemoglobin level and selecting a safer class of drugs for hypoglycemia are appropriate for patients with a high risk of SH. Also, careful clinical attention to prevent hypoglycemia, including intensive education, is necessary to minimize the risk of SH and SH-related fatal outcomes.

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JAMA Network Open.2025; 8(6): e2513293. CrossRef
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Diabetes Research and Clinical Practice.2025; 227: 112401. CrossRef
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Raedeh Basiri, Megan Kassem, Yatisha Rajanala, Cara L. Frankenfeld
Frontiers in Nutrition.2025;[Epub] CrossRef
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Journal of Korean Biological Nursing Science.2025; 27(4): 629. CrossRef
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Н.А. Первышин
Успехи геронтологии.2025; 38(4): 510. CrossRef
Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition)
Lixin Guo, Xinhua Xiao
AGING MEDICINE.2024; 7(1): 5. CrossRef
Risk factors and adverse outcomes of hypoglycemia in older patients with type 2 diabetes mellitus (review)
S. V. Bulgakova, P. Ya. Merzlova, D. P. Kurmaev, E. V. Treneva
Russian Journal of Geriatric Medicine.2024; (1): 30. CrossRef
A novel electronic health record-based, machine-learning model to predict severe hypoglycemia leading to hospitalizations in older adults with diabetes: A territory-wide cohort and modeling study
Mai Shi, Aimin Yang, Eric S. H. Lau, Andrea O. Y. Luk, Ronald C. W. Ma, Alice P. S. Kong, Raymond S. M. Wong, Jones C. M. Chan, Juliana C. N. Chan, Elaine Chow
PLOS Medicine.2024; 21(4): e1004369. CrossRef
Cardiac autonomic neuropathy modified the association between obesity and hypoglycemia in type 2 diabetes
Wenjing Zhang, Yiquan Huang, Ziwei Zhou, Peihan Xie, Xiaodong Zhuang, Jingzhou Jiang, Xinxue Liao
Endocrine.2024; 85(3): 1213. CrossRef
Holistic and Personalized Strategies for Managing in Elderly Type 2 Diabetes Patients
Jae-Seung Yun, Kyuho Kim, Yu-Bae Ahn, Kyungdo Han, Seung-Hyun Ko
Diabetes & Metabolism Journal.2024; 48(4): 531. CrossRef
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S. V. Bulgakova, P. Ya. Merzlova, D. P. Kurmaev, E. V. Treneva
Russian Journal of Geriatric Medicine.2024; (2): 108. CrossRef
Effects of insulin glargine U300 versus insulin degludec U100 on glycemic variability, hypoglycemia, and diet evaluated by continuous glucose monitoring in type 1 diabetes: a retrospective cross‐sectional study
Pin‐Lun Tsai, Chia‐Hung Lin, Yu‐Yao Huang, Hsin‐Yun Chen, Yi‐Hsuan Lin
The Kaohsiung Journal of Medical Sciences.2024; 40(12): 1086. CrossRef
ОПРЕДЕЛЕНИЕ ЦЕЛЕЙ ТЕРАПЕВТИЧЕСКОГО КОНТРОЛЯ САХАРНОГО ДИАБЕТА 2-го ТИПА У ПОЖИЛЫХ ПАЦИЕНТОВ С ПРИМЕНЕНИЕМ ЦИФРОВОГО КЛИНИЧЕСКОГО КАЛЬКУЛЯТОРА
Н.А. Первышин
Успехи геронтологии.2024; 37(5): 537. CrossRef
Evaluation of Computer-Based Insulin Infusion Algorithm Compared With a Paper-Based Protocol in the Treatment of Diabetic Ketoacidosis
Heather M. Martinez, Kirsten Elwood, Chris Werth, Preeyaporn Sarangarm
Journal of Pharmacy Technology.2023; 39(2): 82. CrossRef
A prediction model for assessing hypoglycemia risk in critically ill patients with sepsis
Hongyang Gao, Yang Zhao
Heart & Lung.2023; 62: 43. CrossRef
Systematic Literature Review and Indirect Treatment Comparison of Three Ready-to-Use Glucagon Treatments for Severe Hypoglycemia
Marga Giménez, Kamlesh Khunti, Munehide Matsuhisa, Suresh Chenji, Kristen Syring, Yu Yan
Diabetes Therapy.2023; 14(11): 1757. CrossRef
Use of Second-Generation Basal Insulin Gla-300 in Special Populations: A Narrative Mini-Review
Sujoy Ghosh, Sanjay Kalra, Ganapathi Bantwal, Rakesh Kumar Sahay
Current Diabetes Reviews.2023;[Epub] CrossRef
A Cross-Sectional study on risk factors for severe hypoglycemia among Insulin-Treated elderly type 2 diabetes Mellitus (T2DM) patients in Singapore
Michelle Shi Min Ko, Wai Kit Lee, Li Chang Ang, Su-Yen Goh, Yong Mong Bee, Ming Ming Teh
Diabetes Research and Clinical Practice.2022; 185: 109236. CrossRef
Role of polyphenols in combating Type 2 Diabetes and insulin resistance
Moyad Shahwan, Fahad Alhumaydhi, Ghulam Md. Ashraf, Prince M.Z. Hasan, Anas Shamsi
International Journal of Biological Macromolecules.2022; 206: 567. CrossRef
Real-World Effectiveness and Safety of Insulin Glargine 300 U/mL in Insulin-Naïve People with Type 2 Diabetes: the ATOS Study
Gagik R. Galstyan, Amir Tirosh, Hernando Vargas-Uricoechea, Maria Aileen Mabunay, Mathieu Coudert, Mubarak Naqvi, Valerie Pilorget, Niaz Khan
Diabetes Therapy.2022; 13(6): 1187. 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
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Manoj Chawla, Purvi Chawla, Banshi Saboo, Jothydev Kesavadev, Amit Gupta, Rakesh Parikh
International Journal of Diabetes and Technology.2022; 1(2): 69. CrossRef
Severe hypoglycemia and the risk of end stage renal disease in type 2 diabetes
Jae-Seung Yun, Yong-Moon Park, Kyungdo Han, Hyung-Wook Kim, Seon-Ah Cha, Yu-Bae Ahn, Seung-Hyun Ko
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Severe Hypoglycemia Risk With Long-Acting Insulin Analogs vs Neutral Protamine Hagedorn Insulin
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JAMA Internal Medicine.2021; 181(5): 598. CrossRef
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Xavier Dubucs, Jean-Baptiste Julla, Tiphaine Vidal-Trecan, Jean-Pierre Riveline, Jean-François Gautier
Diabetes Research and Clinical Practice.2020; 162: 108034. CrossRef
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Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy.2020; 40(9): 902. CrossRef
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Associations Between the Knowledge of Different Food Categories and Glycemia in Chinese Adult Patients With Type 2 Diabetes
Yuan Xue, Xiao-Yan Zhang, Hui-Juan Zhou, Omorogieva Ojo, Qi Wang, Li-Li Wang, Qing Jiang, Ting Liu, Xiao-Hua Wang
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Deterioration of Sleep Quality According to Glycemic Status
Myung Haeng Hur, Mi-Kyoung Lee, Kayeon Seong, Jun Hwa Hong
Diabetes & Metabolism Journal.2020; 44(5): 679. CrossRef
Higher versus standard starting dose of insulin glargine 100 U/mL in overweight or obese Chinese patients with type 2 diabetes: Results of a multicentre, open‐label, randomized controlled trial (BEYOND VII)
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Diabetes, Obesity and Metabolism.2020; 22(5): 838. CrossRef
Outcomes for Inappropriate Renal Dose Adjustment of Dipeptidyl Peptidase-4 Inhibitors in Patients With Type 2 Diabetes Mellitus: Population-Based Study
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Stephen A. Brunton, Ofri Mosenzon, Eugene E. Wright Jr
Postgraduate Medicine.2020; 132(sup2): 48. CrossRef
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Alice Y. Y. Cheng, Jencia Wong, Nick Freemantle, Shamasunder H. Acharya, Elif Ekinci
Diabetes Therapy.2020; 11(11): 2555. CrossRef
Predisposing factors of hypoglycemia in patients with type 2 diabetes mellitus presented with symptomatic hypoglycemia in a tertiary hospital of Bangladesh
AjitK Paul, A.B.M. Kamrul-Hasan
Journal of Diabetology.2020; 11(3): 163. CrossRef
Development of a hypoglycaemia risk score to identify high‐risk individuals with advanced type 2 diabetes in DEVOTE
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Diabetes, Obesity and Metabolism.2020; 22(12): 2248. CrossRef
Real-world risk of hypoglycemia-related hospitalization in Japanese patients with type 2 diabetes using SGLT2 inhibitors: a nationwide cohort study
Takeshi Horii, Yoichi Oikawa, Narumi Kunisada, Akira Shimada, Koichiro Atsuda
BMJ Open Diabetes Research & Care.2020; 8(2): e001856. CrossRef
Common inpatient hypoglycemia phenotypes identified from an automated electronic health record–based prediction model
Yoonyoung Choi, Ben Staley, Rene Soria-Saucedo, Carl Henriksen, Amy Rosenberg, Almut G Winterstein
American Journal of Health-System Pharmacy.2019; 76(3): 166. CrossRef
Severe hypoglycemia and the risk of cardiovascular disease and mortality in type 2 diabetes: a nationwide population-based cohort study
Jae-Seung Yun, Yong-Moon Park, Kyungdo Han, Seon-Ah Cha, Yu-Bae Ahn, Seung-Hyun Ko
Cardiovascular Diabetology.2019;[Epub] CrossRef
Analysis of the characteristics of patients with diabetes mellitus who attend a tertiary hospital emergency department for a hypoglycemic event
Jordi Caballero-Corchuelo, Fernando Guerrero-Pérez, Paula García-Sancho de la Jordana, Manuel Pérez-Maraver
Endocrinología, Diabetes y Nutrición (English ed.).2019; 66(1): 19. CrossRef
Management of hypoglycemia in older adults with type 2 diabetes
Jeffrey Freeman
Postgraduate Medicine.2019; 131(4): 241. CrossRef
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Diabetes Therapy.2019; 10(6): 2289. CrossRef
Association between BMI and risk of severe hypoglycaemia in type 2 diabetes
J.-S. Yun, Y.-M. Park, K. Han, S.-A. Cha, Y.-B. Ahn, S.-H. Ko
Diabetes & Metabolism.2019; 45(1): 19. CrossRef
Análisis de las características de los pacientes con diabetes mellitus que consultan por hipoglucemia en el servicio de urgencias de un hospital terciario
Jordi Caballero-Corchuelo, Fernando Guerrero-Pérez, Paula García-Sancho de la Jordana, Manuel Pérez-Maraver
Endocrinología, Diabetes y Nutrición.2019; 66(1): 19. CrossRef
The association between hypoglycemia and hospital use, food insufficiency, and unstable housing conditions: a cross-sectional study among patients with type 2 diabetes in Sudan
Hyder Osman Mirghani
BMC Research Notes.2019;[Epub] CrossRef
Hypoglycemia after initiating insulin therapy based on the results of structured self-control and monitoring of blood glucose
A. V. Petrov, L. G. Strongin
Medical Council.2018; (12): 112. CrossRef
Monotherapy in Patients with Type 2 Diabetes Mellitus
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Diabetes & Metabolism Journal.2017; 41(5): 349. CrossRef
Monotherapy in patients with type 2 diabetes mellitus
Sang Youl Rhee, Hyun Jin Kim, Seung-Hyun Ko, Kyu Yeon Hur, Nan-Hee Kim, Min Kyong Moon, Seok-O Park, Byung-Wan Lee, Kyung Mook Choi, Jin Hwa Kim
The Korean Journal of Internal Medicine.2017; 32(6): 959. CrossRef
Antihyperglycemic agent therapy for adult patients with type 2 diabetes mellitus 2017: a position statement of the Korean Diabetes Association
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The Korean Journal of Internal Medicine.2017; 32(6): 947. CrossRef
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Diabetes & Metabolism Journal.2017; 41(5): 337. CrossRef

