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Prediction of gestational diabetes mellitus in the Born in Guangzhou Cohort Study, China
Author(s) -
Schaefer Kimberly K.,
Xiao Wanqing,
Chen Qiaozhu,
He Jianrong,
Lu Jinhua,
Chan Fanfan,
Chen Niannian,
Yuan Mingyang,
Xia Huimin,
Lam Kin Bong Hubert,
Hirst Jane E.,
Qiu Xiu
Publication year - 2018
Publication title -
international journal of gynecology and obstetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.895
H-Index - 97
eISSN - 1879-3479
pISSN - 0020-7292
DOI - 10.1002/ijgo.12627
Subject(s) - medicine , gestational diabetes , cohort , diabetes mellitus , china , cohort study , obstetrics , pediatrics , gestation , pregnancy , endocrinology , biology , political science , law , genetics
Objective To assess potential risk factors in identifying women at risk for gestational diabetes mellitus ( GDM ). Methods The present study included data collected as part of a prospective cohort study, and included women with singleton pregnancies who underwent initial prenatal examination at a tertiary women and children's hospital in Guangzhou, China between February 1, 2012, and December 31, 2015. Maternal characteristics and medical history were investigated to evaluate associations with GDM . A risk factor scoring system for the prediction of GDM was generated using logistic regression. Results Overall, 1129 (13.5%) of 8381 women were diagnosed with GDM . Women older than 35 years had a 3.95‐fold increased risk of GDM (95% confidence interval 2.80–5.58) compared with women aged 16–25 years; obese women had a 6.54‐fold higher risk (95% confidence interval 3.50–12.23) compared with underweight women. A risk scoring system was established based on age, body mass index, family history of diabetes, weight gain, and history of GDM . Screening for women with a score of 12 or more would have reduced the number undergoing oral glucose tolerance testing by 2131 (25.4%) patients with a sensitivity of 87% for GDM detection. Conclusion The assessment of risk factors for GDM could provide a foundation for improving risk‐based screening strategies in this and similar populations.

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