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The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
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Fatigue, Insomnia, and Disability as Independent Predictors of Depressive Symptoms in Multiple Sclerosis: A
Ceren Alis1, Nuray Kose1, Sibel Sen Kilic1
1Department of Neurology, Sisli Hamidiye Etfal Training and Research Hospital, Istanbul, Türkiye.
Objectives:
This study aimed to identify the clinical factors independently associated with depressive symptoms in patients with multiple sclerosis (MS) and to evaluate the impact of depression on health-related quality of life (QoL).
Methods:
In this prospective observational study, 90 patients with MS were evaluated. Age, sex, disease duration, MS subtype, and Expanded Disability Status Scale (EDSS) scores were recorded. The Fatigue Severity Scale (FSS), Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Leeds Assessment of Neuropathic Symptoms and Signs (S-LANSS) scale, and the EuroQol 5-Dimension 3-Level (EQ-5D-3L) questionnaire were administered. The presence of restless legs syndrome (RLS) was also recorded. Depression severity was measured using the Patient Health Questionnaire-9 (PHQ-9). First, univariable associations were examined, and relevant variables were subsequently entered into a multivariable linear regression model using backward elimination.
Results:
Higher FSS, ISI, and EDSS scores were independently associated with higher PHQ-9 scores. FSS and ISI scores showed the strongest correlations with depression (ρ=+0.52 and +0.57; p<0.001). EDSS showed a modest association (ρ=+0.23, p=0.031). Age, sex, and disease duration were not significant predictors. S-LANSS scores, MS subtype, and RLS were significant in univariate analysis but excluded from the final model. Depression scores were significantly associated with higher EQ-5D-3L scores, indicating poorer QoL (p<0.001).
Conclusion:
Fatigue and insomnia were the strongest independent predictors of depression in MS, surpassing traditional clinical indicators. Routine screening for these symptoms may facilitate earlier detection and treatment of depression and improve QoL in clinical practice.
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