Multicenter observational study reveals 13.1% prevalence of congenital abnormalities in pregnant women, suggesting urgent need for systematic ultrasound screening.
Background and Objectives: Congenital abnormalities are a leading cause of neonatal morbidity and mortality and are frequently detectable through prenatal ultrasound. While widely implemented in high-income countries, such screening remains inconsistently applied in low- and middle-income regions. This study aimed to estimate the prevalence of congenital abnormalities identified via prenatal ultrasound in Lebanon and to explore associated maternal, obstetric, and psychosocial factors. Methods: A multicenter retrospective observational study, supplemented by follow-up interviews, was conducted in five Order of Malta medical centers. Pregnant women in their second trimester underwent an obstetric ultrasound, and data were collected through structured questionnaires and follow-up phone interviews. Variables included maternal demographics, obstetric history, anxiety levels (GAD-7 scores), and ultrasound findings. Results: A total of 426 pregnant women were enrolled (mean age: 28.8 ± 5.9 years). The overall prevalence of congenital abnormalities was 13.1%. Growth abnormalities were observed in 8.5% of fetuses and were significantly associated with obstetric complications and the presence of multiple abnormalities. Morphological malformations were found in 10.1% of cases and were more common among women of advanced maternal age, those with a history of anomalies, and those reporting elevated anxiety scores. Combined abnormalities, as well as growth and morphological malformations, were significantly associated with higher parity, prior anomalies, and current pregnancy complications. Conclusions: Prenatal ultrasound is essential for early detection of congenital abnormalities, facilitating timely intervention and improved neonatal outcomes. These findings emphasize the need to integrate systematic screening into prenatal care in Lebanon and for ongoing research to identify context-specific risk factors.
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Chebl et al. (2025) studied this question.
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