Abstract
BackgroundPostpartum hemorrhage (PPH) is a common complication following vaginal delivery and in severe cases can lead to maternal death. A straightforward predictive model is required to enable prenatal evaluations by obstetricians to prevent PPH complications.MethodsData of patients who delivered vaginally after 37 weeks of gestation were retrospectively collected from the medical database at Shengjing Hospital of China Medical University for the period 2016 to 2020. PPH was defined as blood loss of 500 mL or more within 24 h of delivery, and important independent prognostic factors were determined using univariate and multivariate logistic regression analyses to construct nomograms regarding PPH.ResultsA total of 24,833 patients who delivered vaginally were included in this study. The training cohort included 22,302 patients who delivered between 2016 and 2019 and the external validation cohort included 2,531 patients who delivered during 2020. Nomogram was created using data such as age, race, occupation, parity, gestational weeks, labor time, neonatal weight, analgesic delivery, gestational diabetes mellitus, premature rupture of membranes, anemia, hypertension, adenomyosis, and placental adhesion. The nomogram has good predictive power and clinical practicality through the analysis of the area under the curve and decision curve analysis. Internal verification was performed on the nomogram for PPH, demonstrating consistency between the nomogram's predicted probability and actual probability.ConclusionsThe developed and validatable nomogram is a good predictor of PPH in vaginal delivery and can be used in clinical practice to guide obstetricians to administer preventive therapies before delivery.
Highlights
Severe postpartum hemorrhage is the main cause of maternal morbidity and mortality worldwide
We evaluated the factors related to postpartum hemorrhage (PPH) based on the data of patients who delivered vaginally at our center, and constructed a nomogram for PPH
PPH occurred in 1,468 patients (6.6%) in the training cohort
Summary
Severe postpartum hemorrhage is the main cause of maternal morbidity and mortality worldwide. According to the data released by the World Health Organization (WHO) [1], 25% of the total annual maternal deaths worldwide are caused by postpartum hemorrhage (PPH). Over 80% of PPH cases occur within 2 h following delivery. Severe cases require hysterectomy or can result in maternal death [2]. Complications such as puerperal infection, posttransfusion diseases, postpartum psychological diseases, and Sheehan’s syndrome could still occur in surviving parturients after successful rescue, which can seriously impact their quality of life. Postpartum hemorrhage (PPH) is a common complication following vaginal delivery and in severe cases can lead to maternal death. A straightforward predictive model is required to enable prenatal evaluations by obstetricians to prevent PPH complications
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