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Risk factors for massive intraoperative hemorrhage during cesarean section in patients with complete placenta previa
1Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, 110004, China.
Background:
Research on placenta accreta spectrum (PAS) primarily focuses on patients with complete placenta previa (cPP) and a prior cesarean delivery. Studies on patients without a prior cesarean delivery are relatively scarce. With the increasing maternal age and a growing number of patients with infertility, the incidence of cPP accompanied by PAS has risen, even among individuals without a prior cesarean delivery. Relying solely on the preoperative PASUSS score may underestimate the actual severity of PAS. This study aims to explore the risk factors for massive intraoperative hemorrhage (MIH) during cesarean section in patients with cPP and PAS who have no prior cesarean delivery, based on baseline patient characteristics and ultrasound indicators.
Methods:
Retrospective data were collected from 109 patients diagnosed with cPP accompanied by PAS and without a prior cesarean delivery, who were admitted to Shengjing Hospital affiliated with China Medical University between January 2020 and December 2024. MIH during cesarean section was defined as blood loss of ≥ 2000 mL during the procedure. Participants were classified into two groups: the MIH group (22 cases) and the non-MIH group (87 cases). Independent risk factors for MIH were identified through univariate and multivariate logistic regression analysis.
Results:
In patients with cPP and PAS diagnosed mainly through clinical criteria and no prior cesarean delivery, the incidence of MIH was approximately 20.18%. Independent risk factors for MIH include maternal age, hysteroscopic adhesiolysis, and a higher preoperative PASUSS score.
Conclusions:
In clinical practice, it is essential not only to prioritize the preoperative PASUSS score but also to pay close attention to the patient's baseline characteristics. This approach enables accurate identification of individuals at high risk for MIH, thereby improving patient prognosis.
