Literature DB >> 32227522

Differential diagnosis of fetal large ventricular septal defect and tetralogy of Fallot based on big data analysis.

Jing Lv1, Tingyang Yang2, Xiaoyan Gu1, Ye Zhang1, Lin Sun1, Ying Zhao1, Xiaowei Liu1, Jiancheng Han1, Suzhen Ran3, Zhikun Zhang4, Haogang Zhu2, Yihua He1.   

Abstract

BACKGROUND AND OBJECTIVES: To analyze echocardiographic parameters of fetal large ventricular septal defect (VSD) and tetralogy of Fallot (TOF) in the context of multicenter data and big data analysis because these two diseases are often misdiagnosed in fetuses, and to find the key parameters for the differential diagnosis of these two diseases.
METHODS: A total of 305 cases of large VSD and 192 cases of TOF diagnosed by fetal echocardiography from August 2010 to July 2016 from the database of Beijing Key Laboratory of Fetal Heart Defects were analyzed. Quantile regression of the 48 echocardiographic parameters of the 6272 normal fetuses from seven Chinese medical institutions was performed to determine the Q-score. The forward selection method and the naive Bayesian classification method were used to analyze the core differential diagnostic variables of fetal TOF and VSD.
RESULTS: The Q-score of the internal diameter of the aorta (AO Q-score), the ratio of the diameter of the pulmonary artery to the internal diameter of the aorta (PA/AO), and the Q-score of the ratio of the diameter of the pulmonary artery to the internal diameter of the aorta (PA/AO Q-score) were key parameters for the differential diagnosis of fetal large VSD and TOF. PA/AO was the primary parameter, with an area under the receiver operating characteristic curve of 0.951.
CONCLUSIONS: These findings provide a new method for the prenatal diagnosis of large VSD and TOF and a theoretical basis for the intelligent diagnosis of large VSD and TOF.
© 2020 Wiley Periodicals, Inc.

Entities:  

Keywords:  big data analysis; fetal echocardiography; fetal large ventricular septal defect; tetralogy of fallot

Mesh:

Year:  2020        PMID: 32227522     DOI: 10.1111/echo.14642

Source DB:  PubMed          Journal:  Echocardiography        ISSN: 0742-2822            Impact factor:   1.724


  1 in total

1.  Artificial Intelligence-Based Echocardiographic Left Atrial Volume Measurement with Pulmonary Vein Comparison.

Authors:  Mengyun Zhu; Ximin Fan; Weijing Liu; Jianying Shen; Wei Chen; Yawei Xu; Xuejing Yu
Journal:  J Healthc Eng       Date:  2021-12-06       Impact factor: 2.682

  1 in total

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