ArticleFrontiers in integrative neuroscience2023
Autosomal recessive cerebellar ataxias: a diagnostic classification approach according to ocular features.
Article in Frontiers in integrative neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- How Early Should I Refer My Patient? The Benefits of a Quick Ophthalmic Referral in Spinocerebellar Ataxias, a Case Series and Literature Review.Brain sciences · 2026Article
- Molecular characterization of recessively inherited ataxic and neuropathic disorders in consanguineous Pakistani families.Scientific reports · 2026Article
- Autosomal Recessive Cerebellar Ataxia-27 Caused by a Novel Loss-of-Function Variant of Ganglioside-Induced Differentiation Associated Protein 2 in a Spanish Family.Neurology. Genetics · 2025Article
- Clinical whole Exome Sequencing Reveals Novel Homozygous Missense Variant in thePakistan journal of medical sciences · 2024Article
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6 authors.
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Abstract
Autosomal recessive cerebellar ataxias (ARCAs) are a heterogeneous group of neurodegenerative disorders affecting primarily the cerebellum and/or its afferent tracts, often accompanied by damage of other neurological or extra-neurological systems. Due to the overlap of clinical presentation among ARCAs and the variety of hereditary, acquired, and reversible etiologies that can determine cerebellar dysfunction, the differential diagnosis is challenging, but also urgent considering the ongoing development of promising target therapies. The examination of afferent and efferent visual system may provide neurophysiological and structural information related to cerebellar dysfunction and neurodegeneration thus allowing a possible diagnostic classification approach according to ocular features. While optic coherence tomography (OCT) is applied for the parametrization of the optic nerve and macular area, the eye movements analysis relies on a wide range of eye-tracker devices and the application of machine-learning techniques. We discuss the results of clinical and eye-tracking oculomotor examination, the OCT findings and some advancing of computer science in ARCAs thus providing evidence sustaining the identification of robust eye parameters as possible markers of ARCAs.
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