Slow-Wave Sleep Fragmentation in Disorders of Arousal and Sleep-Related Hypermotor Epilepsy

BACKGROUND AND OBJECTIVES: Disorders of arousal (DOAs) and sleep-related hypermotor epilepsy (SHE) share overlapping clinical features, making differential diagnosis challenging. Although video polysomnography remains the gold standard, EEG patterns to distinguish these conditions are not yet well defined. Slow-wave sleep (SWS) fragmentation is a key marker of DOA, but its characteristics in SHE remain unexplored. The aim of this study was to assess SWS fragmentation in DOAs and SHE, its potential diagnostic value, and overnight dynamics. METHODS: Eighty-seven patients with DOAs (n = 47; mean age 23.90 ± 13.10 years; 44.7% children) or SHE (n = 40; mean age 25.11 ± 13.08 years; 27.5% children) underwent overnight polysomnography with blinded scoring. SWS fragmentation was quantified, distinguishing fast, mixed, and slow arousals, and its overnight evolution was evaluated. Groups were compared and diagnostic SWS fragmentation cutoff values were defined using receiver-operating characteristic curves. RESULTS: = 0.006). Regarding overnight dynamics, linear mixed models revealed significant group × period interactions for SWS fragmentation index and slow/mixed arousal index, indicating distinct overnight patterns, with DOAs showing a marked reduction at the end of the night. In adults, the highest area under the curve (AUC) values were obtained for SWS Fragmentation and slow/mixed arousal indices with satisfactory classification performances (AUC 0.81 and 0.84, respectively). The SWS Fragmentation Index cutoff value of 6.64/h and slow/mixed arousal index cutoff of 2.40/h reached a sensitivity of 80.8% and specificity of 86.2%. In children, SWS Fragmentation Index ≥5.06/h achieved 76.2% sensitivity and 90.9% specificity (AUC 0.84) while slow/mixed arousal index showed excellent discriminative performance (AUC 0.96) with a cutoff of 2.10/h reaching 95.2% sensitivity and 90.9% specificity. DISCUSSION: SWS fragmentation, especially mixed and slow arousals, represents a supportive neurophysiologic marker that may assist the differential diagnostic process between DOAs and SHE. Quantitative SWS microstructure parameters may improve diagnosis and provide insight into pathophysiologic mechanisms.