Advancing prenatal diagnosis: Echocardiographic detection of Scimitar syndrome in China – A case series
Objective: To investigate the clinical value of echocardiographic detection in the prenatal early diagnosis of Scimitar syndrome (SS) in fetuses, and to develop better and more accurate management strategies for improved prognosis. Methods: A retrospective analysis was conducted on medical records and fetal echocardiographic findings of all cases diagnosed as SS between April 1, 2016 and June 1, 2021. To summarize its echocardiographic features and distinguishing points, comprehensive clinical data and prognostic information were gathered. Results: Six patients were diagnosed with SS during the study period. Major associated abnormalities included atrial septal defect (n = 3), right inferior pulmonary vein anomalies (n = 2), ventricular septal defect (n = 1), and right aortic arch (n = 1). Post-surgery, all patients exhibited unobstructed pulmonary vein flow and absence of pulmonary hypertension. The average follow-up duration was 24 months, during which five infants underwent surgical intervention for SS. Conclusion: Comprehensive prenatal screening, particularly combined coronal and sagittal views of the fetal thorax, enables accurate diagnosis of right SS. This approach not only aids in timely intervention but also provides crucial prognostic insights for the child’s future well-being.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Advancing prenatal diagnosis: Echocardiographic detection of Scimitar syndrome in China – A case series ; volume:19 ; number:1 ; year:2024 ; extent:7
Open medicine ; 19, Heft 1 (2024) (gesamt 7)
- Urheber
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Wang, Yan
Geng, Bin
Yang, Peizhi
Li, Wenxiu
- DOI
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10.1515/med-2024-0989
- URN
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urn:nbn:de:101:1-2407081550106.632110358341
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:44 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Wang, Yan
- Geng, Bin
- Yang, Peizhi
- Li, Wenxiu
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