目的:确定预测因子并建立一个评分模型来预测孕产妇近错过(MNM)和孕产妇死亡率。
方法:对2014年至2020年间分娩的1,420名妇女进行了病例对照研究。病例是MNM或孕产妇死亡的妇女,对照组是在病例组中的女性之后直接顺利分娩的女性。回顾了产前特征和并发症。使用多变量逻辑回归和Akaike信息标准来确定预测因子并制定MNM和孕产妇死亡率的风险评分。
结果:MNM和孕产妇死亡率的预测因子(预测模型的aOR和评分)为高龄(aOR1.73,95%CI1.25-2.39,1),肥胖(aOR2.03,95%CI1.22-3.39,1),平价≥3(aOR1.75,95%CI1.27-2.41,1),刮宫史(aOR5.13,95%CI2.47-10.66,3),产后出血病史(PPH)(aOR13.55,95%CI1.40-130.99,5),贫血(aOR5.53,95%CI3.65-8.38,3),孕前糖尿病(aOR5.29,95%CI1.27-21.99,3),心脏病(aOR13.40,95CI4.42-40.61,5),多胎妊娠(aOR5.57,95%CI2.00-15.50,3),前置胎盘和/或胎盘植入谱(aOR48.19,95%CI22.75-102.09,8),妊娠期高血压/子痫前期无严重特征(aOR5.95,95%CI2.64-13.45,4),并有严重特征(aOR16.64,95%CI9.17-30.19,6),早产<37周(aOR1.65,95CI1.06-2.58,1)和<34周(aOR2.71,95%CI1.59-4.62,2)。≥4的截止分数使正确将女性分为高危人群的机会最高,其敏感性为74.4%,特异性为90.4%。
结论:我们确定了预测因子,并提出了一个评分模型来预测MNM和孕产妇死亡率,具有可接受的预测性能。
OBJECTIVE: To identify predictors and develop a scoring model to predict maternal near-miss (MNM) and maternal mortality.
METHODS: A
case-control study of 1,420 women delivered between 2014 and 2020 was conducted. Cases were women with MNM or maternal death, controls were women who had uneventful deliveries directly after women in the cases group. Antenatal characteristics and complications were reviewed. Multivariate logistic regression and Akaike information criterion were used to identify predictors and develop a risk score for MNM and maternal mortality.
RESULTS: Predictors for MNM and maternal mortality (aOR and score for predictive model) were advanced age (aOR 1.73, 95% CI 1.25-2.39, 1), obesity (aOR 2.03, 95% CI 1.22-3.39, 1), parity ≥ 3 (aOR 1.75, 95% CI 1.27-2.41, 1), history of uterine curettage (aOR 5.13, 95% CI 2.47-10.66, 3), history of postpartum hemorrhage (PPH) (aOR 13.55, 95% CI 1.40-130.99, 5), anemia (aOR 5.53, 95% CI 3.65-8.38, 3), pregestational diabetes (aOR 5.29, 95% CI 1.27-21.99, 3), heart disease (aOR 13.40, 95%CI 4.42-40.61, 5), multiple pregnancy (aOR 5.57, 95% CI 2.00-15.50, 3), placenta previa and/or placenta-accreta spectrum (aOR 48.19, 95% CI 22.75-102.09, 8), gestational hypertension/preeclampsia without severe features (aOR 5.95, 95% CI 2.64-13.45, 4), and with severe features (aOR 16.64, 95% CI 9.17-30.19, 6), preterm delivery <37 weeks (aOR 1.65, 95%CI 1.06-2.58, 1) and < 34 weeks (aOR 2.71, 95% CI 1.59-4.62, 2). A cut-off score of ≥4 gave the highest chance of correctly classified women into high risk group with 74.4% sensitivity and 90.4% specificity.
CONCLUSIONS: We identified predictors and proposed a scoring model to predict MNM and maternal mortality with acceptable predictive performance.