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产前主动脉弓角度测量在新生儿主动脉缩窄诊断中的验证。

Validation of Prenatal Aortic Arch Angle Measurements in the Diagnosis of Neonatal Coarctation of the Aorta.

机构信息

Division of Cardiology, Department of Pediatrics, Seattle Children's Hospital and University of Washington School of Medicine, 4800 Sand Point Way NE, Seattle, WA, 98105, USA.

Department of Biostatistics and Collaborative Health Studies, Magnuson Health Sciences Center, University of Washington, F-600, Seattle, WA, 98195, USA.

出版信息

Pediatr Cardiol. 2021 Aug;42(6):1365-1371. doi: 10.1007/s00246-021-02620-2. Epub 2021 Apr 26.

Abstract

Prenatal prediction of coarctation of the aorta (CoA) is challenging. Methods identifying prenatal CoA have high sensitivity with significant false positives. We previously derived prenatal aortic arch angles for identifying CoA with high sensitivity and specificity and aim to validate these angles and compare them with a model utilizing ascending aorta (AAo) and isthmus (Aoi) measures. Retrospective case/cohort study of fetuses with prenatal suspicion for CoA. 35 fetuses were included. Measurements included: ascending-descending aortic angle (AAo.DAo), transverse-descending aortic angle (TAo.DAo); diameters and z-scores of Aoi from sagittal (Aoi-sag), three-vessel (Aoi-3VV) view and AAo. Discriminant functions for the 5 variables were compared using histograms and positive/negative predictive values (PPV/NPV). CoA was confirmed in 28/35 neonates. The PPV and NPV for angle measures were 100% and 77%. The AAo + Aoi-3VV model PPV and NPV were 92% and 80% and Aoi-sag + Aoi-3VV model were 82% and 71%. A linear discriminant model utilizing the 3 most predictive variables improved NPV to 90% and PPV to 100%. In conclusion, we validate that angle measures are superior to standard models of predicting CoA. An optimized 3 variable model maintains accuracy of identifying CoA while eliminating false positives.

摘要

胎儿主动脉缩窄(CoA)的产前预测具有挑战性。识别产前 CoA 的方法具有较高的灵敏度,但假阳性率也较高。我们之前提出了一种基于产前主动脉弓角度的方法,该方法具有较高的灵敏度和特异性,旨在验证这些角度,并与利用升主动脉(AAo)和峡部(Aoi)测量值的模型进行比较。

对有产前 CoA 怀疑的胎儿进行回顾性病例/队列研究。共纳入 35 例胎儿。测量指标包括:升主动脉-降主动脉角度(AAo.DAo)、横主动脉-降主动脉角度(TAo.DAo);矢状位(Aoi-sag)、三血管切面(Aoi-3VV)和 AAo 测量的 Aoi 直径和 Z 评分。利用直方图和阳性/阴性预测值(PPV/NPV)比较 5 个变量的判别函数。在 35 例新生儿中,28 例证实为 CoA。角度测量的 PPV 和 NPV 分别为 100%和 77%。AAo+Aoi-3VV 模型的 PPV 和 NPV 分别为 92%和 80%,Aoi-sag+Aoi-3VV 模型分别为 82%和 71%。利用 3 个最具预测性的变量构建的线性判别模型可将 NPV 提高至 90%,PPV 提高至 100%。

总之,我们验证了角度测量在预测 CoA 方面优于标准模型。一个优化的 3 变量模型在识别 CoA 的同时消除了假阳性,保持了准确性。

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