Diabetes & Metabolism Journal

Original Article

Complications
SUDOSCAN in Combination with the Michigan Neuropathy Screening Instrument Is an Effective Tool for Screening Diabetic Peripheral Neuropathy: Tae Jung Oh, Yoojung Song, Hak Chul Jang, Sung Hee Choi; Diabetes Metab J. 2022;46(2):319-326. Published online September 16, 2021; DOI: https://doi.org/10.4093/dmj.2021.0014

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Background
Screening for diabetic peripheral neuropathy (DPN) is important to prevent severe foot complication, but the detection rate of DPN is unsatisfactory. We investigated whether SUDOSCAN combined with Michigan Neuropathy Screening Instrument (MNSI) could be an effective tool for screening for DPN in people with type 2 diabetes mellitus (T2DM) in clinical practice.
Methods
We analysed the data for 144 people with T2DM without other cause of neuropathy. The presence of DPN was confirmed according to the Toronto Consensus criteria. Electrochemical skin conductance (ESC) of the feet was assessed using SUDOSCAN. We compared the discrimination power of following methods, MNSI only vs. SUDOSCAN only vs. MNSI plus SUDOSCAN vs. MNSI plus 10-g monofilament test.
Results
Confirmed DPN was detected in 27.8% of the participants. The optimal cut-off value of feet ESC to distinguish DPN was 56 μS. We made the DPN screening scores using the corresponding odds ratios for MNSI-Questionnaire, MNSI-Physical Examination, SUDOSCAN, and 10-g monofilament test. For distinguishing the presence of DPN, the MNSI plus SUDOSCAN model showed higher areas under the receiver operating characteristic curve (AUC) than MNSI only model (0.717 vs. 0.638, P=0.011), and SUDOSCAN only model or MNSI plus 10-g monofilament test showed comparable AUC with MNSI only model.
Conclusion
The screening model for DPN that includes both MNSI and SUDOSCAN can detect DPN with acceptable discrimination power and it may be useful in Korean patients with T2DM.

Citations

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Vitamin D deficiency increases the risk of diabetic peripheral neuropathy in elderly type 2 diabetes mellitus patients by predominantly increasing large-fiber lesions
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Early detection of diabetic neuropathy based on health belief model: a scoping review
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Whether coagulation dysfunction influences the onset and progression of diabetic peripheral neuropathy: A multicenter study in middle‐aged and aged patients with type 2 diabetes
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Peripheral Neuropathy in Diabetes Mellitus: Pathogenetic Mechanisms and Diagnostic Options
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Neurophysiologie Clinique.2023; 53(2): 102859. CrossRef
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Primary Care Diabetes.2023; 17(5): 499. CrossRef
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Jean-Pierre Riveline, Roberto Mallone, Clarisse Tiercelin, Fetta Yaker, Laure Alexandre-Heymann, Lysa Khelifaoui, Florence Travert, Claire Fertichon, Jean-Baptiste Julla, Tiphaine Vidal-Trecan, Louis Potier, Jean-Francois Gautier, Etienne Larger, Jean-Pas
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Ana Cristina García-Ulloa, Paloma Almeda-Valdes, Teresa Enedina Cuatecontzi-Xochitiotzi, Jorge Alberto Ramírez-García, Michelle Díaz-Pineda, Fernanda Garnica-Carrillo, Alejandra González-Duarte, K M Venkat Narayan, Carlos Alberto Aguilar-Salinas, Sergio H
BMJ Open Diabetes Research & Care.2022; 10(6): e003005. CrossRef

Brief Report

Complications
Diabetic Retinopathy and Related Clinical Practice for People with Diabetes in Korea: A 10-Year Trend Analysis: Yoo-Ri Chung, Kyoung Hwa Ha, Kihwang Lee, Dae Jung Kim; Diabetes Metab J. 2020;44(6):928-932. Published online July 10, 2020; DOI: https://doi.org/10.4093/dmj.2020.0096

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We performed a retrospective cohort study including people diagnosed with diabetes from 2006 to 2015 according to the Korean National Health Insurance Service-National Sample Cohort database, to analyze the changes in the prevalence, screening rate, and treatment patterns for diabetic retinopathy (DR) over 10 years. The proportion of people who underwent fundus screening for DR steadily increased over the past decade. The prevalence of DR increased from 13.4% in 2006 to 15.9% in 2015, while that of proliferative DR steadily decreased from 1.29% in 2006 to 1.16% in 2015. The proportion of patients undergoing retinal photocoagulation constantly decreased. The prevalence of DR increased over the past decade, while its severity seemed to have improved, with a decreased rate of proliferative DR and retinal photocoagulation. A higher proportion of patients underwent ophthalmic screening using fundus examination, but still less than 30% of patients with diabetes underwent comprehensive examination in 2015.

