4.7 Article

Probability of severe postpartum hemorrhage in repeat cesarean deliveries: a multicenter retrospective study in China

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-87830-7

Keywords

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Funding

  1. National Key R&D Program of China [2016YFC1000405, 2017YFC1001402, 2018YFC1004104, 2018YFC10029002]
  2. National Natural Science Foundation [81830045, 81,671,533, 81,571,518, 81,971,415]
  3. General program of Guangdong province Natural Science Foundation [2020A1515010273]

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This multicenter, retrospective cohort study established predictive models for the probability of severe postpartum hemorrhage (SPPH) in women undergoing repeat cesarean delivery, based on pre-operative and intraoperative features. These models showed good discrimination and calibration, and nomograms were developed to assist in estimating the probability of SPPH and better preparing and managing patients undergoing repeat cesarean delivery.
To determine the factors predicting the probability of severe postpartum hemorrhage (SPPH) in women undergoing repeat cesarean delivery (RCD). This multicenter, retrospective cohort study involved women who underwent RCD from January 2017 to December 2017, in 11 public tertiary hospitals within 7 provinces of China. The all-variables model and the multivariable logistic regression model (pre-operative, operative and simple model) were developed to estimate the probability of SPPH in development data and external validated in validation data. Discrimination and calibration were evaluated and clinical impact was determined by decision curve analysis. The study consisted of 11,074 women undergoing RCD. 278 (2.5%) women experienced SPPH. The pre-operative simple model including 9 pre-operative features, the operative simple model including 4 pre-operative and 2 intraoperative features and simple model including only 4 closely related pre-operative features showed AUC 0.888, 0.864 and 0.858 in development data and 0.921, 0.928 and 0.925 in validation data, respectively. Nomograms were developed based on predictive models for SPPH. Predictive tools based on clinical characteristics can be used to estimate the probability of SPPH in patients undergoing RCD and help to allow better preparation and management of these patients by using a multidisciplinary approach of cesarean delivery for obstetrician.

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