Contactless detection of periodic leg movements during sleep: A 3D video pilot study.

In clinical practice, the quality of polysomnographic recordings in children and patients with neurodegenerative diseases may be affected by sensor displacement and diminished total sleep time due to stress during the recording. In the present study, we investigated if contactless three-dimensional (3D) detection of periodic leg movements during sleep was comparable to polysomnography. We prospectively studied a sleep laboratory cohort from two Austrian sleep laboratories. Periodic leg movements during sleep were classified according to the standards of the World Association of Sleep Medicine and served as ground truth. Leg movements including respiratory-related events (A1) and excluding respiratory-related events (A2 and A3) were presented as A1, A2 and A3. Three-dimensional movement analysis was carried out using an algorithm developed by the Austrian Institute of Technology. Fifty-two patients (22 female, mean age 52.2 ± 15.1 years) were included. Periodic leg movement during sleep indexes were significantly higher with 3D detection compared to polysomnography (33.3 [8.1-97.2] vs. 30.7 [2.9-91.9]: +9.1%, p = .0055/27.8 [4.5-86.2] vs. 24.2 [0.00-88.7]: +8.2%, p = .0154/31.8 [8.1-89.5] vs. 29.6 [2.4-91.1]: +8.9%, p = .0129). Contactless automatic 3D analysis has the potential to detect restlessness mirrored by periodic leg movements during sleep reliably and may especially be suited for children and the elderly.

It twitches without kicking - An association between fragmentary myoclonus and arousal?

OBJECTIVE: Fragmentary myoclonus (FM) is a polysomnographic motor phenomenon of unknown clinical relevance. This study investigates FM prevalence, gender differences, sleep stage distribution and association with clinical factors using recently introduced advanced FM scoring criteria. METHODS: We analyzed polysomnographic recordings of 178 patients of a mixed sleep-disorder patient cohort. FM indices (FMI) of newly introduced 25 µV (FMI25) and standard 50 µV (FMI50) amplitude cut-offs were calculated. RESULTS: FMI25 and FMI50 were higher in men compared to women. FMI were higher during wakefulness and lower during S3 compared to all other sleep stages, with stronger effects in men compared to women. FMI25 was correlated with higher age, lower mean oxygen saturation, lower sleep efficiency, higher periodic limb movement (PLM) index, shorter sleep period time and higher arousal index. Linear regression showed that age predicted higher FMI25 in both males and females. Additionally, higher arousal index predicted higher FMI25 in women only. FMI were not associated with the presence of sleep-related breathing disorders. CONCLUSIONS: We suggest FM represents a ubiquitous motor phenomenon occurring spontaneously during relaxed wakefulness and sleep, primarily in men and with advanced age. SIGNIFICANCE: In women, particularly FMI25 may be a surrogate marker for more frequent arousals and sleep fragmentation.

Wanted: a better cut-off value for the Epworth Sleepiness Scale.

BACKGROUND: Excessive daytime sleepiness (EDS) is the main complaint in many neurological sleep disorders, such as idiopathic hypersomnia, narcolepsy, or obstructive sleep apnea/hypopnea syndrome (OSAS). The validity of the Epworth Sleepiness Scale (ESS) as a screening tool for EDS remains controversial. We therefore investigated (1) the interrelation of the ESS total score and the mean sleep latency (MSL) during the multiple sleep latency test (MSLT) and (2) the diagnostic accuracy of the ESS total score to detect EDS in patients with the chief complaint of subjective EDS. METHODS: A total of 94 patients (48 males) with subjective EDS were included in this study. Regression analyses and ROC curve analyses were carried out to assess the predictive value of the ESS score for MSL. RESULTS: The ESS score significantly predicted a shortened MSL (p = 0.01, ß = -0.29). After dichotomizing into two groups, the ESS score predicted MSL only in patients with hypersomnia or narcolepsy (p = 0.01, ß = -0.33), but not in patients with other clinical diagnoses (e. g. OSAS; p = 0.36, ß = -0.15). The ROC curve analyses indicated an optimal ESS cut-off value of 16 with a sensitivity of 70%; however, specificity remained unsatisfactory (55.6%). CONCLUSIONS: Our results suggest that the predictive value of the ESS score in patients with subjective EDS is low and patient subgroup-specific (superior in hypersomnia/narcolepsy vs. other diagnoses) and that the commonly used cut-off of 11 points may be insufficient for clinical practice.