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胎盘植入谱系疾病中预测产科并发症的评分系统的验证。

Validation of a scoring system for prediction of obstetric complications in placenta accreta spectrum disorders.

机构信息

Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China.

Beijing Key Laboratory of Maternal Fetal Medicine of Gestational Diabetes Mellitus, Beijing, China.

出版信息

J Matern Fetal Neonatal Med. 2022 Nov;35(21):4149-4155. doi: 10.1080/14767058.2020.1847077. Epub 2021 Mar 8.

Abstract

BACKGROUND

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.

METHODS

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.

RESULTS

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,  < .001), for severe postpartum hemorrhage (≥1500 ml) is 0.76 (95%CI, 0.62-0.91,  = .005), for hysterectomy is 0.98 (95%CI, 0.93-1.000,  = .023).

CONCLUSIONS

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).

摘要

背景

胎盘植入谱系疾病(PAS)是指胎盘异常附着于植入部位的一系列疾病,由于产后出血、围产期子宫切除术和产妇死亡率的风险,一直是一个挑战。尽管有超声检查结果,但尚未就 PAS 的产前评估达成共识。我们旨在建立一个评分系统,以提高 PAS 严重程度预测的准确性,特别是区分胎盘穿透性和胎盘植入性。

方法

我们进行了一项回顾性研究,收集了来自中国 20 家三级医疗中心的 2219 例胎盘植入和胎盘穿透病例。收集了人口统计学信息、临床特征和超声检查结果。采用逻辑回归分析确定与胎盘穿透性临床诊断显著相关的危险因素和超声特征。生成公式和后续评分系统。然后在北京大学第一医院 2016 年至 2017 年的 67 例胎盘植入或胎盘穿透病例中验证了该评分系统。胎盘侵犯的诊断通过手术发现或组织病理学结果证实。使用接收者操作特征(ROC)曲线评估评分系统。

结果

该评分系统结合了母体危险因素和超声特征,并在北京大学第一医院的 67 例病例中得到了验证。根据 ROC 曲线,我们的胎盘穿透性产前诊断评分系统的曲线下面积(AUC)为 0.96(95%CI,0.91-1.00,<0.001),用于严重产后出血(≥1500ml)为 0.76(95%CI,0.62-0.91,=0.005),用于子宫切除术为 0.98(95%CI,0.93-1.000,=0.023)。

结论

我们的评分系统结合了母体危险因素和超声特征,可以提高胎盘穿透性和产科结局(严重出血和子宫切除术)的预测准确性。

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