Original Articles

Risk Factors for the Progression of Intima-Media Thickness of Carotid Arteries: A 2-Year Follow-Up Study in Patients with Newly Diagnosed Type 2 Diabetes: Sang Ouk Chin, Jin Kyung Hwang, Sang Youl Rhee, Suk Chon, You-Cheol Hwang, Seungjoon Oh, Kyu Jeung Ahn, Ho Yeon Chung, Jeong-taek Woo, Sung-Woon Kim, Young Seol Kim, Ja-Heon Kang, In-Kyung Jeong; Diabetes Metab J. 2013;37(5):365-374. Published online October 17, 2013; DOI: https://doi.org/10.4093/dmj.2013.37.5.365

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Background

Intima-media thickness (IMT) of the carotid arteries is known to have a positive correlation with the risk of cardiovascular disease. This study was designed to identify risk factors affecting the progression of carotid IMT in patients with type 2 diabetes mellitus (T2DM).

Methods

Patients with newly diagnosed T2DM with carotid IMT measurements were enrolled, and their clinical data and carotid IMT results at baseline and 2 years later were compared.

Results

Of the 171 patients, 67.2% of males and 50.8% of females had abnormal baseline IMT of the left common carotid artery. At baseline, systolic blood pressure, body mass index and smoking in male participants, and fasting plasma glucose and glycated hemoglobin levels in females were significantly higher in patients with abnormal IMT than in those with normal IMT. Low density lipoprotein cholesterol (LDL-C) levels in males and high density lipoprotein cholesterol (HDL-C) levels in females at the 2-year follow-up were significantly different between the nonprogression and the progression groups. Reduction of the United Kingdom Prospective Diabetes Study (UKPDS) 10-year coronary heart disease (CHD) risk score after 2 years was generally higher in the nonprogression group than the progression group.

