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Development of a Predictive Model for Postpartum Hemorrhage in Preterm Deliveries: A Retrospective Matched Case-Control Analysis

  • By

  • Qiuping Liao

  • Baomei Xu

  • Lin Lin

  • Lianghui Zheng

  • Jinying Luo

  • Qian Yu

  • Jianying Yan

  • August 20, 2026

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  • 1

    A predictive model for postpartum hemorrhage (PPH) in preterm deliveries was developed using clinical data from 728 singleton pregnant women.

  • 2

    Logistic regression analysis identified significant risk factors for PPH, including induced abortions, gestational diabetes, anemia, and polyhydramnios.

  • 3

    The nomogram prediction model achieved a receiver operating characteristic (ROC) curve area under the curve (AUC) of 0.770.

  • 4

    Placenta accreta and increta were highlighted as the most significant risk factors for PPH in preterm deliveries, according to the BP neural network analysis.

  • 5

    The study's findings indicate that the predictive model has moderate capability for identifying women at high risk for PPH during preterm delivery.

Original Source(s)

Establishment of an antepartum predictive model for postpartum hemorrhage in preterm delivery: a retrospective matched case-control study

  • by Qiuping Liao, Baomei Xu, Lin Lin, Lianghui Zheng, Jinying Luo, Qian Yu, Jianying Yan

  • August 20, 2026

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