EARLY DIAGNOSIS OF CONGENITAL CRANIOFACIAL DIFFERENCES: A SYSTEMATIC REVIEW OF CURRENT EVIDENCE
DOI:
https://doi.org/10.21142/Keywords:
early diagnosis, craniofacial abnormalities, cleft lip, cleft palate, prenatal ultrasonography, magnetic resonance imagingAbstract
Introduction: Craniofacial congenital differences (CCDs) impact vital functions and have psychosocial implications. Early diagnosis is crucial to optimize prognosis and quality of life. Objective To analyze the current evidence on the early diagnosis of CCDs, identifying effective methodologies and gaps in knowledge. Materials and Methods: This systematic review was conducted following the PRISMA 2020 guidelines. The literature search included 25 studies published between January 2020 and June 2025, covering a variety of designs, such as cohort studies, diagnostic accuracy studies, and randomized controlled trials (RCTs). The consulted databases were PubMed, Scopus, Web of Science, ScienceDirect, LILACS, and Cochrane Library. Study selection and data extraction were performed independently by two reviewers to ensure the reliability of the information. The methodological quality and risk of bias of the included studies were assessed using specific tools: QUADAS-2 for diagnostic accuracy studies, RoB 2.0 or RCTs, and the Newcastle-Ottawa Scale (NOS) for cohort studies. Finally, the overall certainty of evidence was determined using the GRADE rating system. Results: Prenatal ultrasound showed 75% sensitivity and 98% specificity for cleft lip and palate. Fetal MRI achieved 90% sensitivity and 97% specificity for complex CCDs. Prenatal methods allowed for earlier diagnosis (mean 24 weeks of gestation) and facilitated clinical planning. Evidence of the long-term impact on functional/aesthetic prognosis was limited (very low GRADE). Adverse effects were minimal. Conclusions: Prenatal ultrasound and fetal MRI are useful for the early diagnosis of CCDs, improving clinical management. Rigorous research is needed, especially longitudinal studies, to evaluate long-term prognosis and address global disparities.
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This work is licensed under a Creative Commons Attribution 4.0 International License.

Este obra está bajo una licencia de Creative Commons Reconocimiento 4.0 Internacional.






