Purchase this article with an account.
Elena Garcia-Martin, Diego Rodriguez-Mena, Maria Satue, Carmen Almarcegui, Isabel Dolz, Raquel Alarcia, Maria Seral, Vicente Polo, Jose M. Larrosa, Luis E. Pablo; Electrophysiology and Optical Coherence Tomography to Evaluate Parkinson Disease Severity. Invest. Ophthalmol. Vis. Sci. 2014;55(2):696-705. doi: 10.1167/iovs.13-13062.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
To evaluate correlations between visual evoked potentials (VEP), pattern electroretinogram (PERG), and macular and retinal nerve fiber layer (RNFL) thickness measured by optical coherence tomography (OCT) and the severity of Parkinson disease (PD).
Forty-six PD patients and 33 age and sex-matched healthy controls were enrolled, and underwent VEP, PERG, and OCT measurements of macular and RNFL thicknesses, and evaluation of PD severity using the Hoehn and Yahr scale to measure PD symptom progression, the Schwab and England Activities of Daily Living Scale (SE-ADL) to evaluate patient quality of life (QOL), and disease duration. Logistical regression was performed to analyze which measures, if any, could predict PD symptom progression or effect on QOL.
Visual functional parameters (best corrected visual acuity, mean deviation of visual field, PERG positive (P) component at 50 ms -P50- and negative (N) component at 95 ms -N95- component amplitude, and PERG P50 component latency) and structural parameters (OCT measurements of RNFL and retinal thickness) were decreased in PD patients compared with healthy controls. OCT measurements were significantly negatively correlated with the Hoehn and Yahr scale, and significantly positively correlated with the SE-ADL scale. Based on logistical regression analysis, fovea thickness provided by OCT equipment predicted PD severity, and QOL and amplitude of the PERG N95 component predicted a lower SE-ADL score.
Patients with greater damage in the RNFL tend to have lower QOL and more severe PD symptoms. Foveal thicknesses and the PERG N95 component provide good biomarkers for predicting QOL and disease severity.
This PDF is available to Subscribers Only