AUTHOR=Zhang Chao , Wu Qian-qian , Hou Ying , Wang Qi , Zhang Guang-jian , Zhao Wen-bo , Wang Xu , Wang Hong , Li Wei-guo TITLE=Ophthalmologic problems correlates with cognitive impairment in patients with Parkinson's disease JOURNAL=Frontiers in Neuroscience VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2022.928980 DOI=10.3389/fnins.2022.928980 ISSN=1662-453X ABSTRACT=Objective

Visual impairment is a common non-motor symptom (NMS) in patients with Parkinson's disease (PD) and its implications for cognitive impairment remain controversial. We wished to survey the prevalence of visual impairment in Chinese Parkinson's patients based on the Visual Impairment in Parkinson's Disease Questionnaire (VIPD-Q), identify the pathogens that lead to visual impairment, and develop a predictive model for cognitive impairment risk in Parkinson's based on ophthalmic parameters.

Methods

A total of 205 patients with Parkinson's disease and 200 age-matched controls completed the VIPD-Q and underwent neuro-ophthalmologic examinations, including ocular fundus photography and optical coherence tomography. We conducted nomogram analysis and the predictive model was summarized using the multivariate logistic and LASSO regression and verified via bootstrap validation.

Results

One or more ophthalmologic symptoms were present in 57% of patients with Parkinson's disease, compared with 14% of the controls (χ2-test; p < 0.001). The visual impairment questionnaire showed good sensitivity and specificity (area under the curve [AUC] = 0.918, p < 0.001) and a strong correlation with MoCA scores (Pearson r = −0.4652, p < 0.001). Comparing visual impairment scores between pre- and post-deep brain stimulation groups showed that DBS improved visual function (U-test, p < 0.001). The thickness of the retinal nerve fiber layer and vessel percentage area predicted cognitive impairment in PD.

Interpretation

The study findings provide novel mechanistic insights into visual impairment and cognitive decline in Parkinson's disease. The results inform an effective tool for predicting cognitive deterioration in Parkinson's based on ophthalmic parameters.