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Diabetes after pregnancy: a study protocol for the derivation and validation of a risk prediction model for 5-year risk of diabetes following pregnancy

机译:怀孕后的糖尿病:妊娠后5年糖尿病风险预测模型的衍生和验证的研究方案

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Background Pregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman’s 5-year risk of developing type 2 DM after pregnancy. Methods Data will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke’s R 2 ), discrimination (C-statistics), and calibration plots will be generated. Internal validation will be conducted using a bootstrapping approach in 500 samples with replacement, and an optimism-corrected C-statistic will be calculated. External validation of the RPM will be conducted by applying the model in a large population-based pregnancy cohort in Alberta, and estimating the above measures of model performance. The model will be re-calibrated by adjusting baseline hazards and coefficients where appropriate. Discussion The derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.
机译:背景技术怀孕提供了一个独特的机会,以识别患有2型糖尿病(DM)的未来未来的妇女。在怀孕期间,一个女性与医疗保健系统更加接近,并且某些条件更容易表现出来,例如妊娠期DM(GDM),这是未来DM风险的重要标记。本研究协议描述了风险预测模型(RPM)的开发和验证,用于估算怀孕后2 dm的妇女的5年风险。方法数据将从现有的基于Ontario群体的管理数据集获得。衍生队队伍将包括在2006年4月至2014年4月至2014年间加拿大安大略省出生的所有妇女。预先指定的预测因素将包括社会人口因素(交付,种族),母体临床因素(例如,体重指数) ,妊娠相关事件(妊娠期DM,怀孕高血压疾病)和新生儿因子(出生服百分位数)。事件类型2 DM将通过链接到Ontario糖尿病数据库。将开发Weibull加速故障时间模型以预测2 DM的5年风险。将产生预测准确度的措施(Nagelkerke的R 2),歧视(C统计)和校准图。内部验证将在使用500个样本中使用替换的自举方法进行,并且将计算乐观校正的C统计信息。将通过在艾伯塔省的大型人口妊娠队列中应用模型来进行RPM的外部验证,并估算上述模型性能措施。通过调整适当的基线危险和系数来重新校准该模型。讨论衍生的rpm可能有助于在怀孕后的5年期间识别高风险的妇女在妊娠后的5年期间,促进风险较高的女性的生活方式,以及怀孕后2 dm的更频繁筛查。

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