Diabetes & Metabolism Journal

Original Articles

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; Received July 21, 2024 Accepted January 23, 2025 Published online May 21, 2025; DOI: https://doi.org/10.4093/dmj.2024.0406 [Epub ahead of print]

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Abstract PDF Supplementary Material PubReader ePub: 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.

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; Received June 20, 2024 Accepted January 6, 2025 Published online May 21, 2025; DOI: https://doi.org/10.4093/dmj.2024.0319 [Epub ahead of print]

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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.

Complications
Connection between Impaired Fasting Glucose or Type 2 Diabetes Mellitus and Sepsis: A 10-Year Observational Data from the National Health Screening Cohort: Eun Hwa Lee, Kyoung Hwa Lee, Kyu-na Lee, Yebin Park, Kyung Do Han, Sang Hoon Han; Diabetes Metab J. 2025;49(3):485-497. Published online February 17, 2025; DOI: https://doi.org/10.4093/dmj.2024.0387

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The mortality of sepsis without direct drugs is high. The association between prediabetes, based on a single fasting glucose (FG), or long-term type 2 diabetes mellitus (T2DM) and sepsis remains unclear.
Methods
Of the adults aged ≥20 years who were included in the National Health Screening Program (NHSP) in 2009, 40% were randomly sampled. After excluding patients with type 1 diabetes mellitus, with missing information, and who were diagnosed with sepsis during the wash-out (between 2001 and the NHSP) or 1-year lag period, a cohort comprised of 3,863,323 examinees. Body mass index (BMI) measurements, FG tests, and self-reported questionnaires on health-related behaviors were conducted. Individual information was followed up until 2020 and censored upon the first occurrence of sepsis or death. The incidence of sepsis was compared using a multivariable regression adjusted for age, sex, income, BMI, smoking, drinking, physical activity levels, and chronic diseases.
Results
The cohort was divided into those with normal FG (n=2,675,476), impaired fasting glucose (IFG) (n=890,402, 23.0%), T2DM <5 years (n=212,391, 5.5%), or T2DM for ≥5 years (n=85,054, 2.2%). The groups with IFG (adjusted hazard ratio [aHR], 1.03; 95% confidence interval [CI], 1.01 to 1.05), T2DM <5 years (aHR, 1.43; 95% CI, 1.40 to 1.47), and T2DM for ≥5 years (aHR, 1.82; 95% CI, 1.77 to 1.87) exhibited significantly higher incidence of sepsis (P<0.001), with the greatest risk in patients with T2DM aged <40 years (aHR, 1.96; 95% CI, 1.71 to 2.25).
Conclusion
Patients with long-standing and young-onset T2DM show a substantially high risk of sepsis, emphasizing the need for infection prevention and vaccination.

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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Social determinants of health and type 2 diabetes in Asia
Kyunghun Sung, Seung‐Hwan Lee
Journal of Diabetes Investigation.2025;[Epub] CrossRef

Original Article

Genetics
Identification and Potential Clinical Utility of Common Genetic Variants in Gestational Diabetes among Chinese Pregnant Women: Claudia Ha-ting Tam, Ying Wang, Chi Chiu Wang, Lai Yuk Yuen, Cadmon King-poo Lim, Junhong Leng, Ling Wu, Alex Chi-wai Ng, Yong Hou, Kit Ying Tsoi, Hui Wang, Risa Ozaki, Albert Martin Li, Qingqing Wang, Juliana Chung-ngor Chan, Yan Chou Ye, Wing Hung Tam, Xilin Yang, Ronald Ching-wan Ma; Diabetes Metab J. 2025;49(1):128-143. Published online September 20, 2024; DOI: https://doi.org/10.4093/dmj.2024.0139

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Background
The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications.
Methods
We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants.
Results
Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI], 1.38 to 1.96), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; P_meta=7.6×10^-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; P_meta=3.1×10^-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals.
Conclusion
Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Citations

Citations to this article as recorded by

GWAS in Gestational Diabetes Mellitus: Research Advances
Dikun Zhou, Z. Shi, A.H. Hashash, Z.H. Khan
BIO Web of Conferences.2025; 174: 01018. CrossRef
Advancing Early Prediction of Gestational Diabetes Mellitus with Circular RNA Biomarkers
Joon Ho Moon, Sung Hee Choi
Diabetes & Metabolism Journal.2025; 49(3): 403. CrossRef
Hexokinase Domain Containing 1 (HKDC1) Gene Variants and Their Association With Gestational Diabetes Mellitus: A Mini-Review
Sekar Kanthimathi, Polina Popova, Viswanathan Mohan, Wesley Hannah, Ranjit Mohan Anjana, Venkatesan Radha
Journal of Diabetology.2024; 15(4): 354. CrossRef

Review

Drug/Regimen
Benefit and Safety of Sodium-Glucose Co-Transporter 2 Inhibitors in Older Patients with Type 2 Diabetes Mellitus: Ja Young Jeon, Dae Jung Kim; Diabetes Metab J. 2024;48(5):837-846. Published online September 1, 2024; DOI: https://doi.org/10.4093/dmj.2024.0317

