Akademska digitalna zbirka SLovenije - logo
E-viri
Celotno besedilo
Recenzirano Odprti dostop
  • Mohammad Yazdan Panah; Yousef Mokary; Arshia Ghalamkari; Ahmad Pourmohammadi; Saba Naghavi; Iman Adibi; Fereshteh Ashtari

    Neurology letters, 01/2023, Letnik: 2, Številka: Supplementary 1 (20th Iranian Multiple Sclerosis Congress)
    Journal Article

    Background: Sleep disorders are more prevalent in people with multiple sclerosis (pwMS) than in the general population. This study aimed to examine the clinical and sociodemographic factors contributing to sleep disorders in pwMS. Method: The participants in this cross-sectional study were pwMS from the Isfahan Province in Iran. Sleep disorders were assessed using the Insomnia Severity Index (ISI), International Restless Legs Syndrome Study Group (IRLSSG), Berlin, and STOP-Bang questionnaires. A logistic regression model was applied to determine the accuracy of independent factors in predicting sleep impairment. A multivariate logistic regression analysis was conducted to examine the impact of multiple sclerosis (MS) types on sleep disorder severity predictability by independent variables. Result: A total of 796 pwMS were included in the current study, 693 with relapsing-remitting MS and 103 with secondary-progressive MS. Rest leg syndrome (RLS) and insomnia disorders were not present in 48.1% and 50.5% of the pwMS, respectively. According to STOP-Bang and Berlin, 87.3% and 88.4% of patients had a low-severity risk for obstructive sleep apnea (OSA), respectively. The logistic regression showed that age, gender, and Expanded Disability Status Scale (EDSS) were associated with the risk of OSA (p < 0.05). RLS severity was also correlated with age and EDSS (p < 0.05). The association between sleep disorder severity and independent variables was not affected by MS type in multivariate logistic regression. Conclusion: In this study, we found that sleep disorders such as RLS, insomnia, and OSA are common among pwMS in Iran. Sociodemographic factors, as well as disease characteristics, can have an impact on sleep disorders among pwMS.