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Published in: Neurological Sciences 3/2024

14-10-2023 | Intense Pulsed Light | Original Article

Retinal clues for selective neuronal loss in multiple sclerosis

Authors: Vedat Cilingir, Erbil Seven

Published in: Neurological Sciences | Issue 3/2024

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Abstract

Objective

The relationship between the cell body layer and the dendritic network layer of the retina and cognitive performance (CP) in MS patients has not been examined separately. The objective of this study is to predict cognitive impairment (CI) in RRMS patients and to examine the relationship between CP and ganglion cell layer (GCL), inner plexiform layer (IPL), and GCL divided by IPL (GCL/IPL).

Methods

Ophthalmological evaluation, retinal segmentation, and Symbol Digit Modalities Test (SDMT) were performed on 102 RRMS patients and 54 healthy subjects. The relationships of GCL, IPL, and GCL/IPL with CP in eyes without a history of optic neuritis were investigated using Spearman’s correlation. Models were created by accepting 1 standard deviation less of the SDMT mean of the control group as the limit for CI. The cutoff value of the GCL/IPL variable that could predict CI was calculated by ROC analysis, and the ability to accurately predict CI was tested with binary logistic regression.

Results

No correlation was found between OCT parameters and CP in healthy subjects. Correlation was found between GCL thickness and GCL/IPL variable and CP in RRMS patients (r=0.235, r=0.667 respectively). A GCL/IPL value of 1.255 was able to identify CI with 81.8% sensitivity and 75.9% specificity (AUC=0.844, LR=3.38) and predicted CI with 74.5% accuracy (Nagelkerke R2=0.439).

Conclusion

In RRMS patients, the IPL thickness is unrelated to CP. Therewithal, the GCL/IPL-CP relationship is stronger than the GCL-CP relationship and GCL/IPL can predict CI.
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Metadata
Title
Retinal clues for selective neuronal loss in multiple sclerosis
Authors
Vedat Cilingir
Erbil Seven
Publication date
14-10-2023
Publisher
Springer International Publishing
Published in
Neurological Sciences / Issue 3/2024
Print ISSN: 1590-1874
Electronic ISSN: 1590-3478
DOI
https://doi.org/10.1007/s10072-023-07110-2

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