ArticleBMC pregnancy and childbirth2022
A risk prediction model of perinatal blood transfusion for patients who underwent cesarean section: a case control study.
Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- Explainable tabular deep learning models for antenatal cesarean delivery prediction in multiparous women.BMC pregnancy and childbirth · 2026Article
- Construction of a predictive model for the risk of postpartum hemorrhage in women with advanced maternal age undergoing natural childbirth.American journal of translational research · 2025Article
- Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.Scientific reports · 2024Article
- Establishment of Risk Nomogram Model of Postpartum Hemorrhage After Second Cesarean Section.International journal of women's health · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
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Abstract
backgroundSevere obstetric hemorrhage is a leading cause of severe maternal morbidity. A perinatal blood transfusion is the key factor in the treatment of severe obstetric hemorrhage. Our aim is to identify patients with a high risk of perinatal blood transfusions before Cesarean Section, which can promote the effectiveness of the treatment of severe obstetric hemorrhage, as well as improve obstetric preparations.
methodsThis study retrospectively analyzed the data of 71 perinatal blood transfusion patients and 170 controls, who were both underwent Cesarean Section from July 2018 to September 2019. These data were included in the training set to build the risk prediction model of needing blood transfusion. Additionally, the data of 148 patients with the same protocol from October 2019 to May 2020 were included in the validation set for model validation. A multivariable logistic regression model was used. A risk prediction nomogram was formulated per the results of the multivariate analysis.
resultsThe strongest risk factors for perinatal blood transfusions included preeclampsia (OR = 6.876, 95% CI: 2.226-23.964), abnormal placentation (OR = 5.480, 95% CI: 2.478-12.591), maternal age (OR = 1.087, 95% CI: 1.016-1.166), predelivery hemoglobin (OR = 0.973, 95% CI: 0.948-0.998) and predelivery fibrinogen (OR = 0.479, 95% CI: 0.290-0.759). A risk prediction model of perinatal blood transfusions for cesarean sections was developed (AUC = 0.819; sensitivity: 0.735; specificity: 0.848; critical value: 0.287).
conclusionsThe risk prediction model can identify the perinatal blood transfusions before Cesarean Section. With the nomogram, the model can be further quantified and visualized, and clinical decision-making can subsequently be further simplified and promoted.
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