Jo Yun Sung, Kim Woo Jeng, Choi Sae Kyung, Kim Su Mi, Shin Jae Eun, Kil Ki Cheol, Kim Yeon Hee, Wie Jeong Ha, Kim Han Wool, Hong Subeen, Ko Hyun Sun
Department of Obstetrics and Gynecology, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Department of Obstetrics and Gynecology, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Life (Basel). 2023 Jun 6;13(6):1330. doi: 10.3390/life13061330.
This study aimed to develop an early pregnancy risk scoring model for pregnancy-associated hypertension (PAH) based on maternal pre-pregnancy characteristics, such as mean arterial pressure (MAP), pregnancy-associated plasma protein-A (PAPP-A) or neither. The perinatal databases of seven hospitals from January 2009 to December 2020 were randomly divided into a training set and a test set at a ratio of 70:30. The data of a total pregnant restricted population (women not taking aspirin during pregnancy) were analyzed separately. Three models (model 1, pre-pregnancy factors only; model 2, adding MAP; model 3, adding MAP and PAPP-A) and the American College of Obstetricians and Gynecologists (ACOG) risk factors model were compared. A total of 2840 (8.11%) and 1550 (3.3%) women subsequently developed PAH and preterm PAH, respectively. Performances of models 2 and 3 with areas under the curve (AUC) over 0.82 in both total population and restricted population were superior to those of model 1 (with AUCs of 0.75 and 0.748, respectively) and the ACOG risk model (with AUCs of 0.66 and 0.66) for predicting PAH and preterm PAH. The final scoring system with model 2 for predicting PAH and preterm PAH showed moderate to good performance (AUCs of 0.78 and 0.79, respectively) in the test set. "A risk scoring model for PAH and preterm PAH with pre-pregnancy factors and MAP showed moderate to high performances. Further prospective studies for validating this scoring model with biomarkers and uterine artery Doppler or without them might be required".
本研究旨在基于孕妇孕前特征,如平均动脉压(MAP)、妊娠相关血浆蛋白-A(PAPP-A)或两者皆无,开发一种妊娠相关高血压(PAH)的早期妊娠风险评分模型。将2009年1月至2020年12月期间七家医院的围产期数据库以70:30的比例随机分为训练集和测试集。对总共妊娠受限人群(孕期未服用阿司匹林的女性)的数据进行单独分析。比较了三个模型(模型1,仅孕前因素;模型2,加入MAP;模型3,加入MAP和PAPP-A)和美国妇产科医师学会(ACOG)风险因素模型。分别有2840名(8.11%)和1550名(3.3%)女性随后发生了PAH和早产PAH。在总人群和受限人群中,模型2和模型3的曲线下面积(AUC)均超过0.82,其预测PAH和早产PAH的性能优于模型1(AUC分别为0.75和0.748)和ACOG风险模型(AUC分别为0.66和0.66)。用于预测PAH和早产PAH的最终模型2评分系统在测试集中表现出中等至良好的性能(AUC分别为0.78和0.79)。“一个包含孕前因素和MAP的PAH和早产PAH风险评分模型表现出中等至高的性能。可能需要进一步开展前瞻性研究,以使用生物标志物和子宫动脉多普勒或不使用它们来验证该评分模型”。