Diabetes & Metabolism Journal

Sohee Oh (Oh S)

2 Articles

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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Abstract PDF Supplementary Material PubReader ePub

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

Citations to this article as recorded by

Multi-omics reveals the beneficial effect of Scytosiphon lomentaria fucoidan on glucose and lipid metabolism disorders via regulation of the gut-liver axis in pregnant mice
Shuangru Tang, Weiyun Zheng, Xiaomeng Ren, Shuang Song, Chunqing Ai
Food Bioscience.2024; 62: 105436. CrossRef
Predicting the Risk of Insulin-Requiring Gestational Diabetes before Pregnancy: A Model Generated from a Nationwide Population-Based Cohort Study in Korea
Seung-Hwan Lee, Jin Yu, Kyungdo Han, Seung Woo Lee, Sang Youn You, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Mee Kyoung Kim
Endocrinology and Metabolism.2023; 38(1): 129. CrossRef
Metabolic Dysfunction-Associated Fatty Liver Disease and Subsequent Development of Adverse Pregnancy Outcomes
Seung Mi Lee, Young Mi Jung, Eun Saem Choi, Soo Heon Kwak, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Bo Kyung Koo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim, Joong Shin Park
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,
Scientific Reports.2022;[Epub] CrossRef
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

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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282 Download
18 Web of Science
20 Crossref

Abstract PDF Supplementary Material PubReader

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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