Citations

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Present and future screening programs for diabetic retinopathy: a narrative review
Andreas Abou Taha, Sebastian Dinesen, Anna Stage Vergmann, Jakob Grauslund
International Journal of Retina and Vitreous.2024;[Epub] CrossRef
Trends and Barriers in Diabetic Retinopathy Screening: Korea National Health and Nutritional Examination Survey 2016–2021
Min Seok Kim, Sang Jun Park, Kwangsic Joo, Se Joon Woo
Journal of Korean Medical Science.2024;[Epub] CrossRef
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BMC Public Health.2023;[Epub] CrossRef
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Sang-Yeob Kim, Byeong-Yeon Moon, Hyun-Gug Cho, Dong-Sik Yu
International Journal of Environmental Research and Public Health.2022; 19(14): 8689. CrossRef
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Han Na Jang, Min Kyong Moon, Bo Kyung Koo
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Prevalence and Risk Factors of Diabetic Retinopathy in Diabetes People using Korean National Health and Nutrition Examination Survey VII
Ihn Sook Jeong, Chan Mi Kang
Journal of Korean Academy of Community Health Nursing.2022; 33(4): 408. CrossRef
Time to Reach Target Glycosylated Hemoglobin Is Associated with Long-Term Durable Glycemic Control and Risk of Diabetic Complications in Patients with Newly Diagnosed Type 2 Diabetes Mellitus: A 6-Year Observational Study (Diabetes Metab J 2021;45:368-78)
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Diabetes & Metabolism Journal.2021; 45(4): 613. CrossRef

Original Article

Metabolic Risk/Epidemiology
A Comparison of Predictive Performances between Old versus New Criteria in a Risk-Based Screening Strategy for Gestational Diabetes Mellitus: Subeen Hong, Seung Mi Lee, Soo Heon Kwak, Byoung Jae Kim, Ja Nam Koo, Ig Hwan Oh, Sohee Oh, Sun Min Kim, Sue Shin, Won Kim, Sae Kyung Joo, Errol R. Norwitz, Souphaphone Louangsenlath, Chan-Wook Park, Jong Kwan Jun, Joong Shin Park; Diabetes Metab J. 2020;44(5):726-736. Published online April 13, 2020; DOI: https://doi.org/10.4093/dmj.2019.0126

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Background

The definition of the high-risk group for gestational diabetes mellitus (GDM) defined by the American College of Obstetricians and Gynecologists was changed from the criteria composed of five historic/demographic factors (old criteria) to the criteria consisting of 11 factors (new criteria) in 2017. To compare the predictive performances between these two sets of criteria.

Methods

This is a secondary analysis of a large prospective cohort study of non-diabetic Korean women with singleton pregnancies designed to examine the risk of GDM in women with nonalcoholic fatty liver disease. Maternal fasting blood was taken at 10 to 14 weeks of gestation and measured for glucose and lipid parameters. GDM was diagnosed by the two-step approach.

Results

Among 820 women, 42 (5.1%) were diagnosed with GDM. Using the old criteria, 29.8% (n=244) of women would have been identified as high risk versus 16.0% (n=131) using the new criteria. Of the 42 women who developed GDM, 45.2% (n=19) would have been mislabeled as not high risk by the old criteria versus 50.0% (n=21) using the new criteria (1-sensitivity, 45.2% vs. 50.0%, P>0.05). Among the 778 patients who did not develop GDM, 28.4% (n=221) would have been identified as high risk using the old criteria versus 14.1% (n=110) using the new criteria (1-specificity, 28.4% vs. 14.1%, P<0.001).

Conclusion

Compared with the old criteria, use of the new criteria would have decreased the number of patients identified as high risk and thus requiring early GDM screening by half (from 244 [29.8%] to 131 [16.0%]).

Citations

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Endocrinology and Metabolism.2023; 38(1): 129. CrossRef
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Clinical Gastroenterology and Hepatology.2022; 20(11): 2542. CrossRef
Nonalcoholic fatty liver disease and early prediction of gestational diabetes mellitus using machine learning methods
Seung Mi Lee, Suhyun Hwangbo, Errol R. Norwitz, Ja Nam Koo, Ig Hwan Oh, Eun Saem Choi, Young Mi Jung, Sun Min Kim, Byoung Jae Kim, Sang Youn Kim, Gyoung Min Kim, Won Kim, Sae Kyung Joo, Sue Shin, Chan-Wook Park, Taesung Park, Joong Shin Park
Clinical and Molecular Hepatology.2022; 28(1): 105. CrossRef
Nonalcoholic fatty liver disease-based risk prediction of adverse pregnancy outcomes: Ready for prime time?
Seung Mi Lee, Won Kim
Clinical and Molecular Hepatology.2022; 28(1): 47. CrossRef
Postprandial Free Fatty Acids at Mid-Pregnancy Increase the Risk of Large-for-Gestational-Age Newborns in Women with Gestational Diabetes Mellitus
So-Yeon Kim, Young Shin Song, Soo-Kyung Kim, Yong-Wook Cho, Kyung-Soo Kim
Diabetes & Metabolism Journal.2022; 46(1): 140. CrossRef
Effect of Different Types of Diagnostic Criteria for Gestational Diabetes Mellitus on Adverse Neonatal Outcomes: A Systematic Review, Meta-Analysis, and Meta-Regression
Fahimeh Ramezani Tehrani, Marzieh Saei Ghare Naz, Razieh Bidhendi-Yarandi, Samira Behboudi-Gandevani
Diabetes & Metabolism Journal.2022; 46(4): 605. CrossRef
Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning
Seung Mi Lee, Yonghyun Nam, Eun Saem Choi, Young Mi Jung, Vivek Sriram, Jacob S. Leiby, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim,
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The Clinical Characteristics of Gestational Diabetes Mellitus in Korea: A National Health Information Database Study
Kyung-Soo Kim, Sangmo Hong, Kyungdo Han, Cheol-Young Park
Endocrinology and Metabolism.2021; 36(3): 628. CrossRef
The risk of pregnancy‐associated hypertension in women with nonalcoholic fatty liver disease
Young Mi Jung, Seung Mi Lee, Subeen Hong, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan‐Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
Liver International.2020; 40(10): 2417. CrossRef

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