妊娠期高血压患者妊娠结局调查及相关影响因素分析

目的 调查温州市人民医院2018—2021年妊娠期高血压疾病(hypertensive disorders of pregnancy,HDP)患者妊娠结局,并分析其妊娠结局的相关影响因素,为临床采取对应干预措施、降低不良妊娠结局发生风险提供参考。 方法 选取2018年1月—2021年12月于温州市人民医院分娩的400例HDP患者(单胎妊娠)的临床资料,开展回顾性分析,根据其妊娠结局分为不良妊娠结局组(n=157)与正常妊娠结局组(n=243)。比较两组临床资料,分析HDP患者不良妊娠结局发生的影响因素,构建logistic回归模型方程,并分析logistic回归模型的预测价值。 结果 400例HDP患者中共157例(39.25%)发生不良妊娠结局;单因素分析显示患者年龄、孕前BMI、分娩方式、妊娠期糖尿病(gestational diabetes mellitus,GDM)、负性情绪与不良妊娠结局的发生有关(P＜0.05);logistic回归模型显示,年龄≥35岁(OR=23.815,95%CI:10.370～54.655)、孕前BMI≥24.0(OR=16.010,95%CI:6.832～34.620)、阴道分娩(OR=16.336,95%CI:7.325～36.403)、GDM(OR=26.337,95%CI:11.908～58.253)、负性情绪(OR=20.682,95%CI:2.791～54.876)均为HDP患者不良妊娠结局发生的独立危险因素(P＜0.05);5个独立危险因素构建logistic回归模型方程为logistic(P)=-4.125+年龄×3.170+孕前BMI×2.773+阴道分娩×2.793+GDM×3.271+负性情绪×3.029;当logistic(P)=4.11,预测HDP患者发生不良妊娠结局的曲线下面积为0.899(95%CI:0.865～0.926),预测敏感度为84.36%,特异度为82.17%;根据设定的评分标准与不良妊娠结局发生情况,可将HDP患者划分为低风险(0～4分)、中风险(5～8分)与高风险(9～12分)。 结论 HDP患者不良妊娠结局发生率较高,年龄、孕前BMI、阴道分娩、GDM、负性情绪均为不良妊娠结局发生的影响因素,构建logistic回归模型可预测不良妊娠结局发生风险,有助于临床制定相关干预措施。

Pregnancy outcomes and their related influencing factors in patients with hypertension during pregnancy

Objective To investigate the pregnancy outcomes of patients with hypertensive disorders of pregnancy (HDP) in Wenzhou People’s Hospital from 2018 to 2021, to analyze the relevant factors influencing their pregnancy outcomes, and to provide references for taking clinical intervention measures and reducing the risk of adverse pregnancy outcomes. Methods We selected the clinical data about 400 HDP patients (singleton pregnancies) delivered in Wenzhou People’s Hospital from January 2018 to December 2021, and then conducted a retrospective analysis. All the patients were divided into the adverse pregnancy outcome group (n=157) and the normal pregnancy outcome group (n=243) according to their pregnancy outcomes. The clinical data of the two groups were compared, and the factors influencing the occurrence of adverse pregnancy outcomes in the HDP patients were analyzed. Logistic regression model equations were constructed, and the predictive value of the logistic regression model was analyzed. Results Among the 400 HDP patients 157 (39.25%) had adverse pregnancy outcomes. Univariate analysis showed that age, pre-pregnancy body mass index (BMI), mode of delivery, gestational diabetes mellitus (GDM) and negative emotions were associated with adverse pregnancy outcomes (P<0.05). Logistic regression model revealed that age ≥ 35 years (OR=23.815, 95%CI:10.370-54.655), pre-pregnancy BMI ≥ 24.0 (OR=16.010, 95%CI:6.832-34.620), vaginaldelivery (OR=16.336, 95%CI:7.325-36.403), GDM (OR=26.337, 95%CI:11.908-58.253), and negative emotions (OR=20.682, 95%CI:7.791-54.876) were independent risk factors for the occurrence of adverse pregnancy outcomes in the HDP patients (all P<0.05). The logistic regression model equation constructed by 5 independent risk factors was logistic(P)=-4.125+age×3.170+pre-pregnancy BMI×2.773+vaginal delivery×2.793+GDM×3.271+negative emotion×3.029. When logistic (P)=4.11, the area under the curve for predicting adverse pregnancy outcomes in the HDP patients was 0.899 (95%CI:0.865-0.926), and the predictive sensitivity and specificity were 84.36% and 82.17%, respectively. According to the scoring criteria and the occurrence of adverse pregnancy outcomes, the HDP patients could be divided into low risk (0-4 points), intermediate risk (5-8 points) and high risk (9-12 points). Conclusion The incidence rate of adverse pregnancy outcomes in the GH patients is high. Age, pre-pregnancy BMI, vaginal delivery, GDM and negative emotions are all influential factors in the occurrence of adverse pregnancy outcomes. Constructing the logistic regression model can predict the risk of adverse pregnancy outcomes and is conducive to clinical formulation of related interventions.