Ukah U Vivian, Payne Beth, Lee Tang, Magee Laura A, von Dadelszen Peter
From the Department of Obstetrics and Gynaecology (U.V.U., T.L.) and Department of Anaesthesiology (B.P.), University of British Columbia, Vancouver, Canada; Healthy Starts Theme, BC Children's Hospital Research, Vancouver, Canada (U.V.U., B.P., T.L.); Molecular and Clinical Sciences Research Institute, St George's, University of London, United Kingdom (L.A.M., P.v.D.); and Department of Obstetrics and Gynaecology, St George's University Hospitals, NHS Foundation Trust, London, United Kingdom (L.A.M., P.v.D.).
Hypertension. 2017 Apr;69(4):705-711. doi: 10.1161/HYPERTENSIONAHA.116.08706. Epub 2017 Feb 6.
The hypertensive disorders of pregnancy are leading causes of maternal mortality and morbidity, especially in low- and middle-income countries. Early identification of women with preeclampsia and other hypertensive disorders of pregnancy at high risk of complications will aid in reducing this health burden. The fullPIERS model (Preeclampsia Integrated Estimate of Risk) was developed for predicting adverse maternal outcomes from preeclampsia using data from tertiary centers in high-income countries and uses maternal demographics, signs, symptoms, and laboratory tests as predictors. We aimed to assess the validity of the fullPIERS model in women with the hypertensive disorders of pregnancy in low-resourced hospital settings. Using miniPIERS data collected on women admitted with hypertensive disorders of pregnancy between July 2008 and March 2012 in 7 hospitals in 5 low- and middle-income countries, the predicted probability of developing an adverse maternal outcome was calculated for each woman using the fullPIERS equation. Missing predictor values were imputed using multivariate imputation by chained equations. The performance of the model was evaluated for discrimination, calibration, and stratification capacity.Among 757 women with complete predictor data (complete-case analyses), the fullPIERS model had a good area under the receiver-operating characteristic curve of 0.77 (95% confidence interval, 0.72-0.82) with poor calibration (<0·001 for the Hosmer-Lemeshow goodness-of-fit test). Performance as a rule-in tool was moderate (likelihood ratio: 5.9; 95% confidence interval, 4.23-8.35) for women with ≥30% predicted probability of an adverse outcome. The fullPIERS model may be used in low-resourced setting hospitals to identify women with hypertensive disorders of pregnancy at high risk of adverse maternal outcomes in need of immediate interventions.
妊娠高血压疾病是孕产妇死亡和发病的主要原因，尤其是在低收入和中等收入国家。早期识别患有先兆子痫和其他妊娠高血压疾病且有并发症高风险的妇女，将有助于减轻这一健康负担。完整的PIERS模型（先兆子痫综合风险评估模型）是利用高收入国家三级医疗中心的数据开发的，用于预测先兆子痫的不良孕产妇结局，并将孕产妇人口统计学特征、体征、症状和实验室检查作为预测指标。我们旨在评估完整的PIERS模型在资源匮乏的医院环境中对患有妊娠高血压疾病的妇女的有效性。利用2008年7月至2012年3月期间在5个低收入和中等收入国家的7家医院收治的患有妊娠高血压疾病的妇女的miniPIERS数据，使用完整的PIERS方程为每位妇女计算发生不良孕产妇结局的预测概率。缺失的预测指标值采用链式方程多元插补法进行插补。对该模型的区分能力、校准能力和分层能力进行了评估。在757名具有完整预测指标数据的妇女（完整病例分析）中，完整的PIERS模型在受试者工作特征曲线下的面积为0.77，表现良好（95%置信区间为0.72 - 0.82），但校准效果较差（Hosmer-Lemeshow拟合优度检验P<0.001）。对于预测不良结局概率≥30%的妇女，作为一种纳入工具的性能中等（似然比：5.9；95%置信区间为4.23 - 8.35）。完整的PIERS模型可用于资源匮乏地区的医院，以识别患有妊娠高血压疾病且有不良孕产妇结局高风险、需要立即干预的妇女。