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People with type 2 diabetes mellitus (T2DM) are at higher risk of developing cardiovascular disease, heart failure, chronic kidney disease, and premature death than people without diabetes. Therefore, treatment of diabetes aims to reduce these complications. Sodium-glucose co-transporter 2 (SGLT2) inhibitors have shown beneficial effects on cardiorenal and metabolic health beyond glucose control, making them a promising class of drugs for achieving the ultimate goals of diabetes treatment. However, despite their proven benefits, the use of SGLT2 inhibitors in eligible patients with T2DM remains suboptimal due to reports of adverse events. The use of SGLT2 inhibitors is particularly limited in older patients with T2DM because of the lack of treatment experience and insufficient long-term safety data. This article comprehensively reviews the risk-benefit profile of SGLT2 inhibitors in older patients with T2DM, drawing on data from prospective randomized controlled trials of cardiorenal outcomes, original studies, subgroup analyses across different age groups, and observational cohort studies.

Citations

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Trends in prescribing sodium‐glucose cotransporter 2 inhibitors for individuals with type 2 diabetes with and without cardiovascular‐renal disease in South Korea, 2015–2021
Kyoung Hwa Ha, Soyoung Shin, EunJi Na, Dae Jung Kim
Journal of Diabetes Investigation.2025; 16(2): 215. CrossRef
Pharmacological management of diabetes in older adults
Junghyun Noh
Cardiovascular Prevention and Pharmacotherapy.2025; 7(1): 13. CrossRef
Challenges, current innovations, and opportunities for managing type 2 diabetes in frail older adults: a position paper of the European Geriatric Medicine Society (EuGMS)—Special Interest Group in Diabetes
Virginia Boccardi, Gülistan Bahat, Cafer Balci, Isabelle Bourdel-Marchasson, Antoine Christiaens, Lorenzo Maria Donini, Sibel Cavdar, Stefania Maggi, Serdar Özkök, Tajana Pavic, Stany Perkisas, Stefano Volpato, Muhammad Shoaib Zaidi, Andrej Zeyfang, Alan
European Geriatric Medicine.2025;[Epub] 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

Citations to this article as recorded by

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

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

Review

Others
Risk Prediction and Management of Chronic Kidney Disease in People Living with Type 2 Diabetes Mellitus: Ying-Guat Ooi, Tharsini Sarvanandan, Nicholas Ken Yoong Hee, Quan-Hziung Lim, Sharmila S. Paramasivam, Jeyakantha Ratnasingam, Shireene R. Vethakkan, Soo-Kun Lim, Lee-Ling Lim; Diabetes Metab J. 2024;48(2):196-207. Published online January 26, 2024; DOI: https://doi.org/10.4093/dmj.2023.0244

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People with type 2 diabetes mellitus have increased risk of chronic kidney disease and atherosclerotic cardiovascular disease. Improved care delivery and implementation of guideline-directed medical therapy have contributed to the declining incidence of atherosclerotic cardiovascular disease in high-income countries. By contrast, the global incidence of chronic kidney disease and associated mortality is either plateaued or increased, leading to escalating direct and indirect medical costs. Given limited resources, better risk stratification approaches to identify people at risk of rapid progression to end-stage kidney disease can reduce therapeutic inertia, facilitate timely interventions and identify the need for early nephrologist referral. Among people with chronic kidney disease G3a and beyond, the kidney failure risk equations (KFRE) have been externally validated and outperformed other risk prediction models. The KFRE can also guide the timing of preparation for kidney replacement therapy with improved healthcare resources planning and may prevent multiple complications and premature mortality among people with chronic kidney disease with and without type 2 diabetes mellitus. The present review summarizes the evidence of KFRE to date and call for future research to validate and evaluate its impact on cardiovascular and mortality outcomes, as well as healthcare resource utilization in multiethnic populations and different healthcare settings.

Citations

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A Machine Learning-Based Prediction Model for Diabetic Kidney Disease in Korean Patients with Type 2 Diabetes Mellitus
Kyung Ae Lee, Jong Seung Kim, Yu Ji Kim, In Sun Goak, Heung Yong Jin, Seungyong Park, Hyejin Kang, Tae Sun Park
Journal of Clinical Medicine.2025; 14(6): 2065. CrossRef
Chronic Kidney Disease in Diabetes: A Clinical Practice Guideline
Sheldon W. Tobe, Harpreet S. Bajaj, Navdeep Tangri, Rahul Jain, Thuy Pham, Valerie Beaudin, Phil McFarlane
Canadian Journal of Diabetes.2025; 49(2): 73. CrossRef
Prevalence of diabetes and its associated factors in Cape Verde: an analysis of the 2020 WHO STEPS survey on non-communicable diseases risk factors
Joshua Okyere, Castro Ayebeng, Kwamena Sekyi Dickson
BMC Endocrine Disorders.2024;[Epub] CrossRef

Original Articles

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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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
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
Sub‐Acromioclavicular Decompression Increases the Risk of Postoperative Shoulder Stiffness after Arthroscopic Rotator Cuff Repair
Cheng Li, Zhiling Wang, Maslah Idiris Ali, Yi Long, Ymuhanmode Alike, Min Zhou, Dedong Cui, Zhenze Zheng, Ke Meng, Jingyi Hou, Rui Yang
Orthopaedic Surgery.2024; 16(12): 2942. CrossRef
A comprehensive scoring system for the diagnosis and staging of adhesive capsulitis: development, application, and implications
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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Abstract PDF Supplementary Material PubReader ePub: 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.

