ArticleGenetics in medicine : official journal of the American College of Medical Genetics2025
Clinical factors associated with genetic diagnosis in suspected neurogenetic disorders in a tertiary care clinic.
Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Precision diagnostic and therapeutic interventions in rare genetic neurodevelopmental disorders.Pediatric research · 2025Review
- Clinical determinants of psychiatric care in genetic neurodevelopmental disorders: a cross-sectional analysis.Journal of neurodevelopmental disorders · 2025Article
- Impact of Genetic Testing Using Gene Panels, Exomes, and Genome Sequencing in Romanian Children with Epilepsy.International journal of molecular sciences · 2025Article
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Authors and funding
10 authors.
Funding
Abstract
purposeThis study aimed to identify phenotypic factors associated with genetic diagnoses in patients with neurodevelopmental disorders and generate a decision tree to assist clinicians in identifying patients most likely to receive a positive result on genetic testing.
methodsWe retrospectively reviewed the charts of 316 patients evaluated in a neurodevelopmental clinic between 2014 and 2019. Patients were categorized based on genetic test results. Analyses were performed to identify variables that discriminate between patients with and without a genetic diagnosis.
resultsPatients with a genetic diagnosis were more likely to be female and have a history of motor delay, hypotonia, congenital heart disease, and early intervention. Classification and regression tree analysis revealed that 75% of patients with motor delay had a genetic diagnosis. In patients without motor delay, hypotonia, age of walking, and age at initial evaluation were important indicators of a genetic diagnosis.
conclusionOur findings suggest that motor delay and hypotonia are associated with genetic diagnoses in children with neurodevelopmental disorders. The decision tree highlights patient subsets at greater risk and suggests possible phenotypic screens. Future studies could develop validated decision trees based on phenotypic data to assist clinicians in stratifying patients for genetic testing.
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