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STUDY OBJECTIVES: The objective of this study was to evaluate interrater reliability between manual sleep stage scoring performed in 2 European sleep centers and automatic sleep stage scoring performed by the previously validated artificial intelligence–based Stanford-STAGES algorithm. METHODS: Full night polysomnographies of 1,066 participants were included. Sleep stages were manually scored in Berlin and Innsbruck sleep centers and automatically scored with the Stanford-STAGES algorithm. For each participant, we compared (1) Innsbruck to Berlin scorings (INN vs BER); (2) Innsbruck to automatic scorings (INN vs AUTO); (3) Berlin to automatic scorings (BER vs AUTO); (4) epochs where scorers from Innsbruck and Berlin had consensus to automatic scoring (CONS vs AUTO); and (5) both Innsbruck and Berlin manual scorings (MAN) to the automatic ones (MAN vs AUTO). Interrater reliability was evaluated with several measures, including overall and sleep stage-specific Cohen’s κ. RESULTS: Overall agreement across participants was substantial for INN vs BER (κ = 0.66 ± 0.13), INN vs AUTO (κ = 0.68 ± 0.14), CONS vs AUTO (κ = 0.73 ± 0.14), and MAN vs AUTO (κ = 0.61 ± 0.14), and moderate for BER vs AUTO (κ = 0.55 ± 0.15). Human scorers had the highest disagreement for N1 sleep (κ(N1) = 0.40 ± 0.16 for INN vs BER). Automatic scoring had lowest agreement with manual scorings for N1 and N3 sleep (κ(N1) = 0.25 ± 0.14 and κ(N3) = 0.42 ± 0.32 for MAN vs AUTO). CONCLUSIONS: Interrater reliability for sleep stage scoring between human scorers was in line with previous findings, and the algorithm achieved an overall substantial agreement with manual scoring. In this cohort, the Stanford-STAGES algorithm showed similar performances to the ones achieved in the original study, suggesting that it is generalizable to new cohorts. Before its integration in clinical practice, future independent studies should further evaluate it in other cohorts. CITATION: Cesari M, Stefani A, Penzel T, et al. Interrater sleep stage scoring reliability between manual scoring from two European sleep centers and automatic scoring performed by the artificial intelligence–based Stanford-STAGES algorithm. J Clin Sleep Med. 2021;17(6):1237–1247.

Study objectives Rapid eye movement sleep behavior disorder (RBD) is frequent in dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), and poses a risk of injury to patients and their bed partners. We assessed the efficacy of nelotanserin, a selective 5-HT (2A) inverse agonist, for symptomatic treatment of RBD using systematic video analysis. Methods This was a phase 2 multicenter study in DLB or PDD with video polysomnography (vPSG)-confirmed RBD. After a single-blind placebo run-in period, patients meeting eligibility criteria entered a 4-week double-blind treatment period (1:1 ratio with nelotanserin 80 mg/placebo). Whole-night vPSG was conducted during the run-in and at the end of the treatment period. Videos of all rapid eye movement (REM) sleep periods were analysed for RBD behaviors (movements and vocalizations) using the Innsbruck classification system by two of the central reviewers, and a third reviewer adjudicated ambiguous cases. Results 34 patients (N = 26 DLB, N = 8 PDD; 85.3% men; mean age 71.3 ± 6.36 years) were included in the analyses. Two (5.9%) patients were excluded due to protocol deviation in treatment compliance. Systematic video analysis demonstrated no difference between nelotanserin and placebo in RBD behaviors. Bland–Altman plot showed high interrater reliability. Conclusions Despite negative results, this is the first randomized, placebo-controlled study on symptomatic RBD treatment using objective outcome measures based on systematic video analysis. This study provides a new method for outcome research in RBD and proves that movement analysis is a feasible and meaningful outcome for studies evaluating changes in RBD severity. Clinical trial information ClinicalTrials.gov. NCT Number NCT02708186. https://clinicaltrials.gov/ct2/show/NCT02708186 .