Review

Complications
Dyslipidemia in Patients with Chronic Kidney Disease: An Updated Overview: Sang Heon Suh, Soo Wan Kim; Diabetes Metab J. 2023;47(5):612-629. Published online July 24, 2023; DOI: https://doi.org/10.4093/dmj.2023.0067

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Dyslipidemia is a potentially modifiable cardiovascular risk factor. Whereas the recommendations for the treatment target of dyslipidemia in the general population are being more and more rigorous, the 2013 Kidney Disease: Improving Global Outcomes clinical practice guideline for lipid management in chronic kidney disease (CKD) presented a relatively conservative approach with respect to the indication of lipid lowering therapy and therapeutic monitoring among the patients with CKD. This may be largely attributed to the lack of high-quality evidence derived from CKD population, among whom the overall feature of dyslipidemia is considerably distinctive to that of general population. In this review article, we cover the characteristic features of dyslipidemia and impact of dyslipidemia on cardiovascular outcomes in patients with CKD. We also review the current evidence on lipid lowering therapy to modify the risk of cardiovascular events in this population. We finally discuss the association between dyslipidemia and CKD progression and the potential strategy to delay the progression of CKD in relation to lipid lowering therapy.

Citations

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Impact of remnant cholesterol on short-term and long-term prognosis in patients with prediabetes or diabetes undergoing coronary artery bypass grafting: a large-scale cohort study
Zhongchen Li, Chunyu Yu, Heng Zhang, Runze Chen, Yan Zhao, Zhe Zheng
Cardiovascular Diabetology.2025;[Epub] CrossRef
Effects of Tocotrienol on Cardiovascular Risk Markers in Patients With Chronic Kidney Disease: A Randomized Controlled Trial
Liana Trugilho, Lívia Alvarenga, Ludmila Cardozo, Bruna Paiva, Jessyca Brito, Isis Barboza, Jonatas Almeida, Juliana dos Anjos, Pramod Khosla, Marcelo Ribeiro-Alves, Denise Mafra, Eric Gumpricht
Journal of Nutrition and Metabolism.2025;[Epub] CrossRef
The Impact of Glomerular Disease on Dyslipidemia in Pediatric Patients Treated with Dialysis
Edward Zitnik, Elani Streja, Marciana Laster
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Original Articles

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.

Citations

Citations to this article as recorded by

Accounting for time-varying exposures and covariates in the relationship between obesity and diabetes: analysis using parametric g-formula
Boyoung Park, Junghyun Yoon, Thi Xuan Mai Tran
Journal of Epidemiology and Community Health.2024; 78(11): 729. CrossRef
Association of Uterine Leiomyoma with Type 2 Diabetes Mellitus in Young Women: A Population-Based Cohort Study
Ji-Hee Sung, Kyung-Soo Kim, Kyungdo Han, Cheol-Young Park
Diabetes & Metabolism Journal.2024; 48(6): 1105. CrossRef

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.

Citations

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Dysuricemia—A New Concept Encompassing Hyperuricemia and Hypouricemia
Naoyuki Otani, Motoshi Ouchi, Einosuke Mizuta, Asuka Morita, Tomoe Fujita, Naohiko Anzai, Ichiro Hisatome
Biomedicines.2023; 11(5): 1255. CrossRef
Association of Body Mass Index and Fracture Risk Varied by Affected Bones in Patients with Diabetes: A Nationwide Cohort Study (Diabetes Metab J 2023;47:242-54)
Se-Won Lee, Kyungdo Han, Hyuk-Sang Kwon
Diabetes & Metabolism Journal.2023; 47(3): 439. CrossRef
Association of Body Mass Index and Fracture Risk Varied by Affected Bones in Patients with Diabetes: A Nationwide Cohort Study (Diabetes Metab J 2023;47:242-54)
So Young Park
Diabetes & Metabolism Journal.2023; 47(3): 437. CrossRef
Effect of SGLT2 inhibitors on fractures, BMD, and bone metabolism markers in patients with type 2 diabetes mellitus: a systematic review and meta-analysis
Xin Wang, Fengyi Zhang, Yufeng Zhang, Jiayi Zhang, Yingli Sheng, Wenbo Wang, Yujie Li
Osteoporosis International.2023; 34(12): 2013. CrossRef

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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