EP11.01: Impact of detection rate for congenital heart disease by national surgical registry in Japan

AbstractObjectiveThe aim of this study is to evaluate the cumulative detection rate of foetal echocardiography during gestation and in the early neonatal period, with a special emphasis on early foetal echocardiography.MethodsWe conducted a retrospective survey of all singleton pregnancies from 1993 to 2007, with complete sequential echocardiography from 11 plus 0 to 13 plus 6 weeks of gestation. It was mandatory to have at least one foetal echocardiography in the second or third trimester and one postnatally.ResultsOur study included 3521 pregnancies, in which 77 cases were diagnosed with congenital heart disease. Of them, 66 were detected in the first trimester – 11 plus 0 to 11 plus 6 weeks: 22 cases; 12 plus 0 to 12 plus 6 weeks: 23 cases; 13 plus 0 to 13 plus 6 weeks: 21 cases – with an 85.7% detection rate of congenital heart disease in early foetal echocardiography. In the second trimester, seven cases were found, with a detection rate of 9.1%. The third trimester reported two cases, with a detection rate of 2.6%. Postnatally, two (2.6%) cases were detected. The overall in utero detection rate of congenital heart disease was 97.4%.ConclusionsFoetal echocardiography performed at the time of anomaly screening in the first trimester results in high detection rates of congenital heart disease. Cardiac pathology may evolve, and further examinations at later stages of pregnancy could improve the detection rate of congenital heart disease.

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OC067: Detection rate of early fetal echocardiography and spectrum of congenital heart disease

Ultrasound in Obstetrics and Gynecology ◽

10.1002/uog.5475 ◽

2008 ◽

Vol 32 (3) ◽

pp. 264-264

Author(s):

R. Axt-Fliedner ◽

J. Lietz ◽

D. Hartge ◽

M. Krapp ◽

A. Geipel ◽

...

Keyword(s):

Congenital Heart Disease ◽

Heart Disease ◽

Detection Rate ◽

Congenital Heart ◽

Fetal Echocardiography

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Newborn pulse oximetry screening in the context of a high antenatal detection rate of critical congenital heart disease

Acta Paediatrica ◽

10.1111/apa.14946 ◽

2019 ◽

Vol 109 (1) ◽

pp. 93-99

Author(s):

Elza Cloete ◽

Frank H. Bloomfield ◽

Sharnie A. Cassells ◽

Monique W. M. Laat ◽

Lynn Sadler ◽

...

Keyword(s):

Congenital Heart Disease ◽

Heart Disease ◽

Pulse Oximetry ◽

Detection Rate ◽

Congenital Heart ◽

Critical Congenital Heart Disease ◽

Antenatal Detection ◽

Pulse Oximetry Screening

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Clinical Application of Chromosomal Microarray Analysis in Fetuses with Congenital Heart Disease

10.21203/rs.3.rs-1176209/v1 ◽

2021 ◽

Author(s):

Yuxia Jin ◽

Suping Li ◽

Ping Tang ◽

Jie Chen ◽

Jing Yang ◽

...

Keyword(s):

Congenital Heart Disease ◽

Heart Disease ◽

Pregnant Women ◽

Clinical Application ◽

Detection Rate ◽

Congenital Heart ◽

Chromosomal Abnormalities ◽

Karyotype Analysis ◽

Snp Array ◽

Genetic Causes

Abstract Background: Congenital heart disease (CHD) is an important birth defect, but its mechanism is still unclear. In recent years, genetic causes including chromosomal abnormalities are associated with the occurrence of congenital heart disease. In this study, CMA technology is applied to explore the genetic causes of congenital heart disease, so as to further clarify the correlation between genotype and phenotype and prepare for late pregnancy intervention and postnatal diagnosis and treatment.Objective: To explore the chromosomal abnormalities and copy number variation (CNVs) of fetuses with CHD by CMA technology, and to clarify the clinical application value of CMA technology as a detection method of first-tier antenatal CHD.Methods: Amniotic fluid sample from 155 pregnant women diagnosed with fetus CHD by prenatal ultrasound from 2018 to 2021 are collected for SNP-array detection and karyotype analysis. According to the detected CNVs results, FISH, CMA or karyotype analysis are further selected for parental verification.Results: Among the 155 fetuses with CHD, a total of 32 (20.6%) cases of chromosomal abnormalities are detected, of which 31.3% are chromosome number abnormalities. CNVs of likely pathogenicity and unknown significance are 2.5% and 5.2% respectively. The detection rate of chromosomal abnormalities in CHD of different subtypes is different, among which the high detection rate is complex CHD (31.2%), right ventricular outflow tract obstruction (30.7%) and conotruncal defects (25%). The detection rate of chromosomal abnormalities in CHD with extracardiac structural abnormalities is significantly higher than that in isolated CHD (52.4% vs 11.3%, p<0.05). In addition, the detection rate of CHD with abnormal extracardiac structure is significantly higher than that of CHD with soft markers (52.4% vs 17.8%, p<0.05), which is statistically significant. There is no significant difference in detection rate between CHD with soft markers and isolated CHD (17.8% vs 11.3%). Of the 155 pregnant women with fetus CHD, 59 chose to terminate their pregnancies, some of which were terminated according to the results of SNP-array, and some of which were terminated according to the severity of CHD.Conclusion: SNP-array technology can be used to detect chromosomal abnormalities of first-tier antenatal CHD fetuses, with high resolution, short reporting period and high efficiency. Meanwhile, pregnancy intervention can be taken according to the results.

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Recognition of Child Congenital Heart Disease Using Cardiac Cycle Segment of Electrocardiogram

10.3233/atde210249 ◽

2021 ◽

Author(s):

Yunmei Du ◽

Canhui Huang ◽

Shuai Huang ◽

Huiying Liang

Keyword(s):

Congenital Heart Disease ◽

Heart Disease ◽

Detection Rate ◽

Congenital Heart ◽

Cardiac Cycle ◽

Screening Method ◽

Independent Set ◽

Data Set ◽

Sensitivity Specificity ◽

Segment Data

The results of previous studies showed that ECG could detect CHD in children with a detection rate of 76.43%. Although this result is better than the traditional CHD screening method, the sensitivity still needs to be improved if it is to be popularized clinically. Based on the previous ECG recording data, this study selects the more representative cardiac cycle segments to identify CHD, in order to achieve better screening effect. Firstly, better cardiac cycle segment data were extracted from ECG records of each patient. The final data set contains 72626 patients and each patient has a 9-lead ECG segment with duration of about one second. Then we trained a RoR network to identify the underlying patients with CHD using 62626 samples in the dataset. When tested on an independent set of 10000 patients, the network model yielded values for the sensitivity, specificity, and accuracy of 0.93, 86.3%, 85.7%, and 85.7% respectively. It can be seen that extracting more effective cardiac cycle fragments can significantly improve the sensitivity of CHD screening on the basis of ensuring better specificity, so as to find more potential patients with congenital heart disease.

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