ATRIOVENTRICULAR CANAL DEFECT

Abstract

Atrioventricular canal defects (AVCD) is a spectrum of congenital heart defects (CHD) raging from large isolated ventricular septal defect or atrial septal defect, endocardial cushions anomalies to complete atrioventricular septal defect. The Rastelli classification further categorizes AVCD into 3 types, depending on the morphology of atrioventricular valvular apparatus. Usually, they arise in the setting of chromosomal aneuploydies such as Trisomy 21, chromosomal deletion syndromes, ciliopahties, RASopathies, or monogenic disorders affecting EVC, EVC2, WDR35, DYNC2LI1, and DYNC2H1 genes. Material and methods: This paper discusses recent advances in multidisciplinary diagnosis and treatment in cases with AVCD. Pubmed and ScienceDirect have been used as scientific databases and atrivoentricular canal, gene editing, machine learning, medical mangement, surgical repairment were the main research keywords. Results: Classically, AVCD management is a 3 step process. Firstly, medical management aims at improving myocardial function by acting both on the ventricular preload and postload using diuretics and Angiotensin-converting enzyme inhibitors, and enhancing myocardial contractility. Staged surgical management should be undertaken between 3-6 months of age and it involves primary defect repair or palliative interventions, depending on the severity of the cardiac defect. Recent therapeutic strategies are based on the CRISPR- Casp9 gene editing technologies. Promising results have been obtained in animal models of RASopathies and ongoing research is focused on extending its application in monogenic mutations implicated in AVCD etiology. Machine learning techniques have been deployed in order to achieve early CHD diagnostic, evaluate recurrence risk, establish long-term prognosis and tailored medical management.

Keywords

• atrioventricular canal defect
• machine learning
• gene editing
• genetic anomalies
• management