Prediction of bleeding in labor in women with uterine scar as a tool to prevent massive blood loss: an observational cohort study
Authors: Makukhina T. B. , Penzhoyan G. A. , Dontsova M. V. 
Published: April 2024

Background. Postpartum hemorrhage is recognized as a leading cause of maternal mortality and morbidity in the world. Predicting postpartum hemorrhage in high-risk patients with uterine scar enables preventive measures to be scheduled and costs of treatment and rehabilitation to be reduced.Objective. To determine antenatal predictors of high postpartum hemorrhage risk in pregnant women with uterine scar in order to improve the prevention of massive blood loss.Methods. An observational cohort study involves the medical records of 4494 maternity women with uterine scar (pregnancy and delivery histories) of the Perinatal Center of Regional Clinical Hospital No. 2, Krasnodar Krai. The study sample included data of maternity women coded O34.2 according to International Classification of Diseases, 10th Edition, for the period from 2017 to 2020. The sample participants were distributed into two groups depending on the blood loss during delivery, determined in compliance with clinical recommendations: a group of patients without massive blood loss during delivery and a group of patients with massive blood loss in labor/early postpartum period. The study was mainly focused on parameters of the prediction performance of bleeding in labor and early postpartum period in pregnant women with uterine scar using a multiparametric, logistic regression models. The study considered demographic data, comorbidity, obstetric history, pregnancy course, ultrasound data, and volume of blood loss at delivery. The performance of prediction for postpartum hemorrhage was calculated using multivariate binary logistic regression. Descriptive statistical analysis was carried out by means of statistical software package SPSS Version 26 (IBM, USA). Two-sided p-value < 0.05 was taken as a statistically significant difference. A prognostic significance of predictors was determined by binary logistic regression. The Wald statistic was used to determine an observed significance. In order to define the performance of the model, the study involved calculating sensitivity, specificity, positive and negative predictive value, Nagelkerke coefficient of determination, as well as performing ROC analysis. The DeLong test was used for paired comparisons of ROC curves.Results. In the retrospective follow-up group (2017–2020) (n = 502), postpartum hemorrhage with massive blood loss occurred in 41 cases (8.17%). For the model based on clinical-anamnestic predictors, the prediction performance for postpartum hemorrhage comprised: sensitivity = 12.2% (95% confidence interval (CI) 4.1–26.2); specificity = 99.3% (95% CI 98.1–99.9); positive predictive value = 62.5% (95% CI 24.5–91.5); negative predictive value = 92.6% (95% CI 89.9–94.8); area under the ROC curve = 0.864 (95% CI 0.807–0.920), p < 0.001. The prediction performance for the model based on three ultrasound predictors (asymmetry coefficient of placental thickness, uterine wall bulging in the scar and myometrial thickness in the placentation zone) comprised: sensitivity = 85.4% (95% CI 70.8–94.4); specificity = 98.5% (95% CI 96.9–99.4); positive predictive value = 83.3% (95% CI 68.6–93.0); negative predictive value = 98.7% (95% CI 97.2–99.5); area under the ROC curve = 0.919 (95% CI 0.855–0.983), p < 0.001. No significant difference was revealed for the performance of the models ( p = 0.170). For the model based on ultrasound predictors and placenta previa, the prediction performance comprised: sensitivity = 85.4% (95% CI 70.8–94.4); specificity = 98.5% (95% CI 96.9–99.4); positive predictive value = 83.3% (95% CI 68.6–93.0); negative predictive value = 98.7% (95% CI 97.2–99.5); area under the ROC curve = 0.955 (95% CI 0.912–0.999), p < 0.001. The model based on clinical-anamnestic and ultrasound indicators predicted postpartum hemorrhage with sensitivity equal to 85.4% (95% CI 70.8–94.4); specificity — 98.9% (95% CI 97.4–99.6); positive predictive value — 87.5% (95% CI 73.2–95.8); negative predictive value — 98.7% (95% CI 97.1–99.5); area under the ROC curve — 0.984 (95% CI 0.966–1.0), р < 0,001. Thus, this model outperformed the model based on clinical-anamnestic data (p < 0.001), based on ultrasound predictors (p = 0.006) and revealed no difference with the model considering placenta previa and ultrasound predictors (p = 0.127). Using prenatal prediction of postpartum hemorrhage based on ultrasound features, the incidence of massive blood loss at delivery decreased from 6.88/1000 deliveries (2019–2020) to 4.18/1000 deliveries (2021–2022) (p < 0.001).Conclusion. Ultrasound predictors in pregnant women with uterine scar increase the sensitivity of antenatal prediction of postpartum hemorrhage based on the assessment of clinical and anamnestic risk factors, thereby enabling preventive measures to be scheduled in the risk group and incidence of massive blood loss to be reduced.