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  1. Home
  3. Optimization Of A Preeclampsia Early Warning Model Driven By Psychosocial Factors: A Five-year Cohort Study And Its Clinical Impact.
  1. Home
  3. Optimization Of A Preeclampsia Early Warning Model Driven By Psychosocial Factors: A Five-year Cohort Study And Its Clinical Impact.

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Optimization of a preeclampsia early warning model driven by psychosocial factors: a five-year cohort study and its

Rumin Wang1, Qinkan Xu1, Xiaodi Wang1

  • 1Department of Obstetrics, Yongkang First People's Hospital, Jinhua, China.

The Journal of Maternal-Fetal & Neonatal Medicine : the Official Journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
|June 12, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

This study developed an improved preeclampsia early warning model by including psychological stress and social support. The new model enhances early detection accuracy for pregnant women at high risk.

Keywords:
AUCPreeclampsiadisease burdenearly identificationearly warning modelpsychosocial factors

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Area of Science:

  • Obstetrics and Gynecology
  • Maternal-Fetal Medicine
  • Psychosomatic Medicine

Background:

  • Preeclampsia poses significant risks to maternal and fetal health.
  • Early detection is crucial for effective management and improved outcomes.
  • Traditional models often lack comprehensive risk assessment, potentially missing key contributing factors.

Purpose of the Study:

  • To optimize a preeclampsia early warning model by integrating psychosocial factors with clinical indicators.
  • To enhance the precision of early identification tools for preeclampsia.
  • To analyze the impact of psychosocial elements on maternal disease burden.

Main Methods:

  • A retrospective case-control study utilizing inpatient data from January 2018 to December 2023.
  • Propensity score matching (PSM) was employed for control selection at a 1:2 ratio.
  • A multivariable logistic regression model was developed, incorporating clinical indicators and psychosocial factors (Modified Pregnancy Stress Scale-Revised [MPSS-R] and social support), with performance evaluated using ROC curves.

    • Main Results:

    • The integrated model achieved an AUC of 0.823, indicating good predictive performance.
    • Elevated MPSS-R scores significantly correlated with preeclampsia severity (p < 0.001).
    • Approximately 42.6% of severe preeclampsia cases showed elevated psychological stress scores 2-4 weeks prior to diagnosis, with a high incidence rate (38.5%) observed in the high-risk group.

    Conclusions:

    • A validated preeclampsia early warning model integrating psychosocial factors was successfully developed.
    • Psychosocial health status and social support are significant predictors of preeclampsia.
    • The model offers a new basis for personalized screening and intervention strategies for high-risk pregnancies.