Prediction of pre-eclampsia in nulliparous women using routinely collected maternal characteristics: a model development and validation study
Prediction of pre-eclampsia in nulliparous women using routinely collected maternal characteristics: a model development and validation study
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DOI：
10.1186/s12884-019-2712-x
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发表时间：
2020-01-06
影响因子：
3.1
通讯作者：
Lord, Sarah J.
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文献类型：
--
作者：
Al-Rubaie, Ziad T. A.;Hudson, H. Malcolm;Lord, Sarah J.
背景指南建议在妊娠早期识别先兆子痫风险升高的妇女。本研究的目的是开发和验证一个先兆子痫的风险预测模型，为未经产的妇女参加常规产前保健“西悉尼（WS）模型”;并将其表现与国家卫生和护理卓越研究所（NICE）的风险因素列表方法进行比较，将女性分类为高风险，该回顾性队列研究包括2011-2014年在澳大利亚西悉尼当地卫生区的三家公立医院分娩的所有未经产妇女。使用2011年至2012年的出生，多变量logistic回归纳入了已建立的孕产妇风险因素，以开发和内部验证WS模型。然后，使用2013年至2014年的出生人数对WS模型进行外部验证，评估其歧视和校准。我们拟合了2011年至2014年所有出生的最终WS模型，并将其预测先兆子痫的准确性与NICE approach.ResultsAmong 12，395生育未经产的妇女在2011-2014年，有293（2.4%）先兆子痫事件。WS模型包括：母亲年龄、体重指数、种族、多胎妊娠、先兆子痫家族史、自身免疫性疾病、慢性高血压和慢性肾病。在验证样本（6201例出生）中，模型c-统计量为0.70（95%置信区间0.65-0.75）。先兆子痫的观察：预期比值为0.91，Hosmer-Lemeshow拟合优度检验p值为0.20。在整个研究样本的12，395名新生儿中，374名（3.0%）妇女的WS模型估计的先兆子痫风险>= 8%，这是考虑阿司匹林预防的预先规定的风险阈值。其中，54例（14.4%）发展为先兆子痫（敏感性18%（14-23），特异性97%（97-98））。使用NICE方法，1173名（9.5%）妇女被归类为高风险，其中107名（9.1%）发展为先兆子痫（敏感性37%（31-42），特异性91%（91-92））。最终的模型表现出类似的准确性NICE的方法时，使用较低的风险阈值>= 4%，将妇女归类为高风险的先兆子痫。ConclusionThe WS风险模型，结合现成的产妇特征，实现了适度的性能预测先兆子痫在未经产的妇女。该模型没有优于NICE方法，但具有提供个体化绝对风险估计的优势，以协助咨询，为进一步检测的决策提供信息，并考虑阿司匹林预防。
BackgroundGuidelines recommend identifying in early pregnancy women at elevated risk of pre-eclampsia. The aim of this study was to develop and validate a pre-eclampsia risk prediction model for nulliparous women attending routine antenatal care "the Western Sydney (WS) model"; and to compare its performance with the National Institute of Health and Care Excellence (NICE) risk factor-list approach for classifying women as high-risk.MethodsThis retrospective cohort study included all nulliparous women who gave birth in three public hospitals in the Western-Sydney-Local-Health-District, Australia 2011-2014. Using births from 2011 to 2012, multivariable logistic regression incorporated established maternal risk factors to develop and internally validate the WS model. The WS model was then externally validated using births from 2013 to 2014, assessing its discrimination and calibration. We fitted the final WS model for all births from 2011 to 2014, and compared its accuracy in predicting pre-eclampsia with the NICE approach.ResultsAmong 12,395 births to nulliparous women in 2011-2014, there were 293 (2.4%) pre-eclampsia events. The WS model included: maternal age, body mass index, ethnicity, multiple pregnancy, family history of pre-eclampsia, autoimmune disease, chronic hypertension and chronic renal disease. In the validation sample (6201 births), the model c-statistic was 0.70 (95% confidence interval 0.65-0.75). The observed:expected ratio for pre-eclampsia was 0.91, with a Hosmer-Lemeshow goodness-of-fit test p-value of 0.20. In the entire study sample of 12,395 births, 374 (3.0%) women had a WS model-estimated pre-eclampsia risk >= 8%, the pre-specified risk-threshold for considering aspirin prophylaxis. Of these, 54 (14.4%) developed pre-eclampsia (sensitivity 18% (14-23), specificity 97% (97-98)). Using the NICE approach, 1173 (9.5%) women were classified as high-risk, of which 107 (9.1%) developed pre-eclampsia (sensitivity 37% (31-42), specificity 91% (91-92)). The final model showed similar accuracy to the NICE approach when using lower risk-threshold of >= 4% to classify women as high-risk for pre-eclampsia.ConclusionThe WS risk model that combines readily-available maternal characteristics achieved modest performance for prediction of pre-eclampsia in nulliparous women. The model did not outperform the NICE approach, but has the advantage of providing individualised absolute risk estimates, to assist with counselling, inform decisions for further testing, and consideration of aspirin prophylaxis.