吴霞,雷琳.超声风险模型预测胎盘植入性疾病侵袭性[J].中国医学影像技术,2024,40(2):256~260
超声风险模型预测胎盘植入性疾病侵袭性
Ultrasonic risk model for predicting invasiveness of placenta accreta spectrum disorders
投稿时间:2023-04-23  修订日期:2023-10-31
DOI:10.13929/j.issn.1003-3289.2024.02.021
中文关键词:  胎盘植入  超声检查
英文关键词:placenta accreta  ultrasonography
基金项目:
作者单位E-mail
吴霞 湖北医药学院附属太和医院超声医学科, 湖北 十堰 442000  
雷琳 湖北医药学院附属太和医院超声医学科, 湖北 十堰 442000 guanj6@mail.sysu.edu.cn 
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中文摘要:
      目的 观察基于超声征象建立的风险模型预测胎盘植入性疾病(PAS)侵袭性的价值。方法 回顾性分析133例PAS患者资料,根据PAS有无侵袭性将其分为侵袭组(63例)和非侵袭组(70例)。比较组间12个PAS相关超声征象及胎盘下缘与宫颈内口距离(D值)的差异,以单因素logistic回归及受试者工作特征(ROC)曲线分析选定判断PAS侵袭性超声征象的数目阈值,并建立其二分类变量,通过多因素logistic回归确定其与D值是否为预测PAS侵袭性的独立影响因素,并由此建立预测模型。结果 12个相关征象中,胎盘后低回声带中断或消失、子宫肌层变薄、异常胎盘陷窝、胎盘增厚、宫颈受累、膀胱壁中断或消失、胎盘陷窝供应血管、桥血管、胎盘基底部血流增多及子宫膀胱间血管增多在侵袭组中的检出率均高于非侵袭组(P均<0.05),而胎盘隆起和外生性包块组间检出率差异均无统计学意义(P均>0.05)。侵袭组多见前壁为主的前置胎盘及多超声征象;多超声征象及D值过小是预测PAS侵袭性的独立危险因素(P均<0.05),所获预测模型为logit(P)=-0.717+1.551×多超声征象-0.216×D值,其曲线下面积(AUC)为0.905。结论 PAS多超声征象及胎盘下缘与宫颈内口距离过短均为预测PAS侵袭性的独立危险因素;所获模型用于预测PAS侵袭性风险效能较佳。
英文摘要:
      Objective To explore the value of a risk model established based on ultrasonic features for predicting invasiveness of placenta accreta spectrum disorders (PAS). Methods Data of 133 PAS patients were retrospectively analyzed. According to being invasive PAS or not, the patients were divided into invasive group (n=63) and non-invasive group (n=70). PAS-related ultrasonic features and distance between the lower margin of placenta and internal os of cervix (D value) were compared between groups. Univariate logistic regression and the receiver operating characteristic (ROC) curve were used to define the optimal cut-off value of figure of ultrasonic features for identifying invasiveness of PAS, then a dichotomous variable of the above figure was created. Multivariate logistic regression was performed to detect whether the dichotomous variable of the above figure and D were the independent impact factors for identifying invasiveness of PAS, and the risk prediction model was constructed. Results Among 12 PAS-related ultrasonic features, the detection rates of 10 features, including interruption or disappearance of retroplacental clear zone,thinner myometrium,lacunae, thickened placenta, cervix involvement, interrupted or disappeared bladder wall, feeding vessels of lacunae, bridge vessels, as well as hypervascularity of uteroplacental interface and between uterus and bladder in invasive group were higher than those in non-invasive group (all P<0.05), while those of lumpy contour and placental bulge were not significantly different between groups (both P>0.05). In invasive group, anterior placenta mainly located on the anterior wall and multiple PAS-related ultrasonic features were more common. Multiple ultrasonic features and smaller D value were both independent risk factors for identifying invasiveness of PAS (both P<0.05). The prediction model for identifying invasiveness of PAS was logit(P)=-0.717+1.551×Positivemultiple ultrasonic features-0.216×D value, with the area under curve (AUC) of 0.905. Conclusion Multiple PAS-related ultrasonic features and shorter distance of the lower margin of placenta to the internal os of cervix were independent risk factors for identifying invasiveness of PAS. The constructed risk model was effective for predicting invasiveness of PAS.
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