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Novel biomarkers for prediction of atonic postpartum hemorrhage among 'low-risk' women in labor.
Zhang, Pei; Jia, Yanju; Song, Hui; Fan, Yifan; Lv, Yan; Geng, Hao; Zhao, Ying; Cui, Hongyan; Chen, Xu.
Afiliación
  • Zhang P; School of Medicine, Nankai University, Tianjin, China.
  • Jia Y; Tianjin Key Laboratory of Human Development and Reproductive Regulation, Tianjin, China.
  • Song H; School of Medicine, Nankai University, Tianjin, China.
  • Fan Y; Department of Obstetrics, Tianjin Central Hospital of Gynecology Obstetrics, Tianjin, China.
  • Lv Y; School of Medicine, Nankai University, Tianjin, China.
  • Geng H; Tianjin Key Laboratory of Human Development and Reproductive Regulation, Tianjin, China.
  • Zhao Y; Department of Obstetrics, Tianjin Central Hospital of Gynecology Obstetrics, Tianjin, China.
  • Cui H; School of Medicine, Nankai University, Tianjin, China.
  • Chen X; Tianjin Key Laboratory of Human Development and Reproductive Regulation, Tianjin, China.
Front Immunol ; 15: 1416990, 2024.
Article en En | MEDLINE | ID: mdl-39055706
ABSTRACT

Background:

Postpartum hemorrhage (PPH) is the primary cause of maternal mortality globally, with uterine atony being the predominant contributing factor. However, accurate prediction of PPH in the general population remains challenging due to a lack of reliable biomarkers.

Methods:

Using retrospective cohort data, we quantified 48 cytokines in plasma samples from 40 women diagnosed with PPH caused by uterine atony. We also analyzed previously reported hemogram and coagulation parameters related to inflammatory response. The least absolute shrinkage and selection operator (LASSO) and logistic regression were applied to develop predictive models. Established models were further evaluated and temporally validated in a prospective cohort.

Results:

Fourteen factors showed significant differences between the two groups, among which IL2Rα, IL9, MIP1ß, TNFß, CTACK, prenatal Hb, Lymph%, PLR, and LnSII were selected by LASSO to construct predictive model A. Further, by logistic regression, model B was constructed using prenatal Hb, PLR, IL2Rα, and IL9. The area under the curve (AUC) values of model A in the training set, internal validation set, and temporal validation set were 0.846 (0.757-0.934), 0.846 (0.749-0.930), and 0.875 (0.789-0.961), respectively. And the corresponding AUC values for model B were 0.805 (0.709-0.901), 0.805 (0.701-0.894), and 0.901 (0.824-0.979). Decision curve analysis results showed that both nomograms had a high net benefit for predicting atonic PPH.

Conclusion:

We identified novel biomarkers and developed predictive models for atonic PPH in women undergoing "low-risk" vaginal delivery, providing immunological insights for further exploration of the mechanism underlying atonic PPH.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biomarcadores / Citocinas / Hemorragia Posparto Límite: Adult / Female / Humans / Pregnancy Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biomarcadores / Citocinas / Hemorragia Posparto Límite: Adult / Female / Humans / Pregnancy Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza