1. Validation of a scoring system for prediction of obstetric complications in placenta accreta spectrum disorders.
- Author
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Zheng, Weiran, Zhang, Huijing, Ma, Jingmei, Dou, Ruochong, Zhao, Xianlan, Yan, Jie, and Yang, Huixia
- Abstract
Placenta accreta spectrum (PAS) refers to a spectrum of conditions characterized by the abnormal adherence of the placenta to the implantation site and has been a challenge due to the risk of postpartum hemorrhage, peripartum hysterectomy and maternal mortality. Despite of sonographic findings, no consensus on the prenatal evaluation of PAS has been established yet. We are aiming to establish a scoring system to increase the accuracy of prediction of PAS severity, especially to differentiate placenta percreta and placenta increta. We conducted a retrospective study and collected 2,219 cases of placenta increta and placenta percreta obtained from 20 tertiary care centers in China. Demographic information, clinical characteristics, and sonographic findings were collected. Logistic regression analysis was used to determine the risk factors and sonographic features that were significantly associated with a clinical diagnosis of placenta percreta. The formula and subsequent scoring system were generated. This scoring system was then verified in 67 cases of placenta increta or placenta percreta in Peking University First Hospital from 2016 to 2017. Diagnosis of placental invasion was confirmed by surgical findings or histopathologic results. The scoring system was evaluated using a receiver operating characteristic (ROC) curve. The scoring system combined maternal risk factors and ultrasound features and was then verified in 67 cases. According to ROC curve, the area under the curve (AUC) of our scoring system for prenatal diagnosis of placenta percreta is 0.96 (95%CI, 0.91–1.00, p <.001), for severe postpartum hemorrhage (≥1500 ml) is 0.76 (95%CI, 0.62–0.91, p =.005), for hysterectomy is 0.98 (95%CI, 0.93–1.000, p =.023). Our scoring system combining maternal risk factors and ultrasound features can improve the predictive accuracy of placenta percreta and obstetric outcomes (severe hemorrhage and hysterectomy). [ABSTRACT FROM AUTHOR]
- Published
- 2022
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