Conclusion

LDL-C levels in males and HDL-C levels in females at the 2-year follow-up were significantly different between participants with and without progression of carotid IMT. Furthermore, a reduction in the UKPDS 10-year CHD risk score appeared to delay the advancement of atherosclerosis. Therefore, the importance of establishing the therapeutic goal of lipid profiles should be emphasized to prevent the progression of carotid IMT in newly diagnosed T2DM patients.

Citations

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Nutrients.2022; 14(20): 4391. CrossRef
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Rong Shi, Birong Wu, Zheyun Niu, Hui Sun, Fan Hu
Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy.2020; Volume 13: 5025. CrossRef
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Qinghai Zhang, Ling Chen, Zhibo Zhao, Ying Wu, Jing Zhong, Gebo Wen, Renxian Cao, Xuyu Zu, Jianghua Liu
DNA and Cell Biology.2018; 37(4): 389. CrossRef
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Tomoya Mita, Naoto Katakami, Toshihiko Shiraiwa, Hidenori Yoshii, Nobuichi Kuribayashi, Takeshi Osonoi, Hideaki Kaneto, Keisuke Kosugi, Yutaka Umayahara, Masahiko Gosho, Iichiro Shimomura, Hirotaka Watada
Scientific Reports.2017;[Epub] CrossRef
Impact of carotid atherosclerosis detection on physician and patient behavior in the management of type 2 diabetes mellitus: a prospective, observational, multicenter study
In-Kyung Jeong, Sin-Gon Kim, Dong Hyeok Cho, Chong Hwa Kim, Chul Sik Kim, Won-Young Lee, Kyu-Chang Won, Doo-Man Kim
BMC Cardiovascular Disorders.2016;[Epub] CrossRef
The effect of fibroblast growth factors and advanced glycation end-products on the intima-media complex thickness in patients with coronary heart disease and type 2 diabetes
Ekaterina Vladimirovna Ivannikova, Victor Yurievich Kalashnikov, Olga Mikhailovna Smirnova, Alexander Borisovich Kuznetsov, Сергей Anatolievich Terekhin, Alexander Viktorovich Il'in
Diabetes mellitus.2014; 17(2): 47. CrossRef

Chronic Kidney Disease and Associated Cardiovascular Risk Factors in Chinese with Type 2 Diabetes: Qing-Lin Lou, Xiao-Jun Ouyang, Liu-Bao Gu, Yong-Zhen Mo, Ronald Ma, Jennifer Nan, Alice Kong, Wing-Yee So, Gary Ko, Juliana Chan, Chun-Chung Chow, Rong-Wen Bian; Diabetes Metab J. 2012;36(6):433-442. Published online December 12, 2012; DOI: https://doi.org/10.4093/dmj.2012.36.6.433

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Background

To determine the frequency of chronic kidney disease (CKD) and its associated risk factors in Chinese type 2 diabetic patients, we conducted a cross-sectional study in Nanjing, China, in the period between January 2008 and December 2009.

Methods

Patients with type 2 diabetes under the care by Jiangsu Province Official Hospital, Nanjing, China were invited for assessment. CKD was defined as the presence of albuminuria or estimated glomerular filtration rate <60 mL/min/1.73 m². Albuminuria was defined as urinary albumin-to-creatinine ratio ≥30 mg/g.

Results

We recruited 1,521 urban Chinese patients with type 2 diabetes (mean age, 63.9±12.0 years). The frequency of CKD and albuminuria was 31.0% and 28.9%, respectively. After adjusted by age and sex, hypertension, anemia and duration of diabetes were significantly associated with CKD with odds ratio (95% confidence interval) being 1.93 (1.28 to 2.93), 1.70 (1.09 to 2.64), and 1.03 (1.00 to 1.06), respectively.

Conclusion

In conclusion, CKD was common in the urban Nanjing Chinese with type 2 diabetes. Strategies to prevent or delay progression of kidney disease in diabetes should be carried out at the early disease course of type 2 diabetes.

