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Provincial variability in congenital heart disease prevalence in Argentina, 2014-2019: A population-based analysis from national registry data

Vita, M. C.; Fantozzi, N.; Ortiz, F. M.; Di Lullo, L.; Kokal, R.; Peralta, S.; Di Lalla, S.

2025-09-07 epidemiology
10.1101/2025.09.04.25335135 medRxiv
Show abstract

Congenital heart defects are a leading cause of neonatal morbidity and mortality worldwide. Early diagnosis is essential to enable timely treatment and improve patient outcomes; however, access to early detection and specialized care is unevenly distributed across regions in Argentina. This study describes the prevalence and timing of diagnosis of congenital heart defects and critical congenital heart defects among live births covered by the public health system nationwide. We performed a cross-sectional, descriptive, ecological study including all live births between 2014 and 2019 with a diagnosis of congenital heart defects reported up to five years of age in the National Registry of Congenital Heart Diseases. We calculated prevalence rates and median age at case notification for each province to assess geographic disparities. Out of 2,473,720 live births, 16,150 cases of congenital heart defects (prevalence 65.3 per 10,000 live births) and 3,700 cases of critical congenital heart defects (15.0 per 10,000) were identified. Provincial prevalence ranged widely, from 34.9 to 212.2 per 10,000 for congenital heart defects and from 10.7 to 27.3 per 10,000 for critical cases. The national median age at notification was 75 days for all congenital heart defects and 29 days for critical cases, with notable provincial differences. These findings demonstrate significant provincial variability in both the prevalence of congenital heart defects and the age at which cases are reported to the national health registry. Strengthening early detection efforts and ensuring equitable access to specialized care are crucial to reduce morbidity and mortality associated with these conditions in Argentina and similar settings.

Published in PLOS Global Public Health (predicted rank #4) · training set

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