Department of Gynaecology and Obstetrics, Wenzhou Central Hospital, No.252, Baili East Road, Lucheng District, Wenzhou City, 325000, Zhejiang Province, China.
BMC Pregnancy Childbirth. 2023 Aug 10;23(1):576. doi: 10.1186/s12884-023-05860-7.
This study aims to construct the risk prediction nomogram model of critical condition in patients with hypertension during pregnancy and to verify its evaluation effect.
A total of 531 patients with hypertension during pregnancy were randomly grouped into 427 model group and 104 validation group. The model group patients included 59 cases of critical group and 368 cases of non-critical group according to the occurrence of critical situation. Multivariate Logistic regression analysis was conducted to determine the risk factors of critical condition in patients with hypertension during pregnancy, and R software was used to construct the nomogram model. Moreover, the prediction efficiency of the model was evaluated.
The proportions of patients aged over 30 years, with an educational background of junior high school or below, a family history of hypertension, anemia during pregnancy, and a lower erythrocyte count were significantly higher in the critical group compared to the non-critical group (P < 0.05). Age > 30 years old, educational background of junior high school and below, family history of hypertension, anemia during pregnancy, and red blood cell count were independent risk factors for the occurrence of critical condition in patients with hypertension during pregnancy (P < 0.05). The prediction model formula Z = 1.857×Age + 1.167×Education + 1.601×Family history of hypertension + 1.815×Pregnancy anemia + 3.524×Red blood cell count+(-19.769). The area under the curve (AUC) of the nomogram in the modeling group for predicting the risk of critical situations was 0.926 (95% CI = 0.887 ~ 0.964), indicating excellent discrimination. The calibration curve closely resembled the ideal curve, demonstrating good agreement between the predicted and actual values. The AUC of the validation group's nomogram to predict the risk of critical situation was 0.942 (95% CI = 0.872 ~ 0.998), with good discrimination. The calibration curve was close to the ideal curve, and the actual value was in good agreement with the predicted value.
The nomograph model can predict the risk of critical condition in patients with hypertension during pregnancy and screen high-risk population.
本研究旨在构建妊娠期高血压患者危急情况风险预测列线图模型，并验证其评价效果。
将 531 例妊娠期高血压患者随机分为 427 例模型组和 104 例验证组。根据危急情况的发生，模型组患者包括 59 例危急组和 368 例非危急组。采用多因素 Logistic 回归分析确定妊娠期高血压患者危急情况的危险因素，并使用 R 软件构建列线图模型。此外，评估了该模型的预测效率。
危急组患者年龄大于 30 岁、文化程度为初中及以下、有高血压家族史、妊娠贫血、红细胞计数较低的比例明显高于非危急组（P<0.05）。年龄大于 30 岁、文化程度为初中及以下、有高血压家族史、妊娠贫血、红细胞计数是妊娠期高血压患者发生危急情况的独立危险因素（P<0.05）。预测模型公式 Z=1.857×年龄+1.167×教育+1.601×高血压家族史+1.815×妊娠贫血+3.524×红细胞计数+(-19.769)。建模组预测危急情况风险的列线图曲线下面积（AUC）为 0.926（95%CI=0.8870.964），提示具有良好的区分度。校准曲线与理想曲线非常接近，表明预测值与实际值之间具有良好的一致性。验证组预测危急情况风险的列线图 AUC 为 0.942（95%CI=0.8720.998），具有良好的区分度。校准曲线接近理想曲线，实际值与预测值吻合良好。
该列线图模型可预测妊娠期高血压患者危急情况的风险，并筛选高危人群。