Citations

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The burden of chronic kidney disease in Asia region: a review of the evidence, current challenges, and future directions
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Kidney Research and Clinical Practice.2025; 44(3): 411. CrossRef
Prevalence of diabetic kidney disease by world region of birth among immigrants and long-term residents of Canada with type 2 diabetes
Sebat Mohamed, Lorraine L Lipscombe, Jennifer Lipscombe, Chris Kenaszchuk, Deva Thiruchelvam, Baiju R Shah, Ghazal S Fazli, Gillian Booth, Laura Rosella, Calvin Ke
Diabetes Research and Clinical Practice.2025; 226: 112365. CrossRef
Associations between dietary patterns and renal impairment in individuals with diabetes: a cross‐sectional study
Ziling Ding, Xingzhe Wu, Chao Liu, Ruixue Ying, Yi Zhang, Shiqi Zhang, Qiu Zhang, Honglin Hu, Fang Dai
Journal of Human Nutrition and Dietetics.2024; 37(1): 193. CrossRef
A Randomised Controlled Study of Can Ling Bai Shu San Combined with Guizhi Fuling Pills and Dagliflozin in the Treatment of Proteinuria in Type 2 Diabetic Nephropathy Stage IV
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Advances in Clinical Medicine.2024; 14(01): 1829. CrossRef
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BMJ Open.2024; 14(5): e079415. CrossRef
Prevalence and characteristics of chronic kidney disease in people with type 2 diabetes mellitus in the Autonomous Community of Aragon
María Antonia Sánchez-Calavera, Rafael Gómez Navarro, Elena Asso Otal, Isabel Blasco González, Daniel Escribano Pardo, Laia Homedes Celma, Michelot Lamarre, Pilar López Esteban, María Luisa Lozano del Hoyo, Liliana Mahulea, Inés Mera Gallego, Juan Carlos
Primary Care Diabetes.2024; 18(5): 555. CrossRef
Cardiometabolic traits mediating the effect of education on the risk of DKD and CKD: a Mendelian randomization study
Yukai Wang, Mengmeng Chen, Lin Wang, Yonggui Wu
Frontiers in Nutrition.2024;[Epub] CrossRef
Chronic kidney disease and risk factors among Type 2 Diabetic patients in selected hospitals in Dhaka, Bangladesh
Md Rasel Mahbub, Maksudul Akash Shadat, Md. Osman Goni, Shahanaz Chowdhury
HEALTH SCIENCES QUARTERLY.2024; 4(4): 259. CrossRef
Evaluation of Renal Impairment in Patients with Diabetic Kidney Disease by Integrated Chinese and Western Medicine
Yi-lun Qu, Zhe-yi Dong, Hai-mei Cheng, Qian Liu, Qian Wang, Hong-tao Yang, Yong-hui Mao, Ji-jun Li, Hong-fang Liu, Yan-qiu Geng, Wen Huang, Wen-hu Liu, Hui-di Xie, Fei Peng, Shuang Li, Shuang-shuang Jiang, Wei-zhen Li, Shu-wei Duan, Zhe Feng, Wei-guang Zh
Chinese Journal of Integrative Medicine.2023; 29(4): 308. CrossRef
Extracellular status of thrombospondin-2 in type 2 diabetes mellitus and utility as a biomarker in the determination of early diabetic kidney disease
Zhenzhen Lin, Didong Zhang, Xinxin Zhang, Wanxie Guo, Wenjun Wang, Yingchao Zhang, Zhen Liu, Yanxue Bi, Maolan Wu, Zhuofeng Lin, Xuemian Lu
BMC Nephrology.2023;[Epub] CrossRef
Serum Lipocalin-2 Levels Are Increased and Independently Associated With Early-Stage Renal Damage and Carotid Atherosclerotic Plaque in Patients With T2DM
Jing Gan, Yu Zheng, Qiongli Yu, Yingchao Zhang, Wei Xie, Yaru Shi, Ning Yu, Yu Yan, Zhuofeng Lin, Hong Yang
Frontiers in Endocrinology.2022;[Epub] CrossRef
The Prevalence, Progress and Risk Factor Control of Chronic Kidney Disease in Chinese Adults With Type 2 Diabetes Mellitus in Primary Care
Lingwang An, Qiuzhi Yu, Hong Tang, Xianglan Li, Dandan Wang, Qi Tang, Haiyang Xing, Yali He, Xiaona Zhao, Shuhui Zhao, Yaujiunn Lee, Juming Lu
Frontiers in Endocrinology.2022;[Epub] CrossRef
Hydration status according to impedance vectors and its association with clinical and biochemical outcomes and mortality in patients with chronic kidney disease
Paola Vanessa Miranda Alatriste, Eloísa Colin Ramírez, Ximena Atilano Carsi, Cristino Cruz-Rivera, Ángeles Espinosa-Cuevas
Nutrición Hospitalaria.2022;[Epub] CrossRef
The Prevalence of Diabetic Microvascular Complications in China and the USA
Yu Kuei Lin, Bixia Gao, Lili Liu, Lynn Ang, Kara Mizokami-Stout, Rodica Pop-Busui, Luxia Zhang
Current Diabetes Reports.2021;[Epub] CrossRef
Reno-protective potential of sodium glucose cotransporter-2 (SGLT2) inhibitors: Summary evidence from clinical and real-world data
Niti Mittal, Vikas Sehray, Rakesh Mittal, Surjit Singh
European Journal of Pharmacology.2021; 907: 174320. CrossRef
Association between Renal Podocalyxin Expression and Renal Dysfunction in Patients with Diabetic Nephropathy: A Single‐Center, Retrospective Case‐Control Study
Rongzhen Wang, Can Yao, Feng Liu, Claudio De Lucia
BioMed Research International.2020;[Epub] CrossRef
Renoprotection with SGLT2 inhibitors in type 2 diabetes over a spectrum of cardiovascular and renal risk
Francesco Giorgino, Jiten Vora, Peter Fenici, Anna Solini
Cardiovascular Diabetology.2020;[Epub] CrossRef
Prevalence of diabetic nephropathy among Chinese patients with type 2 diabetes mellitus and different categories of their estimated glomerular filtration rate based on the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation in primary car
Ka Yee Mok, Pang Fai Chan, Loretta K. P. Lai, Kai Lim Chow, David V. K. Chao
Journal of Diabetes & Metabolic Disorders.2019; 18(2): 281. CrossRef
The association between serum uric acid to creatinine ratio and renal disease progression in type 2 diabetic patients in Chinese communities
Yao Chunlei, Gu Liubao, Wang Tao, Xing Changying
Journal of Diabetes and its Complications.2019; 33(7): 473. CrossRef
Risk factors of chronic kidney diseases in Chinese adults with type 2 diabetes
Lin Yang, Tsun Kit Chu, Jinxiao Lian, Cheuk Wai Lo, Pak Ki Lau, Hairong Nan, Jun Liang
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Any grade of relative overhydration is associated with long-term mortality in patients with Stages 4 and 5 non-dialysis chronic kidney disease
Almudena Vega, Soraya Abad, Nicolás Macías, Inés Aragoncillo, Ana García-Prieto, Tania Linares, Esther Torres, Andrés Hernández, José Luño
Clinical Kidney Journal.2018; 11(3): 372. CrossRef
The impact of the quality of care and other factors on progression of chronic kidney disease in Thai patients with Type 2 Diabetes Mellitus: A nationwide cohort study
Paithoon Sonthon, Supannee Promthet, Siribha Changsirikulchai, Ram Rangsin, Bandit Thinkhamrop, Suthee Rattanamongkolgul, Cameron P. Hurst, Cheng Hu
PLOS ONE.2017; 12(7): e0180977. CrossRef
Association of Chronic Kidney Disease with Coronary Heart Disease and Stroke Risks in Patients with Type 2 Diabetes Mellitus
Xue Sun, Jie He, Xiao-Li Ji, Yi-Ming Zhao, Han-Yu Lou, Xiao-Xiao Song, Li-Zhen Shan, Ying-Xiu Kang, Wen-Heng Zeng, Xiao-Hong Pang, Song-Zhao Zhang, Yue Ding, Yue-Zhong Ren, Peng-Fei Shan
Chinese Medical Journal.2017; 130(1): 57. CrossRef
Prevalence of chronic kidney disease and associated factors in Chinese individuals with type 2 diabetes: Cross-sectional study
Kaifeng Guo, Lei Zhang, Fangya Zhao, Junxi Lu, Pan Pan, Haoyong Yu, Yuqian Bao, Haibing Chen, Weiping Jia
Journal of Diabetes and its Complications.2016; 30(5): 803. CrossRef
The association between abnormal heart rate variability and new onset of chronic kidney disease in patients with type 2 diabetes: A ten-year follow-up study
Jae-Seung Yun, Yu-Bae Ahn, Ki-Ho Song, Ki-Dong Yoo, Hyung-Wook Kim, Yong-Moon Park, Seung-Hyun Ko
Diabetes Research and Clinical Practice.2015; 108(1): 31. CrossRef
Association of elevated glycosylated hemoglobin A1c with hyperfiltration in a middle-aged and elderly Chinese population with prediabetes or newly diagnosed diabetes: a cross-sectional study
Wen Hu, Hairong Hao, Weinan Yu, Xiaojuan Wu, Hongwen Zhou
BMC Endocrine Disorders.2015;[Epub] CrossRef
Prevalence of Chronic Kidney Disease in Adults with Type 2 Diabetes Mellitus
Serena KM Low, Chee Fang Sum, Lee Ying Yeoh, Subramaniam Tavintharan, Xiao Wei Ng, Simon BM Lee, Wern Ee Tang, Su Chi Lim
Annals of the Academy of Medicine, Singapore.2015; 44(5): 164. CrossRef
Low Ankle-Brachial Index Is Associated with Early-Stage Chronic Kidney Disease in Type 2 Diabetic Patients Independent of Albuminuria
Xuehong Dong, Dingting Wu, Chengfang Jia, Yu Ruan, Xiaocheng Feng, Guoxing Wang, Jun Liu, Yi Shen, Hong Li, Lianxi Li, Karin Jandeleit-Dahm
PLoS ONE.2014; 9(10): e109641. CrossRef
Health Behaviors and Risk Factors Associated with Chronic Kidney Disease in Korean Patients with Diabetes: The Fourth Korean National Health and Nutritional Examination Survey
Suk Jeong Lee, Chae Weon Chung
Asian Nursing Research.2014; 8(1): 8. CrossRef
Urinary miR-29 Correlates with Albuminuria and Carotid Intima-Media Thickness in Type 2 Diabetes Patients
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PLoS ONE.2013; 8(12): e82607. CrossRef
Diabetes and its comorbidities—where East meets West
Alice P. S. Kong, Gang Xu, Nicola Brown, Wing-Yee So, Ronald C. W. Ma, Juliana C. N. Chan
Nature Reviews Endocrinology.2013; 9(9): 537. CrossRef

