Fabio Pizza1,2, Stefano Vandi1,2, Martina Iloti1, Christian Franceschini3, Rocco Liguori1,2, Emmanuel Mignot4, Giuseppe Plazzi1,2. 1. Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy. 2. IRCCS, Istituto delle Scienze Neurologiche, ASL di Bologna, Bologna, Italy. 3. Department of Clinical and Experimental Medicine, University of Parma, Parma, Italy. 4. Centre for Narcolepsy, Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA.
Abstract
STUDY OBJECTIVES: To evaluate the reliability of nocturnal sleep dynamics in the differential diagnosis of central disorders of hypersomnolence. DESIGN: Cross-sectional. SETTING: Sleep laboratory. PATIENTS: One hundred seventy-five patients with hypocretin-deficient narcolepsy type 1 (NT1, n = 79), narcolepsy type 2 (NT2, n = 22), idiopathic hypersomnia (IH, n = 22), and "subjective" hypersomnolence (sHS, n = 52). INTERVENTIONS: None. METHODS: Polysomnographic (PSG) work-up included 48 h of continuous PSG recording. From nocturnal PSG conventional sleep macrostructure, occurrence of sleep onset rapid eye movement period (SOREMP), sleep stages distribution, and sleep stage transitions were calculated. Patient groups were compared, and receiver operating characteristic (ROC) curve analysis was used to test the diagnostic utility of nocturnal PSG data to identify NT1. RESULTS: Sleep macrostructure was substantially stable in the 2 nights of each diagnostic group. NT1 and NT2 patients had lower latency to rapid eye movement (REM) sleep, and NT1 patients showed the highest number of awakenings, sleep stage transitions, and more time spent in N1 sleep, as well as most SOREMPs at daytime PSG and at multiple sleep latency test (MSLT) than all other groups. ROC curve analysis showed that nocturnal SOREMP (area under the curve of 0.724 ± 0.041, P < 0.0001), percent of total sleep time spent in N1 (0.896 ± 0.023, P < 0.0001), and the wakefulness-sleep transition index (0.796 ± 0.034, P < 0.0001) had a good sensitivity and specificity profile to identify NT1 sleep, especially when used in combination (0.903 ± 0.023, P < 0.0001), similarly to SOREMP number at continuous daytime PSG (0.899 ± 0.026, P < 0.0001) and at MSLT (0.956 ± 0.015, P < 0.0001). CONCLUSIONS: Sleep macrostructure (i.e. SOREMP, N1 timing) including stage transitions reliably identifies hypocretin-deficient narcolepsy type 1 among central disorders of hypersomnolence.
STUDY OBJECTIVES: To evaluate the reliability of nocturnal sleep dynamics in the differential diagnosis of central disorders of hypersomnolence. DESIGN: Cross-sectional. SETTING: Sleep laboratory. PATIENTS: One hundred seventy-five patients with hypocretin-deficient narcolepsy type 1 (NT1, n = 79), narcolepsy type 2 (NT2, n = 22), idiopathic hypersomnia (IH, n = 22), and "subjective" hypersomnolence (sHS, n = 52). INTERVENTIONS: None. METHODS: Polysomnographic (PSG) work-up included 48 h of continuous PSG recording. From nocturnal PSG conventional sleep macrostructure, occurrence of sleep onset rapid eye movement period (SOREMP), sleep stages distribution, and sleep stage transitions were calculated. Patient groups were compared, and receiver operating characteristic (ROC) curve analysis was used to test the diagnostic utility of nocturnal PSG data to identify NT1. RESULTS: Sleep macrostructure was substantially stable in the 2 nights of each diagnostic group. NT1 and NT2 patients had lower latency to rapid eye movement (REM) sleep, and NT1 patients showed the highest number of awakenings, sleep stage transitions, and more time spent in N1 sleep, as well as most SOREMPs at daytime PSG and at multiple sleep latency test (MSLT) than all other groups. ROC curve analysis showed that nocturnal SOREMP (area under the curve of 0.724 ± 0.041, P < 0.0001), percent of total sleep time spent in N1 (0.896 ± 0.023, P < 0.0001), and the wakefulness-sleep transition index (0.796 ± 0.034, P < 0.0001) had a good sensitivity and specificity profile to identify NT1 sleep, especially when used in combination (0.903 ± 0.023, P < 0.0001), similarly to SOREMP number at continuous daytime PSG (0.899 ± 0.026, P < 0.0001) and at MSLT (0.956 ± 0.015, P < 0.0001). CONCLUSIONS: Sleep macrostructure (i.e. SOREMP, N1 timing) including stage transitions reliably identifies hypocretin-deficient narcolepsy type 1 among central disorders of hypersomnolence.
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