Literature DB >> 33044738

Dyschromatopsia in multiple sclerosis reflects diffuse chronic neurodegeneration beyond anatomical landmarks.

Antonio Barreiro-González1, Maria T Sanz2, Sara Carratalà-Boscà3, Francisco Pérez-Miralles3, Carmen Alcalá3, Enrique España-Gregori4,5, Bonaventura Casanova3,6.   

Abstract

To formulate and validate a dyschromatopsia linear regression model in patients with multiple sclerosis (MS). 64 MS patients (50 to formulate the model and 14 for its validation) underwent neurological (Expanded Disability Status Scale, EDSS), color vision (Farnsworth D15 test), and peripapillary retinal nerve fiber layer (pRNFL) and retinal evaluation with spectral-domain optical coherence tomography (SD-OCT). Neuroradiological examination permitted to obtain brain parenchymal fraction (BPF) and cervical spinal cord volume (SC). Ophthalmic parameters were calculated as the average of both non-optic neuritis (ON) eyes, and in case the patient had previous ON, the value of the fellow non-ON eye was taken. The influence of sex, age, disease duration, and history of disease-modifying treatment (first- or second-line DMT) was tested as covariables that could influence color perception. Color confusion index (log CCI) correlated with pRNFL (r =  - 0.322, p = 0.009), ganglion cell layer (GCL, r =  - 0.321, p = 0.01), BPF (r =  - 0.287, p = 0.021), SC volume (r =  - 0.33, p = 0.008), patients' age (r = 0.417, p = 0.001), disease duration (r = 0.371, p = 0.003), and EDSS (r = 0.44, p = 0.001). The following CCI equation was obtained: log (CCI) = 0.316-0.224 BPF - 0.187 SC volume (mm3) + 0.226 age (years) + 0.012 disease duration (years) - 0.372 GCL (µm). CCI correlates with MS clinical and paraclinical established biomarkers suggesting chronic diffuse neurodegeneration in MS operates at brain, SC, and retina linking all three compartments. Color vision outcome can be calculated through the aforementioned variables for clinical and research purposes.
© 2020. Belgian Neurological Society.

Entities:  

Keywords:  Color vision defects; Magnetic resonance imaging; Multiple sclerosis; Neurodegeneration; Optical coherence tomography

Mesh:

Year:  2020        PMID: 33044738     DOI: 10.1007/s13760-020-01516-x

Source DB:  PubMed          Journal:  Acta Neurol Belg        ISSN: 0300-9009            Impact factor:   2.396


  38 in total

Review 1.  Optical coherence tomography and multiple sclerosis: Update on clinical application and role in clinical trials.

Authors:  Jeffrey Lambe; Shiv Saidha; Robert A Bermel
Journal:  Mult Scler       Date:  2019-09-06       Impact factor: 6.312

Review 2.  Afferent visual pathways in multiple sclerosis: a review.

Authors:  Stuart L Graham; Alexander Klistorner
Journal:  Clin Exp Ophthalmol       Date:  2016-04-28       Impact factor: 4.207

3.  The dyschromatopsia of optic neuritis is determined in part by the foveal/perifoveal distribution of visual field damage.

Authors:  S E Silverman; W M Hart; M O Gordon; C Kilo
Journal:  Invest Ophthalmol Vis Sci       Date:  1990-09       Impact factor: 4.799

4.  Retinal periphlebitis is associated with multiple sclerosis severity.

Authors:  Santiago Ortiz-Pérez; Elena H Martínez-Lapiscina; Iñigo Gabilondo; Elena Fraga-Pumar; Eloy Martínez-Heras; Albert Saiz; Bernardo Sanchez-Dalmau; Pablo Villoslada
Journal:  Neurology       Date:  2013-07-31       Impact factor: 9.910

5.  Primary retinal pathology in multiple sclerosis as detected by optical coherence tomography.

Authors:  Shiv Saidha; Stephanie B Syc; Mohamed A Ibrahim; Christopher Eckstein; Christina V Warner; Sheena K Farrell; Jonathan D Oakley; Mary K Durbin; Scott A Meyer; Laura J Balcer; Elliot M Frohman; Jason M Rosenzweig; Scott D Newsome; John N Ratchford; Quan D Nguyen; Peter A Calabresi
Journal:  Brain       Date:  2011-01-20       Impact factor: 13.501

Review 6.  Monitoring the Course of MS With Optical Coherence Tomography.

Authors:  Alexander U Brandt; Elena H Martinez-Lapiscina; Rachel Nolan; Shiv Saidha
Journal:  Curr Treat Options Neurol       Date:  2017-04       Impact factor: 3.598

7.  Patient perception of bodily functions in multiple sclerosis: gait and visual function are the most valuable.

Authors:  C Heesen; J Böhm; C Reich; J Kasper; M Goebel; S M Gold
Journal:  Mult Scler       Date:  2008-05-27       Impact factor: 6.312

Review 8.  Vision Disturbances in Multiple Sclerosis.

Authors:  Fiona Costello
Journal:  Semin Neurol       Date:  2016-04-26       Impact factor: 3.420

Review 9.  Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis.

Authors:  Laura J Balcer; Jenelle Raynowska; Rachel Nolan; Steven L Galetta; Raju Kapoor; Ralph Benedict; Glenn Phillips; Nicholas LaRocca; Lynn Hudson; Richard Rudick
Journal:  Mult Scler       Date:  2017-02-16       Impact factor: 6.312

10.  Predictors of vision impairment in Multiple Sclerosis.

Authors:  Bernardo Sanchez-Dalmau; Elena H Martinez-Lapiscina; Irene Pulido-Valdeolivas; Irati Zubizarreta; Sara Llufriu; Yolanda Blanco; Nuria Sola-Valls; Maria Sepulveda; Ana Guerrero; Salut Alba; Magi Andorra; Anna Camos; Laura Sanchez-Vela; Veronica Alfonso; Albert Saiz; Pablo Villoslada
Journal:  PLoS One       Date:  2018-04-17       Impact factor: 3.240

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