Sulwon Lecture 2011

Post-Renal Transplant Diabetes Mellitus in Korean Subjects: Superimposition of Transplant-Related Immunosuppressant Factors on Genetic and Type 2 Diabetic Risk Factors: Hyun Chul Lee; Diabetes Metab J. 2012;36(3):199-206. Published online June 14, 2012; DOI: https://doi.org/10.4093/dmj.2012.36.3.199

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Postrenal transplantation diabetes mellitus (PTDM), or new-onset diabetes after organ transplantation, is an important chronic transplant-associated complication. Similar to type 2 diabetes, decreased insulin secretion and increased insulin resistance are important to the pathophysiologic mechanism behind the development of PTDM. However, β-cell dysfunction rather than insulin resistance seems to be a greater contributing factor in the development of PTDM. Increased age, family history of diabetes, ethnicity, genetic variation, obesity, and hepatitis C are partially accountable for an increased underlying risk of PTDM in renal allograft recipients. In addition, the use of and kinds of immunosuppressive agents are key transplant-associated risk factors. Recently, a number of genetic variants or polymorphisms susceptible to immunosuppressants have been reported to be associated with calcineurin inhibition-induced β-cell dysfunction. The identification of high risk factors of PTDM would help prevent PTDM and improve long-term patient outcomes by allowing for personalized immunosuppressant regimens and by managing cardiovascular risk factors.

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International Journal of Endocrinology.2020; 2020: 1. CrossRef
Synthesis of Fructose Biosensors and Progressing Their Efficiency Using Californium Colloidal Nanoparticles for Detecting Fructose and Triglycerides
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Advanced Science, Engineering and Medicine.2020; 12(8): 1002. CrossRef
Comparison of Glucose Tolerance between Kidney Transplant Recipients and Healthy Controls
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Journal of Clinical Medicine.2019; 8(7): 920. CrossRef
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Renal posttransplantation diabetes mellitus: An overview
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Transplantation.2014; 97(4): 419. CrossRef
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Post-Transplant Diabetes Mellitus: Is It Associated With Poor Allograft Outcomes in Renal Transplants?
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Transplantation Proceedings.2013; 45(8): 2892. CrossRef

Original Article

The Prevalence of Peripheral Arterial Disease in Korean Patients with Type 2 Diabetes Mellitus Attending a University Hospital: Ji Hee Yu, Jenie Yoonoo Hwang, Mi-Seon Shin, Chang Hee Jung, Eun Hee Kim, Sang Ah Lee, Eun Hee Koh, Woo Je Lee, Min-Seon Kim, Joong-Yeol Park, Ki-Up Lee; Diabetes Metab J. 2011;35(5):543-550. Published online October 31, 2011; DOI: https://doi.org/10.4093/dmj.2011.35.5.543

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Background

Peripheral arterial disease (PAD) is a common manifestation of systemic atherosclerosis and is associated with significant morbidity and mortality. Diabetes is known to increase the risk of PAD two- to four-fold. The prevalence of PAD in Korean diabetic patients has not been established. In this study, we investigated the prevalence of PAD in Korean patients with type 2 diabetes attending a large university hospital and analyzed the factors associated with PAD.

Methods

A total of 2,002 patients with type 2 diabetes who underwent ankle-brachial index (ABI) measurement in an outpatient clinic were enrolled. PAD was defined as an ABI ≤0.9. Clinical characteristics of 64 patients with PAD were compared with those of 192 age- and sex-matched control patients without PAD.

Results

Of the 2,002 type 2 diabetic patients, 64 (3.2%) were diagnosed as having PAD. PAD was associated with higher prevalences of retinopathy, nephropathy, neuropathy, cerebrovascular and coronary artery disease. Patients with PAD had higher systolic blood pressure and serum triglyceride level and reported higher pack-years of smoking. Multivariate analysis showed that the presence of micro- and macrovascular complications and high systolic blood pressure are factors independently associated with PAD.

Conclusion

The prevalence of PAD in diabetic patients was 3.2%, suggesting that the prevalence in Korean diabetic patients is lower than that of patients in Western countries.

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Risk factors for peripheral arterial disease in type 2 diabetes mellitus patients: A systematic review and meta-analysis
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Inverted U-shaped relationship between HbA1c and diabetic retinopathy in diabetic patients: a cross-sectional study
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Journal of Diabetes Research.2022; 2022: 1. CrossRef
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Journal of the Korean Society of Radiology.2021; 82(3): 551. CrossRef
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Orighomisan Freda Agboghoroma, Fatai Momodu Akemokwe, Fabian H. Puepet
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The significance of ankle-brachial index in determining peripheral artery disease in patients with type 2 diabetes mellitus over 40 years of age and the relationship of peripheral artery disease with chronic complications of diabetes
Tuğçe Nur YİĞENOĞLU, Medine KEBAPÇI, Hülya ÖZEN
Journal of Health Sciences and Medicine.2020; 3(2): 115. CrossRef
Correlation of systemic arterial stiffness with changes in retinal and choroidal microvasculature in type 2 diabetes
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Abnormally Low or High Ankle-Brachial Index Is Associated With the Development of Diabetic Retinopathy in Type 2 Diabetes Mellitus
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Peripheral Arterial Disease in Type 2 Diabetes Is Associated with an Increase in Fibrinogen Levels
Qin-Fen Chen, Dan Cao, Ting-Ting Ye, Hui-Hui Deng, Hong Zhu
International Journal of Endocrinology.2018; 2018: 1. CrossRef
Association between peripheral arterial disease and diabetic foot ulcers in patients with diabetes mellitus type 2
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Medicina Universitaria.2017; 19(76): 123. CrossRef
Factors associated with lower extremity atherosclerotic disease in Chinese patients with type 2 diabetes mellitus
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Medicine.2016; 95(51): e5230. CrossRef
Significant interarm blood pressure difference predicts cardiovascular risk in hypertensive patients
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Medicine.2016; 95(24): e3888. CrossRef
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Review