Study Objectives The differentiation of isolated rapid eye movement (REM) sleep behavior disorder (iRBD) or its prodromal phase (prodromal RBD) from other disorders with motor activity during sleep is critical for identifying α-synucleinopathy in an early stage. Currently, definite RBD diagnosis requires video polysomnography (vPSG). The aim of this study was to evaluate automated 3D video analysis of leg movements during REM sleep as objective diagnostic tool for iRBD. Methods A total of 122 participants (40 iRBD, 18 prodromal RBD, 64 participants with other disorders with motor activity during sleep) were recruited among patients undergoing vPSG at the Sleep Disorders Unit, Department of Neurology, Medical University of Innsbruck. 3D videos synchronous to vPSG were recorded. Lower limb movements rate, duration, extent, and intensity were computed using a newly developed software. Results The analyzed 3D movement features were significantly increased in subjects with iRBD compared to prodromal RBD and other disorders with motor activity during sleep. Minor leg jerks with a duration < 2 seconds discriminated with the highest accuracy (90.4%) iRBD from other motor activity during sleep. Automatic 3D analysis did not differentiate between prodromal RBD and other disorders with motor activity during sleep. Conclusions Automated 3D video analysis of leg movements during REM sleep is a promising diagnostic tool for identifying subjects with iRBD in a sleep laboratory population and is able to distinguish iRBD from subjects with other motor activities during sleep. For future application as a screening, further studies should investigate usefulness of this tool when no information about sleep stages from vPSG is available and in the home environment.

Study objectives Periodic limb movements in sleep (PLMS) are frequent motor phenomena; however, population-based data are scarce. We assessed the prevalence of PLMS and factors associated with PLMS within two German population-based cohorts, the SHIP-TREND and BiDirect. Methods Single-night polysomnography was performed on 1107 subjects recruited from the general population (mean age: 52.9 years, 54.1% men) in the SHIP-TREND and on 247 participants (mean age: 57.6 years, 50.6% men) in the BiDirect. PLMS were evaluated using the standard criteria of the American Academy of Sleep Medicine. Sociodemographic data, behavioral variables, medical history, current medication, and other sleep disorders were assessed. Results The prevalence of PLMS index (PLMSI) >15/hour was 32.4% (SHIP-TREND) and 36.4% (BiDirect). In multivariable models, age (odds ratio [OR] = 1.05 per +1 year), male gender (OR = 2.20), restless legs syndrome (OR = 2.32), physical inactivity (OR = 1.52), current smoking (OR = 1.49), diabetes (OR = 2.13), antidepressant use (OR = 2.27), lower serum magnesium (OR per -0.1 mmol/L = 1.27) showed a positive, and the intake of beta-blockers an inverse association with PLMSI >15/hour in SHIP-TREND. In BiDirect, age (OR = 1.13 per +1 year), body mass index (OR = 1.11 per +1 kg/m2), and restless legs syndrome (OR = 8.77) were significantly associated with PLMSI >15/hour. Conclusions A high PLMSI is frequent in the German population. Age, male gender, restless legs syndrome, physical inactivity, current smoking, obesity, diabetes, antidepressant use, and lower magnesium were independently associated with PLMSI >15/hour in at least one of the cohorts.

Study objectives and design Rapid eye movement sleep without atonia (RWA) is the polysomnographic hallmark of REM sleep behavior disorder (RBD). To partially overcome the disadvantages of manual RWA scoring, which is time consuming but essential for the accurate diagnosis of RBD, we aimed to validate software specifically developed and integrated with polysomnography for RWA detection against the gold standard of manual RWA quantification. Setting Academic referral center sleep laboratory. Participants Polysomnographic recordings of 20 patients with RBD and 60 healthy volunteers were analyzed. Interventions N/A. Measurements and results Motor activity during REM sleep was quantified manually and computer assisted (with and without artifact detection) according to Sleep Innsbruck Barcelona (SINBAR) criteria for the mentalis ("any," phasic, tonic electromyographic [EMG] activity) and the flexor digitorum superficialis (FDS) muscle (phasic EMG activity). Computer-derived indices (with and without artifact correction) for "any," phasic, tonic mentalis EMG activity, phasic FDS EMG activity, and the SINBAR index ("any" mentalis + phasic FDS) correlated well with the manually derived indices (all Spearman rhos 0.66-0.98). In contrast with computerized scoring alone, computerized scoring plus manual artifact correction (median duration 5.4 min) led to a significant reduction of false positives for "any" mentalis (40%), phasic mentalis (40.6%), and the SINBAR index (41.2%). Quantification of tonic mentalis and phasic FDS EMG activity was not influenced by artifact correction. Conclusion The computer algorithm used here appears to be a promising tool for REM sleep behavior disorder detection in both research and clinical routine. A short check for plausibility of automatic detection should be a basic prerequisite for this and all other available computer algorithms.

