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确定新生儿心脏畸形的发病率:一种新颖且经临床批准的解决方案。

Determining the incidence of heart malformations in neonates: A novel and clinically approved solution.

作者信息

Bordbar Arash, Kashaki Mandana, Vafapour Maryam, Sepehri Amir A

机构信息

Shahid Akbarabadi Clinical Research & Development Unit (ShACRDU), Iran University of Medical Sciences (IUMS), Tehran, Iran.

Department of Pediatrics, Ali-Asghar Children's Hospital, Iran University of Medical Sciences, Tehran, Iran.

出版信息

Front Pediatr. 2023 Mar 15;11:1058947. doi: 10.3389/fped.2023.1058947. eCollection 2023.

Abstract

BACKGROUND

Screening for critical congenital heart defects should be performed as early as possible and is essential for saving the lives of children and reducing the incidence of undetected adult congenital heart diseases. Heart malformations remain unrecognized at birth in more than 50% of neonates at maternity hospitals. Accurate screening for congenital heart malformations is possible using a certified and internationally patented digital intelligent phonocardiography machine. This study aimed to assess the actual incidence of heart defects in neonates. A pre-evaluation of the incidence of unrecognized severe and critical congenital heart defects at birth in our well-baby nursery was also performed.

METHODS

We conducted the Neonates Cardiac Monitoring Research Project (ethics approval number: IR-IUMS-FMD. REC.1398.098) at the Shahid Akbarabadi Maternity Hospital. This study was a retrospective analysis of congenital heart malformations observed after screening 840 neonates. Using a double-blind format, 840 neonates from the well-baby nursery were randomly chosen to undergo routine clinical examinations at birth and digital intelligent phonocardiogram examinations. A pediatric cardiologist performed echocardiography for each neonate classified as having abnormal heart sounds using an intelligent machine or during routine medical examinations. If the pediatric cardiologist requested a follow-up examination, then the neonate was considered to have a congenital heart malformation, and the cumulative incidence was calculated accordingly.

RESULTS

The incidence of heart malformations in our well-baby nursery was 5%. Furthermore, 45% of heart malformations were unrecognized in neonates at birth, including one critical congenital heart defect. The intelligent machine interpreted innocent murmurs as healthy heart sound.

CONCLUSION

We accurately and cost-effectively screened for congenital heart malformations in all neonates in our hospital using a digital intelligent phonocardiogram. Using an intelligent machine, we successfully identified neonates with CCHD and congenital heart defects that could not be detected using standard medical examinations. The Pouya Heart machine can record and analyze sounds with a spectral power level lower than the minimum level of the human hearing threshold. Furthermore, by redesigning the study, the identification of previously unrecognized heart malformations could increase to 58%.

摘要

背景

对严重先天性心脏缺陷的筛查应尽早进行,这对于挽救儿童生命及降低未被发现的成人先天性心脏病发病率至关重要。在妇产医院,超过50%的新生儿出生时心脏畸形未被识别。使用经过认证且拥有国际专利的数字智能心音图仪能够准确筛查先天性心脏畸形。本研究旨在评估新生儿心脏缺陷的实际发病率。同时,对我院健康婴儿护理室中出生时未被识别的严重及关键先天性心脏缺陷的发病率进行了预评估。

方法

我们在沙希德·阿克巴拉巴迪妇产医院开展了新生儿心脏监测研究项目(伦理批准号:IR-IUMS-FMD.REC.1398.098)。本研究是对840名新生儿筛查后观察到的先天性心脏畸形进行的回顾性分析。采用双盲形式,从健康婴儿护理室随机选取840名新生儿,在出生时进行常规临床检查及数字智能心音图检查。儿科心脏病专家对每一名经智能机器分类为心音异常或在常规医学检查中被判定心音异常的新生儿进行超声心动图检查。如果儿科心脏病专家要求进行后续检查,则该新生儿被视为患有先天性心脏畸形,并据此计算累积发病率。

结果

我院健康婴儿护理室中心脏畸形的发病率为5%。此外,45%的心脏畸形在新生儿出生时未被识别,其中包括一例严重先天性心脏缺陷。智能机器将无害杂音解读为健康心音。

结论

我们使用数字智能心音图对我院所有新生儿进行了准确且经济高效的先天性心脏畸形筛查。通过智能机器,我们成功识别出了患有严重先天性心脏缺陷及使用标准医学检查无法检测出的先天性心脏缺陷的新生儿。普亚心脏机器能够记录和分析频谱功率水平低于人类听力阈值最低水平的声音。此外,通过重新设计研究,先前未被识别的心脏畸形的识别率可能会提高到58%。

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本文引用的文献

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Artificial intelligence-assisted auscultation in detecting congenital heart disease.人工智能辅助听诊在先天性心脏病检测中的应用
Eur Heart J Digit Health. 2021 Jan 6;2(1):119-124. doi: 10.1093/ehjdh/ztaa017. eCollection 2021 Mar.
9
Adult congenital heart disease: Past, present and future.成人先天性心脏病:过去、现在和未来。
Acta Paediatr. 2019 Oct;108(10):1757-1764. doi: 10.1111/apa.14921. Epub 2019 Aug 18.

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