Gestational Diabetes in Korea: Incidence and Risk Factors of Diabetes in Women with Previous Gestational Diabetes: Hak Chul Jang; Diabetes Metab J. 2011;35(1):1-7. Published online February 28, 2011; DOI: https://doi.org/10.4093/dmj.2011.35.1.1

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Korean women with a history of gestational diabetes mellitus (GDM) have a 3.5 times greater risk of developing postpartum diabetes than the general population. The incidence of type 2 diabetes mellitus in early postpartum is reported as 10-15% in Korean women. A prospective follow-up study on Korean women with GDM showed that approximately 40% of women with previous GDM were expected to develop diabetes within 5 years postpartum. Independent risk factors for the development of diabetes in Korean women with previous GDM are pre-pregnancy body weight, gestational age at diagnosis, antepartum hyperglycemia on oral glucose tolerance test, low insulin response to oral glucose load, and family history of diabetes. Women with postpartum diabetes have greater body mass indexes, body weight, and waist circumferences than women with normal glucose tolerance. Multiple logistic regression analysis has revealed that waist circumference is the strongest obesity index along with systolic blood pressure and that triglyceride levels are a major independent risk factor for developing diabetes. These results in Korean women with previous GDM underline the importance of postpartum testing in Korean women diagnosed with GDM, and demonstrate that impaired B-cell function, obesity, and especially visceral obesity, are associated with the development of diabetes.

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Journal of Clinical Medicine.2023; 12(5): 1738. CrossRef
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Current Diabetes Reports.2023; 23(9): 231. CrossRef
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Original Articles

The Status of Diabetes Mellitus and Effects of Related Factors on Heart Rate Variability in a Community.: Kyeong Soon Chang, Kwan Lee, Hyun Sul Lim; Korean Diabetes J. 2009;33(6):537-546. Published online December 1, 2009; DOI: https://doi.org/10.4093/kdj.2009.33.6.537

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Abstract PDF

BACKGROUND
This study was performed to examine the status of diabetes mellitus (DM) in the community and effects of related factors on heart rate variability (HRV). METHODS: The author conducted HRV testing, a questionnaire survey, and blood chemistry analysis for fasting blood sugar (FBS) and HbA1c levels in 855 patients in a community over a period of 10 days, from August 14 to 25, 2006. The subjects were divided into a DM group and normal group by our study criteria. RESULTS: The proportion of DM was 12.6% and increased with old age. The mean measures of HRV (SDNN, Tp, Vlf, Lf, Hf, Lf/Hf) in the DM group were 22.7 (1.6) msec, 364.9 (2.7) msec2, 174.1 (3.0) msec2, 88.1 (3.2) msec2, 55.3 (3.2) msec2, and 1.6 (2.6), respectively, while those in the normal group were 32.2 (1.6) msec, 676.6 (2.8) msec2, 295.7 (3.1) msec2, 169.2 (3.4) msec2, 117.2 (3.2) msec2, and 1.4 (2.6), respectively. All parameters except for Lf/Hf were significantly lower in the DM group than in the normal group (P < 0.01). The Spearman's correlation coefficients between HRV and FBS or HbA1c were SDNN -0.222/-0.244 (P < 0.01), Tp -0.211/-0.212 (P < 0.01), Vlf -0.149/-0.132 (P < 0.01), Lf -0.188/-0.235 (P < 0.01), Hf -0.207/-0.204 (P < 0.01), and Lf/Hf (P > 0.05), respectively. CONCLUSION: This study shows that the DM group had a reduced HRV and increased pulse rate in comparison with the normal group. According to our results, the HRV test may be used accessorily for the early detection of cardiovascular autonomic neuropathy (CAN) and its related factors, as well as to prevent CAN.

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Psychophysiological Responses of Adults According to Cognitive Demand Levels for Horticultural Activities
Seon-Ok Kim, Yun-Jin Kim, Sin-Ae Park
Sustainability.2022; 14(14): 8252. CrossRef
Physiological and psychological responses of humans to the index of greenness of an interior space
Ji-Young Choi, Sin-Ae Park, Soo-Jin Jung, Ji-Young Lee, Ki-Cheol Son, Youn-Joo An, Sang-Woo Lee
Complementary Therapies in Medicine.2016; 28: 37. CrossRef

Risk Factors for Early Development of Macrovascular Complications in Korean Type 2 Diabetes.: Hae Ri Lee, Jae Myung Yu, Moon Gi Choi, Hyung Joon Yoo, Eun Gyoung Hong; Korean Diabetes J. 2009;33(2):134-142. Published online April 1, 2009; DOI: https://doi.org/10.4093/kdj.2009.33.2.134

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Abstract PDF

BACKGROUND
The average duration of diabetes and predictive factors of macrovascular complications in Korean diabetic patients remain to be elucidated. This study examines the average duration of diabetes up to the onset of macrovascular complications and clinically important factors of early development of these complications in Korean type 2 diabetic patients. METHODS: Clinical characteristics in type 2 diabetics with (n = 121) and without macrovascular complications (n = 115) were analyzed. In addition, early onset (< or = 5 years, n = 54) and late onset groups (> 5 years, n = 67) were compared, as were the clinical characteristics between male and female patients in the macrovascular complications group. RESULTS: The average duration of diabetes was 8.7 +/- 7.8 years in the macrovascular complications group. Average age, systolic and diastolic blood pressures and smoking history were all higher in the macrovascular complications group than the control group. However, HbA1c levels and prevalence of microvascular complications were higher in the controls. Average age was lower in the early onset group and many more patients of that group had a smoking history. In the analysis based on sex, marcrovascular complications developed earlier in male patients. In addition, the prevalence of family history of diabetes was higher in males and 77.8% of male patients had a smoking history (female: 3.4%). CONCLUSION: Our study confirms that older age, high blood pressure and smoking history are major risk factors for the development of macrovascular complications. Moreover, a smoking history in males can be both risk and predictive factors for earlier development of macrovascular complications in Korean type 2 diabetic patients. We also found that several clinical characteristics including age, family history of diabetes, hypertension and smoking history, vary between the sexes, and these findings can provide useful indices for the prevention of macrovascular complications.

