School of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, Australia; Centre for Behavioural Research in Cancer, Cancer Council Victoria, Melbourne, Australia; Discipline of Obstetrics and Gynaecology, Robinson Research Institute, The University of Adelaide, Adelaide, South Australia, Australia.
Department of Public Health, Centre for Medical Decision Sciences, Erasmus MC, Rotterdam, the Netherlands.
Diabetes Res Clin Pract. 2018 Dec;146:48-57. doi: 10.1016/j.diabres.2018.09.021. Epub 2018 Oct 5.
To develop a prediction model for preconception identification of women at risk of gestational diabetes mellitus (GDM).
Data from a prospective cohort, the Australian Longitudinal Study on Women's Health, were used. Nulliparous women aged 18-23 who reported a pregnancy up to age 37-42 were included. Preconception predictors of GDM during a first pregnancy were selected using logistic regression. Regression coefficients were multiplied by a shrinkage factor estimated with bootstrapping to improve prediction in external populations.
Among 6504 women, 314 (4.8%) developed GDM during their first pregnancy. The final prediction model included age at menarche, proposed age at future first pregnancy, ethnicity, body mass index, diet, physical activity, polycystic ovary syndrome, and family histories of type 1 or 2 diabetes and GDM. The model showed good discriminative ability with a C-statistic of 0.79 (95% CI 0.76, 0.83) after internal validation. More than half of the women (58%) were classified to be at risk of GDM (>2% predicted risk), with corresponding sensitivity and specificity values of 91% and 43%.
Nulliparous women at risk of GDM in a future first pregnancy can be accurately identified based on preconception lifestyle and health-related characteristics. Further studies are needed to test our model in other populations.
开发一种预测模型，用于识别有患妊娠糖尿病（GDM）风险的孕妇。
使用前瞻性队列澳大利亚妇女健康纵向研究的数据。纳入年龄在 18-23 岁之间、报告至 37-42 岁怀孕的初产妇。使用逻辑回归选择首次妊娠期间 GDM 的孕前预测因素。通过自举法估计收缩因子来对回归系数进行乘法运算，以改善在外部人群中的预测。
在 6504 名女性中，有 314 名（4.8%）在首次妊娠期间患上 GDM。最终的预测模型包括初潮年龄、未来首次妊娠年龄、种族、体重指数、饮食、身体活动、多囊卵巢综合征，以及 1 型或 2 型糖尿病和 GDM 的家族史。该模型在内部验证后显示出良好的区分能力，C 统计量为 0.79（95%CI 0.76，0.83）。超过一半的女性（58%）被归类为 GDM 风险较高（>2%的预测风险），其相应的敏感性和特异性值分别为 91%和 43%。
根据孕前生活方式和与健康相关的特征，可以准确识别未来首次妊娠中患有 GDM 的初产妇。需要进一步的研究来在其他人群中测试我们的模型。
