1
|
Wu S, Wang S, Wu M, Lin F, Ji X, Yan J. Duration of N1 sleep is a factor for excessive daytime sleepiness in epilepsy patients with interictal epileptiform discharges: A polysomnographic study. Heliyon 2024; 10:e36500. [PMID: 39247309 PMCID: PMC11379998 DOI: 10.1016/j.heliyon.2024.e36500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 06/24/2024] [Accepted: 08/16/2024] [Indexed: 09/10/2024] Open
Abstract
Purpose This study aimed to identify the occurrence of excessive daytime sleepiness (EDS) in epilepsy patients with interictal epileptiform discharges and to explore the impact of interictal sleep architecture and sleep-related events on EDS. Methods This study included 101 epilepsy patients with interictal epileptiform discharges (IED) and 100 control patients who underwent simultaneous polysomnography and video ambulatory electroencephalography for >7 h throughout a single night. Multiple sleep latency tests were used to assess EDS. Comorbid EDS was present in 25 and 11 patients in the IED epilepsy and control groups, respectively. In addition, univariate and multivariate logistic regression analyses were performed to explore the factors influencing EDS. Results The epilepsy group had a higher prevalence of comorbid EDS and shorter R sleep duration. Univariate logistic regression analysis indicated that an increased risk of EDS may be associated with prolonged N1 sleep duration, higher arousal index, lower mean saturation (mSaO2), higher oxygen desaturation index (ODI), and duration of wake after sleep onset (WASO). Multivariate logistic regression analysis revealed that N1 sleep duration was significantly correlated with EDS. Conclusion In epilepsy patients with IED, the arousal index, mSaO2, ODI, and duration of WASO were weakly correlated with EDS, and the duration of N1 sleep demonstrated a significant positive correlation with EDS, which requires further research.
Collapse
Affiliation(s)
- Sangru Wu
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| | - Sihang Wang
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| | - Meina Wu
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| | - Fang Lin
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| | - Xiaolin Ji
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| | - Jinzhu Yan
- Department of Neurology, Fujian Provincial Governmental Hospital, Fuzhou, Fujian, China
| |
Collapse
|
2
|
Zeng S, Feng F, Li W, Xu Y, Zhao R, Liang S, Cheng Y, Fang R, Jia H, Wang Y, Lv D, Zhang B. Exploring sleep characteristics in Chinese patients with narcolepsy: insights from the nocturnal sleep onset rapid eye movement period (nSOREMP). J Clin Sleep Med 2024; 20:1349-1355. [PMID: 38648114 PMCID: PMC11294126 DOI: 10.5664/jcsm.11168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 04/02/2024] [Accepted: 04/03/2024] [Indexed: 04/25/2024]
Abstract
STUDY OBJECTIVES This study aimed to investigate the unique characteristics and clinical significance of the nocturnal sleep onset rapid eye movement period (nSOREMP) in the Chinese population with narcolepsy, enhancing our understanding and management of the disorder globally. METHODS This retrospective analysis investigated narcolepsy in Chinese patients from six hospitals, using the International Classification of Sleep Disorders. A parallel retrospective analysis of the Chinese Clinical Sleep Database focused on polysomnography records was conducted to evaluate nSOREMP prevalence in other sleep disorders. RESULTS The study found a 2.51% nSOREMP prevalence in other sleep disorders in the Chinese Clinical Sleep Database. Significant differences in age, N2 and rapid eye movement percentages, rapid eye movement latency, and various indexes were noted among patients with narcolepsy with or without nSOREMP and other sleep disorders with nSOREMP in the Chinese Clinical Sleep Database. nSOREMP prevalence in narcolepsy type 1 was 33.33% and in narcolepsy type 2 was 28.30%. Noteworthy disparities in narcolepsy type 1 included N2 percentages, rapid eye movement latency, and SOREMPs on Multiple Sleep Latency Test. In narcolepsy type 2, differences were significant for age, sleep latency, N2 and rapid eye movement latencies, arousal index, mean sleep latency on the Multiple Sleep Latency Test, and Multiple Sleep Latency Test SOREMPs. CONCLUSIONS This study highlights the distinct characteristics of nSOREMP in the Chinese population. Patients exhibiting symptoms suggestive of the onset of narcolepsy are advised to undergo a Multiple Sleep Latency Test, irrespective of the occurrence of SOREMP during nocturnal polysomnography. CITATION Zeng S, Feng F, Li W, et al. Exploring sleep characteristics in Chinese patients with narcolepsy: insights from the nocturnal sleep onset rapid eye movement period (nSOREMP). J Clin Sleep Med. 2024;20(8):1349-1355.