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Impact of new-onset diabetes on clinical outcomes after ST segment-elevated myocardial infarction
Ji-Yeoun Seo, Jin-Sun Park, Kyoung-Woo Seo, Hyoung-Mo Yang, Hong-Seok Lim, Byoung-Joo Choi, So-Yeon Choi, Myeong-Ho Yoon, Gyo-Seung Hwang, Seung-Jea Tahk, Joon-Han Shin
Scandinavian Cardiovascular Journal.2019; 53(6): 379. CrossRef
Associations Between the Continuity of Ambulatory Care of Adult Diabetes Patients in Korea and the Incidence of Macrovascular Complications
Young-Hoon Gong, Seok-Jun Yoon, Hyeyoung Seo, Dongwoo Kim
Journal of Preventive Medicine and Public Health.2015; 48(4): 188. CrossRef
Relationship of Daily Activity and Biochemical Variables in the Elderly with Diabetes Mellitus
Ki-Wol Sung
Journal of Korean Academy of Nursing.2011; 41(2): 182. CrossRef
Epidemiology of Micro- and Macrovascular Complications of Type 2 Diabetes in Korea
Jung Hee Kim, Dae Jung Kim, Hak Chul Jang, Sung Hee Choi
Diabetes & Metabolism Journal.2011; 35(6): 571. CrossRef

Effects of Type 2 Diabetes Mellitus on Risk Factors of Acute Coronary Syndrome.: Hong Ju Moon, Jun Goo Kang, Min Ho Jo, Byung Wan Lee, Cheol Young Park, Seong Jin Lee, Eun Kyung Hong, Jae Myoung Yu, Doo Man Kim, Sung Hee Ihm, Hyun Kyu Kim, Chong Yun Rhim, Moon Gi Choi, Hyung Joon Yoo, Sung Woo Park; Korean Diabetes J. 2006;30(6):435-441. Published online November 1, 2006; DOI: https://doi.org/10.4093/jkda.2006.30.6.435

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Abstract PDF

BACKGROUND
Diabetes mellitus (DM) is equivalent as well a risk factor of cardiovascular disease. We analyzed the effects of DM on clinical risk factors of acute coronary syndrome by comparing DM group with Non-DM group. METHODS: A total of 847 (514 males and 333 females) patients with acute coronary syndrome was selected from 1664 patients who had undergone coronary angiography (CAG). These patients comprised 105 subjects with non-ST elevation myocardial infarction (MI), 313 with ST elevation MI and 429 with unstable angina. According to the presence of DM, we retrospectively reviewed the measured basic demographics, biochemical markers and coronary angiographic findings. RESULTS: In the multivariated analysis, history of hypertension (P = 0.001), C-reactive protein (CRP) level (P = 0.001) and triglyceride level (P = 0.018) were independent risk factors in type 2 diabetic group. Also the frequency of multiple coronary vessel disease was higher in DM group than non-DM group on the coronary angiographic finding CONCLUSIONS: Classic risk factors for acute coronary syndrome are strong predictors in patients with type 2 DM. Among these factors, the most important powerful risk factor is history of hypertension.

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Gender-Based Differences in the Management and Prognosis of Acute Coronary Syndrome in Korea
Hee Tae Yu, Kwang Joon Kim, Woo-Dae Bang, Chang-Myung Oh, Ji-Yong Jang, Sung-Soo Cho, Jung-Sun Kim, Young-Guk Ko, Donghoon Choi, Myeong-Ki Hong, Yangsoo Jang
Yonsei Medical Journal.2011; 52(4): 562. CrossRef

Association Between Impaired Vascular Endothelial Function and High Sensitivity C-reactive Protein, a Chronic Inflammatory Marker, in Patients with Type 2 Diabetes Mellitus.: Jang Yel Shin, Mi Young Lee, Jang Hyun Koh, Jang Young Kim, Young Goo Shin, Choon Hee Chung; Korean Diabetes J. 2005;29(5):469-478. Published online September 1, 2005

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Abstract PDF: BACKGOUND: Eighty percents of diabetes-related mortalities are due to atherosclerotic vascular complications. The accelerated atherosclerosis in type 2 diabetic patients is partly due to the increased incidences of cardiovascular risk factors, such as hypertension, obesity, dyslipidemia, insulin resistance and oxidative stress. Endothelial dysfunction is known as an early marker of cardiovascular disease and a predictor of cardiovascular events. The flow mediated dilation (FMD) of the brachial artery has been documented as being reduced in type 2 diabetic patients. Inflammatory markers, such as C-reactive protein(CRP) and interleukin-6(IL-6), are associated with the risk of cardiovascular disease. Endothelial dysfunction has a direct correlation with the levels of CRP, which are elevated in patients with diabetes compared with non-diabetic subjects. In this study, the FMD in diabetic and non-diabetic subjects were compared, and the association of cardiovascular risk factors and endothelial function examined in type 2 diabetic patients. METHODS: 57 consecutive diabetic subjects and 29 non-diabetic subjects, aged 35 to 69(54.0+/-1.0 years), without proven macrovascular complications, were enrolled in this study. Cardiovascular risk factors, such as body weight, height, waist and hip circumference, fasting plasma glucose and insulin levels, lipid profiles, inflammatory and coagulation markers were measured. The FMD of the brachial artery and the intima-media thickness(IMT) of the carotid artery were determined using high-resolution B-mode ultrasound. RESULTS: The FMD values were significantly lower in the diabetic compared with the non-diabetic subjects(7.6+/-0.2% vs. 8.9+/-0.4%, P=0.004). The homocysteine levels were significantly higher in the diabetic than non-diabetic subjects(12.4+/-0.4micromol/L vs. 9.5+/-0.6micromol/L, P<0.0001). In diabetic subjects, the FMD was shown to be significantly negatively correlated with high sensitivity C-reactive protein(hsCRP)(P=0.006), fibrinogen(P=0.024) and homocysteine (P=0.038). A multiple regression analysis, after adjusted for age, sex, body mass index(BMI), hypertension, and smoking, showed that hsCRP(beta=-0.424, P=0.002) and fibrinogen(beta=-0.324, P=0.025) had significant inverse association with the FMD in diabetic subjects. CONCLUSION: Diabetic subjects have an impaired endothelial function compared with the non-diabetic subjects, and the vascular endothelial function has a significant negative correlation with hsCRP and fibrinogen. These findings suggest that hsCRP might be an independent predictor of endothelial dysfunction and atherosclerosis, and chronic inflammation might play a pivotal role in the impairment of the endothelial function in diabetic patients.

The Relationship Between the C1818T Polymorphism in Exon 4 of the klotho Gene with Fasting Glucose and Insulin Levels in Korean Women.: Ki Won Oh, Eun Joo Yun, Eun Jung Rhee, Won Young Lee, Ki Hyun Baek, Kun Ho Yoon, Moo Il Kang, Seong Gyun Kim, Cheol Young Park, Sung Hee Ihm, Moon Gi Choi, Hyung Joon Yoo, Sung Woo Park; Korean Diabetes J. 2005;29(3):189-197. Published online May 1, 2005