• First PSG study evaluating the acute effect of exposure to high altitude on PLM in RLS and normals.

Study objectives Despite differences between American Academy of Sleep Medicine (AASM) and Rechtschaffen and Kales scoring criteria, normative values following the current AASM criteria are lacking. We investigated sleep and respiratory variables in healthy adults over the lifespan, and established polysomnographic normative values according to current standards. Design Prospective polysomnographic investigation. Setting Academic referral hospital sleep laboratory. Participants One hundred healthy sleepers aged 19-77 y were selected from a representative population sample by a two-step screening. Interventions N/A. Measurements and results All subjects underwent one full-night polysomnography. Sleep and arousals were scored according to AASM standards. Respiration was scored according to AASM 2007 and 2012 criteria in order to compare both methods. Percentile curves showed age-related differences in sleep architecture: a decrease was found for sleep efficiency [≤ 30 y: 87.0 (71.9-94.1)% versus > 60 y: 79.7 (44.5-90.9)%], total sleep time [≤ 30 y: 413.5 (345.6-451.9) min versus > 60 y: 378.3 (216.0-440.0) min], the percentages of N3 [≤ 30 y 20.7 (15.2-37.5)% versus > 60 y: 14.9 (2.4-35.6)%] and rapid eye movement sleep [≤ 30 y 15.5 (7.5-23.6)% versus. > 60 y: 10.3 (1.9-21.9)%], whereas the percentage of wake time after sleep onset increased with age [≤ 30 y 6.0 (1.9-22.8)% versus > 60 y: 15.2 (6.3-48.7)%]. The apnea-hypopnea index (AHI) was higher when applying the AASM 2012 criteria [AHI AASM 2007 0.7 (0.0-21.5)/h versus 2012: 1.7 (0.0-25)/h; P 15/h. Conclusions This study provides normative data on sleep macrostructure, microstructure, and respiration in adults following AASM standards. Furthermore, we demonstrated that respiration scoring according to AASM 2012 results in higher AHIs, and challenge the use of age-independent respiratory cutoff values.

This explorative study aims at characterizing the breath behavior of two prototypic volatile organic compounds, acetone and isoprene, during normal human sleep and to possibly relate changes in the respective concentration time courses to the underlying sleep architecture. For this purpose, six normal healthy volunteers (two females, four males, age 20-29 years) were monitored over two consecutive nights (the first one being an adaption night) by combining real-time proton-transfer-reaction mass spectrometry measurements from end-tidal exhalation segments with laboratory-based polysomnographic data. Breath acetone concentrations increased overnight in all measurements, with an average relative change by a factor of up to 4 (median 2.5). Nighttime concentration maxima were usually recorded 2-3 h before lights on. For breath isoprene, a nocturnal increase in baseline concentrations of about 74% was observed, with individual changes ranging from 36-110%. Isoprene profiles exhibited pronounced concentration peaks, which were highly specific for leg movements as scored by tibial electromyography. Furthermore, relative to a linear trend, baseline isoprene concentrations decreased during the transition from the NREM to the REM phase of a complete sleep cycle.

Background Periodic leg movements (PLM) during sleep (PLMS) are considered strongly related to restless legs syndrome (RLS), and are associated with polymorphisms in RLS risk genes. Various software for automatic analysis of PLMS are available, but only few of them have been validated. Aim of this study was to validate a leg movements count and analysis integrated in a commercially available polysomnography (PSG) system against manual scoring. Methods Twenty RLS patients with a PLMS index > 20/h and 20 controls with a PLMS index