Collapse
Affiliation(s)
- Shufei Zeng
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Fei Feng
- Shenzhen Kangning Hospital, Shenzhen, Guangdong, China
| | - Weimin Li
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Yan Xu
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Rui Zhao
- Inner Mongolia Mental Health Center (The Third Hospital of Inner Mongolia Autonomous Region, Brain Hospital of Inner Mongolia Autonomous Region), Hohhot, Inner Mongolia autonomous Region, China
| | - Shengpeng Liang
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Yihong Cheng
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Ruichen Fang
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| | - Hailing Jia
- Mental Health Center of Hebei Province, Baoding, Hebei, China
| | - Yang Wang
- The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen, Guangdong, China
| | - Dongsheng Lv
- Inner Mongolia Mental Health Center (The Third Hospital of Inner Mongolia Autonomous Region, Brain Hospital of Inner Mongolia Autonomous Region), Hohhot, Inner Mongolia autonomous Region, China
| | - Bin Zhang
- Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangzhou, Guangdong, China
| |
Collapse
|
3
|
Hamdan S, Wasling P, Lind A. High-resolution HLA sequencing and hypocretin receptor 2 autoantibodies in narcolepsy type 1 and type 2. Int J Immunogenet 2024. [PMID: 38898624 DOI: 10.1111/iji.12688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/30/2024] [Accepted: 06/03/2024] [Indexed: 06/21/2024]
Abstract
Narcolepsy is a sleep disorder caused by an apparent degeneration of orexin/hypocretin neurons in the lateral hypothalamic area and a subsequent decrease in orexin/hypocretin levels in the cerebrospinal fluid. Narcolepsy is classified into type 1 (NT1) and type 2 (NT2). While genetic associations in the human leukocyte antigen (HLA) region and candidate autoantibodies have been investigated in NT1 to imply an autoimmune origin, less is known about the pathogenesis in NT2. Twenty-six NT1 and 15 NT2 patients were included, together with control groups of 24 idiopathic hypersomnia (IH) patients and 778 general population participants. High-resolution sequencing was used to determine the alleles, the extended haplotypes, and the genotypes of HLA-DRB3, -DRB4, -DRB5, -DRB1, -DQA1, -DQB1, -DPA1, and -DPB1. Radiobinding assay was used to determine autoantibodies against hypocretin receptor 2 (anti-HCRTR2 autoantibodies). NT1 was associated with HLA-DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01, -DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01 (odds ratio [OR]: 9.15; p = 8.31 × 10-4) and HLA-DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01, -DRB4*01:03:01, -DRB1*04:01:01, -DQA1*03:02//03:03:01, -DQB1*03:01:01 (OR: 23.61; p = 1.58 × 10-4) genotypes. Lower orexin/hypocretin levels were reported in the NT2 subgroup (n = 5) that was associated with the extended HLA-DQB1*06:02:01 haplotype (p = .001). Anti-HCRTR2 autoantibody levels were not different between study groups (p = .8524). We confirmed the previous association of NT1 with HLA-DQB1*06:02:01 extended genotypes. A subgroup of NT2 patients with intermediate orexin/hypocretin levels and association with HLA-DQB1*06:02:01 was identified, indicating a possible overlap between the two distinct narcolepsy subtypes, NT1 and NT2. Low anti-HCRTR2 autoantibody levels suggest that these receptors might not function as autoimmune targets in either NT1 or NT2.