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Abstract PDF: BACKGROUND
A novel gene, termed klotho has been identified as a suppressor of several aging phenotypes, and a genetic defect of klotho in mice resulted in a syndrome resembling human aging, i.e., a short lifespan, infertility, arteriosclerosis, skin atrophy, osteoporosis, and pulmonary emphysema. Since klotho mice also showed an abnormal glucose metabolism, we investigated the relationship between the C1818T polymorphism in exon 4 of the klotho gene and fasting glucose and insulin resistance in Korean women to observe its contribution to glucose metabolism. METHODS: The weight, height, blood pressure, fasting blood glucose, insulin, and lipid profiles were measured in 241 women(mean age, 51.2+/-7.0yr) by using the standard methods. Homeostasis model assessment(HOMA)-insulin resistance(IR), the quantitative insulin sensitivity check index(QUICKI) and HOMAbeta-cell were calculated. The genotyping of the C1818T polymorphism in exon 4 of the klotho gene was performed by allelic discrimination with using a 5' nuclease polymerase chain reaction assay. RESULTS: The allele frequencies were 0.805 for the C allele and 0.195 for the T allele, and they were in Hardy-Weinberg equilibrium(P=0.290). The mean fasting blood glucose(P= 0.005) and HOMA IR(P=0.035) were significantly higher in the T allele carriers compared with the non-carriers. After adjustment was made for age, fasting blood glucose was persistently significant(P=0.015), but the HOMA-IR became marginally significant(P=0.063). In the premenopausal women, the T allele carriers showed a higher mean fasting blood glucose(P=0.038), insulin(P=0.024), HOMA-IR(P=0.010), total cholesterol(P=0.039), and triglyceride levels(P=0.031) than in the non-carriers. After adjustment was made for age, the fasting blood glucose, insulin, HOMA-IR and triglyceride were persistently significant(P= 0.043, P=0.026, P=0.011, P=0.040). Also, the QUICKI, total cholesterol and low-density ilpo-protein cholesterol became marginally significant(P=0.073, P=0.061, P=0.098). For the postmenopausal women, the T allele carriers showed a tendency for higher mean fasting blood glucose levels(P=0.065) and lower HOMA beta-cell levels(P=0.085) than in the noncarriers. These differences became non-significant after adjustment was made for age. CONCLUSION: We observed that the C1818T polymorphism in exon 4 of the klotho gene was partly associated with glucose metabolism in Korean women. Also, these data suggest that the C1818T polymorphism is related with some cardiovascular risk factors in Korean women. The mechanism linking this gene with glucose metabolism warrants further study

Poor Prognosis Factors and Risk Factors of Amputation in Foot ulcers in Diabetes.: Mi Jung Eun, Jung Hoon Lee, Jin Ho Kim, Ji Eun Lee, Jae Hong Kim, Kyu Chang Won, In Ho Jo, Hyoung Woo Lee; Korean Diabetes J. 2004;28(4):304-314. Published online August 1, 2004

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Abstract PDF: BACKGROUND
Foot ulcers are a common complication of diabetes mellitus, and their prevalence is increased relative to those without diabetes. Foot ulcers and related complications represent an important cause of morbidity among patients with diabetes mellitus. Most of the poor prognosis factors and amputation risk factors of diabetic foot ulcers have been found to be largely affected by male sex, inadequate blood glucose control, vascular disease, neuropathy, end organ defects, and the depth and size of ulcers, prior ulcer history, infection and ischemia. Currently, the poor prognosis factors and amputation risk factors of diabetic foot ulcers in the Korean diabetic population are unknown. The purpose of this study was to identify and quantify the poor prognosis factors of diabetic foot ulcers and the risk factors of lower extremity amputation. METHODS: This study comprised of involved 37 male and 14 female diabetics with foot ulcers aged 23 to 83 years. According to the results of treatment, the patients were divided into 4 groups; complete healing (CH), partial healing (PH), unhealing (UH), and amputation (AM) groups. The baseline characteristics of the study subjects (gender, age, duration of diabetes, BMI, drinking, smoking, insulin therapy, blood pressure, whole blood count, renal function test and the size and depth of ulcer, prior ulcer history, osteomyelitis, infection, ischemia, neuropathy and retinopathy) were examined. RESULTS: The following characteristics were not significantly related to the poor prognosis factors and amputation risk factors of diabetic foot ulcers: age, duration of diabetes, BMI; drinking, smoking, insulin therapy, blood pressure, whole blood count and renal function test. The following characteristics were significantly related to the poor prognosis factors and amputation risk factors of diabetic foot ulcers: male (p=0.021), ischemia (p<0.05), infection (p<0.01), osteomyelitis (p<0.01), prior ulcer history (p<0.05), retinopathy (p<0.05), size of ulcer (p<0.001) and depth of ulcer (p<0.001). The size and depth of an ulcer, prior ulcer history, ischemia and infection were found to be associated with poor prognosis factors of treatment and risk factors of amputation in diabetic foot ulcer patients by a multiple regression test (P<0.05). CONCLUSION: This study shows that the size and depth of an ulcer, prior ulcer history, ischemia and infection are poor prognosis factors of diabetic foot ulcer and amputation risk factors However, further studies will be required due to the smaill size of our study population.

Risk Factors of Peripheral Vascular Disease (PVD) and Nutritional Factors in Diabetic Patients over 60 Years Old Complicated with PVD Diagnosed by Ankle-Brachial Index ( ABI ).: Yoo Sun Chung, Hyung Joon Yoo, Sung O Seo, Hyun Kyu Kim, Doo Man Kim, Jae Myung Yoo, Sung Hee Ihm, Moon Gi Choi, Sung Woo Park; Korean Diabetes J. 1999;23(6):814-821. Published online January 1, 2001

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Abstract PDF: BACKGROUND
The subjects with diabetes mellitus are at high risk for peripheral vascular disease (PVD). The ABI (Ankle-Brachial Index) was done for diagnosis of PVD in diabetes. Numerous studies have been conducted to determine the risk factors for diabetes PVD. Most of the risk factors have been found are largely affected by the age and patients nutritional status to some extent. Especially in older diabetes, risk factors cannot be evaluated by numerical values only, for most patients are in background of poor nutritional support. Therefore, in this study, our aim was to evaluate on the influences of the nutritional status as the risk factors for PVD in older patients, ie., 60 years and older. METHODS: We selected 59 patients who are above 60 years old and took neither anti-hypertensive drug nor lipid lowering agents. All subjects ABI was measured by IMEXLAB 9000 and the study group was stratified according to the ABI values: the normal (ABI >10), PVD group (ABI <0.9). The ABI (Ankle-Brachial Index) was measured by The data were analyzed using one-way analysis of variance. If statistically significant effect was found, post hoc analysis (e.g., Newman-Keuls' test) was performed to evaluate the difference between the groups. The values are expressed as the mean+/-standard error (SE). RESULT: There was significant difference in smoking (ABI < 0.9; 0.54+/-0.16 packs/day, ABI > 1.0; 0.35+/-0.08 packs/day), the serum level triglyceride(ABI < 0.9; 1.960.19 mmol/L, ABI > 1.0; 1.56 + 0.21 mmol/L), HDL-cholesterol(ABI < 0.9; 0.88+/-0.11 mmol/L, ABI > 1.0; 1.10+/-0.08 mmol/1) when compared between the normal and ABI decreased subjects(P < 0.05). However, we found no significant differences in systolic blood pressure, total cholesterol and LDL-C between the two groups. Serum level of the nutritional factors such as albumin, transferrin, total lympocyte count, folate, zinc were lower than the normal values in both groups. However, these levels were not statistically significant when two groups compared. CONCLUSION: The relationship between the known PVD risk factors and PVD in older diabetes was weak. Therefore, based on the findings from this study, we suggest that when investigators interpretate the risk factors of PVD in elderly patients one must consider nutritional effects along the other factors.

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