Multiple sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system which is associated with the development of diffuse demyelination and axonal lesions. MS is the primary global cause of non-traumatic handicap in young adults and widespread dissemination of lesions lead to great heterogeneity in the clinical picture (Tullman, 2013).

Sleep related breathing disorders, especially obstructive sleep apnea (OSA), are highly frequent in patients with MS compared to the general population (Foschi et al., 2019; Hensen et al., 2017; Abdel Salam et al., 2019; Shaygannejad et al., 2020) but yet often remains underdiagnosed (Braley et al., 2014; Brass et al., 2014). OSA is commonly associated with snoring, daytime sleepiness, fatigue, cognitive dysfunction and mood changes in the non-disabled (Jordan et al., 2014). In addition, it is associated with an increase in cardiovascular morbidity and mortality (Young et al., 2008; Mazzotti et al., 2019; Trzepizur et al., 2022; Blanchard et al., 2021). In patients with multiple sclerosis specific association have been found between OSA and fatigue (Braley et al., 2014; Kaminska et al., 2012), cognitive dysfunction (Braley et al., 2016), and quality of life (Veauthier et al., 2015). Despite continuous progress in OSA diagnosis and management, these underlying sleep disorders continue escape routine clinical evaluations in patients with MS (Braley and Chervin, 2015).

Few studies have looked at specific predictive factors of OSA in MS. Studies have to date been limited by various methodologies, small sample size and have led to conflicting results (Abdel Salam et al., 2019; Shaygannejad et al., 2020; Kaminska et al., 2011). Several authors have proposed using screening tools which have been validated in the general population (STOP-BANG, Berlin) in OSA screening of patients with MS (Dias et al., 2012; Sunter et al., 2021; Singh et al., 2022). However, this strategy has obvious limitations in this population: questions focus on fatigue which is the most common symptom of MS and is estimated to affect 90 % of patients (Goodin, 1999). Moreover, these tools are often subjective which imposes obvious limit in a population often affected by cognitive dysfunction especially in the case of advanced disease.

To the best of our knowledge, these screening tools have not been tested in patients with severe MS and an elevated EDSS (≥ 4). The aim of this study is to identify specific predictive factors for OSA in a population of patients with advanced MS and EDSS score ≥ 4. This strategy will then be developed adding data from simple objective tools such as oximetry.