Purpose: To investigate visual function in the central 10 degrees in patients who have undergone vigabatrin (VGB) antiepileptic drug (AED) therapy with the aim of identifying a clinical regimen for assessing central visual function.
Methods: The sample comprised 12 epilepsy patients (mean age, 38.6 +/- 11.7 years) who had been treated with VGB (either as monotherapy or polytherapy). A number of central visual-function tests were carried out for each eye, including high-contrast LogMAR visual acuity, short-wavelength automated perimetry (SWAP 10-2), spatial contrast sensitivity (CSV-1000), and Farnsworth-Munsell (FM) 100-hue colour discrimination.
Results: The group mean cumulative VGB dose was 5,086 +/- 3,245 g. The average SWAP 10-2 mean deviation (MD) for the group was -3.24 +/- 3.23 dB; 14 eyes of eight patients showed defects (range, -1.62 to -9.46 dB). The square root of the group mean total error score for FM 100-hue was 7.42 +/- 3.84; nine eyes of five patients were classified as abnormal with an unsolved colour axis suggestive of complex drug interactions. For contrast sensitivity, 15 eyes of eight patients yielded abnormal results in one or more spatial frequencies. Defects were more prominent at higher spatial frequencies. Overall, four patients had defects in all three visual-function tests, six patients had mixed defects, and two patients were normal.
Conclusions: Visual-function deficits in epilepsy patients treated with VGB are present in the central 10 degrees of the retina. We recommend a battery of investigations, including SWAP 10-2 and spatial contrast sensitivity testing, to assess central visual function.
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http://dx.doi.org/10.1046/j.1528-1157.2002.00502.x | DOI Listing |
Neurosurg Rev
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Department of Ophthalmology, Renmin Hospital of Wuhan University, Jiefang Road, Wuhan, Hubei, 430060, China.
Diabetic retinopathy is a major ocular complication of diabetes, characterized by progressive retinal microvascular damage and significant visual impairment in working-age adults. Traditional bulk RNA sequencing offers overall gene expression profiles but does not account for cellular heterogeneity. Single-cell RNA sequencing overcomes this limitation by providing transcriptomic data at the individual cell level and distinguishing novel cell subtypes, developmental trajectories, and intercellular communications.
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