Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model

作者：Songchang Chen, Jia Li, Xiao Zhang, Wenqiu Xu, Zhixu Qiu, Siyao Yan, Wenrui Zhao, Zhiguang Zhao, Peirun Tian, Qiang Zhao, Qun Zhang, Weiping Chen, Huahua Li, Xiaohong Ruan, Gefei Xiao, Sufen Zhang, Liqing Hu, Jie Qin, Wuyan Huang, Zhongzhe Li, Shunyao Wang, Rui Zhang, Shang Huang, Xin Wang, Yao Yao, Jian Ran, Danling Cheng, Qi Luo, Teng Pan, Ruyun Gao, Jing Zheng, Yuxuan Wang, Cong Liu, Xianling Cao, Xuanyou Zhou, Naixin Xu, Lanlan Zhang, Xu Han, Haolin Wang, Suihua Feng, Shuyuan Li, Jian‐Guo Zhang, Lijian Zhao, Fengxiang Wei · 发表于：BMC Medical Informatics and Decision Making · 年份：2025 · DOI：10.1186/s12911-025-02999-5 · 被引用次数：11 · 研究领域：Pregnancy and preeclampsia studies、Gestational Diabetes Research and Management、Maternal and fetal healthcare

BACKGROUND: This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclampsia (LOPE), and preterm preeclampsia (Preterm PE) were developed using maternal characteristics and laboratory data. METHODS: Between January 2019 and December 2021, we retrospectively recruited 144 EOPE, 363 LOPE, 231 Preterm PE, and 1458 healthy participants from six hospitals. We utilized all available clinical and laboratory data obtained during routine prenatal visits in early pregnancy. The models for EOPE, LOPE, and Preterm PE were created using ensemble machine learning models with patient clinical and laboratory data. RESULTS: By comparing laboratory variables between PE patients and healthy controls, we identified 7, 18, 8, 15, 7,29 laboratory markers for EOPE, LOPE, and Preterm PE, severe PE, superimposed PE, first-time PE respectively. The ensemble EOPE and LOPE models incorporating clinical and laboratory predictors outperformed the clinical factor models respectively. The ensemble EOPE model demonstrated good sensitivity (72.22%,95% confidence interval [CI]: 57.59%-86.85%) and specificity (85.25%,95% CI: 80.54%-89.97%) in distinguishing EOPE from controls in early pregnancy. Similarly, the ensemble LOPE model showed good accuracy in differentiating LOPE from healthy participants (sensitivity: 69.57%, 95% CI: 56.27%-8...