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Beyond EDSS: Memory-guided saccades as candidate digital biomarkers of processing speed and fatigue in MS-A
Mariano Ruiz-Ortiz1, Cecilia García-Cena2, Rosa Hernández-Ramírez3
1Department of Neurology, 12 de Octubre University Hospital, Madrid, Spain; Hospital Universitario 12 de Octubre Research Institute (imas12), Madrid, Spain; Complutense University of Madrid (PhD Program in Medical and Surgical Sciences), Madrid, Spain.
Background:
Disability monitoring in multiple sclerosis (MS) relies on EDSS and MRI lesion metrics that are often insensitive to cognitive dysfunction and fatigue.
Objective:
To test whether memory-guided saccade (MGS) performance relates to processing speed and fatigue independent of mood symptoms, EDSS, and MRI inflammatory activity.
Methods:
Forty-four MS patients completed MGS eye tracking. Error types and Total Task Error Rate were related to the Symbol Digit Modalities Test (SDMT), fatigue impact, mood scales, EDSS, and MRI lesion measures (including 5-year new T2 lesions) using age- and sex-adjusted partial correlations with mood sensitivity analyses.
Results:
Mean Total Task Error Rate was 21.5% (SD 20.6); delay errors predominated. Lower SDMT scores correlated with more delay errors (r = -0.47, p = 0.002) and higher Total Task Error Rate (r = -0.40, p = 0.008). Greater fatigue correlated with more omissions (r = 0.36, p = 0.018) and higher Total Task Error Rate (r = 0.35, p = 0.022). Associations persisted after mood adjustment. No relationships were observed with EDSS or new T2 lesions (all p > 0.1).
Conclusions:
Preliminary, exploratory associations were observed between MGS metrics and measures of processing speed and fatigue in MS, independent of EDSS and MRI lesion activity. These findings should be regarded as hypothesis-generating and support further investigation of MGS as a candidate functional digital biomarker in larger, prospective, controlled studies with longitudinal follow-up and test-retest reliability assessment.
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