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A simple questionnaire to prevent blindness: a cross-sectional study screening for Stickler syndrome in children

Year: 2026
Type: article
Study design: Observational Study
Abstract: OBJECTIVES: Stickler syndrome is a skeletal dysplasia that is widely under-recognized yet the most common cause of inherited retinal detachment in children. The most prevalent subtype is Stickler syndrome type 1 (STL1), with an autosomal dominant variant in COL2A1 typically resulting in ophthalmic, orofacial, auditory and musculoskeletal manifestations. However, manifestations across these domains are not as prominent in children, making identification of individuals suitable for further assessment difficult. Thus, we sought to test an easy-to-use screening tool capable of differentiating children with STL1 from the general paediatric population. METHODS: Children aged 4-10 years with and without COL2A1-confirmed STL1 were recruited from a single specialist centre and online via the national patient support group Stickler Syndrome UK (Registered Charity number 1060421). A screening tool was administered, and planned analysis of the median final score and individual components of the questionnaire was completed. RESULTS: Twenty-six general paediatric and twenty-eight STL1 participants were recruited. STL1 participants scored higher on screening tool final score with a median score (IQR) of 7 (3.5) vs 0 [1], which was statistically significant on a Mann-Whitney U test (P < 0.001). The sensitivity and specificity were 93% and 96%, respectively, and STL1 participants were more likely to have myopia, palate abnormalities, family history of cleft palate and hypermobility on secondary analysis of the individual screening tool components (Hochberg-corrected all P < 0.005). CONCLUSION: We demonstrate a clinically powerful screening tool capable of identifying children with underlying STL1, and thus this questionnaire can now be applied to at-risk children to inform the need for further specialist assessment.
Language: English
Subfield: Genetics
Open Access status: hybrid
Estimated APC paid: $4,597
OpenAlex ID: W7172017376
FWCI:
Cites: 29
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