Collapse
Affiliation(s)
- Samia Hamdan
- Department of Clinical Sciences, Malmö, Lund University, Malmo, Sweden
| | - Pontus Wasling
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neurology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Alexander Lind
- Department of Clinical Sciences, Malmö, Lund University, Malmo, Sweden
| |
Collapse
|
4
|
Trotti LM, Nichols KJ. Narcolepsy type 2: phenotype is fundamental. Sleep 2024; 47:zsae047. [PMID: 38452192 PMCID: PMC11082467 DOI: 10.1093/sleep/zsae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Indexed: 03/09/2024] Open
Affiliation(s)
- Lynn Marie Trotti
- Department of Neurology and Emory Sleep Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Kendall J Nichols
- Department of Neurology and Emory Sleep Center, Emory University School of Medicine, Atlanta, GA, USA
| |
Collapse
|
5
|
Zhao W, Zhang B, Yan Z, Zhao M, Zhang X, Zhang X, Liu X, Tang J. Correlation analysis between HLA-DQA1*0102/DQB1*0602 genotypes and narcolepsy patients in China. Front Neurol 2024; 15:1379723. [PMID: 38725645 PMCID: PMC11079304 DOI: 10.3389/fneur.2024.1379723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 04/03/2024] [Indexed: 05/12/2024] Open
Abstract
Background and objective At present, the etiology of narcolepsy is not fully understood, and it is generally believed to be an autoimmune reaction caused by interactions between environmental and genetic factors. Human leukocyte antigen (HLA) class II genes are strongly associated with this gene, especially HLA-DQB1*0602/DQA1*0102. In this study, we mainly analyzed the correlation between different genotypes of HLA-DQB1*0602/DQA1*0102 and clinical manifestations in Chinese patients with narcolepsy. Experimental method Narcolepsy patients who were treated at the Department of Neurology, The First Affiliated Hospital of Shandong First Medical University from January 2021 to September 2023 were selected. General information, sleep monitoring data, cerebrospinal fluid (CSF) orexin levels, and human leukocyte antigen gene typing data were collected. The statistical analysis was performed using SPSS 26.0, and the graphs were drawn using GraphPad Prism 9.5. Main results A total of 78 patients were included in this study. The DQA1 and DQB1 gene loci were detected in 54 patients, and only the DQB1 gene locus was detected in 24 narcoleptic patients. The most common allele at the HLA-DQB1 locus was *0602 (89.7%), and the most common genotype at this locus was *0602*0301 (19.2%), followed by *0602*0602 (17.9%). The most common phenotype of the HLA-DQA1 locus is *0102 (92.6%), and the most common genotype of this locus is *0102*0102 (27.8%), followed by *0102*0505 (14.8%). There were significant differences (p < 0.05) between HLA-DQB1*0602-positive and HLA-DQB1*0602-negative patients in terms of orexin-A levels, presence or absence of cataplexy, UNS, PSG sleep latency, REM sleep latency, N1 sleep percentage, oxygen depletion index, and average REM latency on the MSLT. The HLA-DQA1*0102-positive and HLA-DQA1*0102-negative patients showed significant differences (p < 0.05) in disease course, presence or absence of sudden onset, PSG REM sleep latency, N1 sleep percentage, and average REM latency on the MSLT. There were significant differences in the average REM latency of the MSLT between HLA-DQB1*0602/DQA1*0102 homozygous and heterozygous patients p < 0.05, and no differences were found in the baseline data, orexin-A levels, scale scores, or other sleep parameters. Conclusion Different genotypes of HLA-DQA1*0102/DQB1*0602 are associated with symptoms of cataplexy in Chinese narcoleptic patients. Homozygous individuals have a shorter mean REM latency in the MSLT, greater genetic susceptibility, and relatively more severe sleepiness.
Collapse
Affiliation(s)
- Wanyu Zhao
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Baokun Zhang
- Department of Neurology, Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Zian Yan
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Mengke Zhao
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Xiao Zhang
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Xiaoyu Zhang
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Xiaomin Liu
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
| | - Jiyou Tang
- Department of Neurology, The First Affiliated Hospital of Shandong First Medical University, Jinan, Shandong, China
- Department of Neurology, Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| |
Collapse
|
6
|
Cajochen C, Reichert CF, Münch M, Gabel V, Stefani O, Chellappa SL, Schmidt C. Ultradian sleep cycles: Frequency, duration, and associations with individual and environmental factors-A retrospective study. Sleep Health 2024; 10:S52-S62. [PMID: 37914631 DOI: 10.1016/j.sleh.2023.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 09/04/2023] [Accepted: 09/06/2023] [Indexed: 11/03/2023]
Abstract
OBJECTIVE Sleep varies between individuals in response to sleep-wake history and various environmental factors, including light and noise. Here we report on the intranight variation of the ultradian nonrapid eye movement-rapid eye movement (NREM-REM) sleep cycle in 369 participants who have contributed to different laboratory studies from 1994 to 2020 at the Centre for Chronobiology, Basel, Switzerland. RESULTS We observed a large interindividual variability in sleep cycle duration, including NREM and REM sleep episodes in healthy participants who were given an 8-hour sleep opportunity at habitual bedtime in controlled laboratory settings. The median sleep cycle duration was 96 minutes out of 6064 polysomnographically-recorded cycles. The number and duration of cycles were not normally distributed, and the distribution became narrower for NREM sleep and wider for REM sleep later in the night. The first cycle was consistently shorter than subsequent cycles, and moderate presleep light or nocturnal noise exposure had no significant effects on ultradian sleep cycle duration. Age and sex significantly affected NREM and REM sleep duration, with older individuals having longer NREM and shorter REM sleep particularly in the end of the night, and females having longer NREM sleep episodes. High sleep pressure (ie, sleep deprivation) and low sleep pressure (ie, multiple naps) altered ultradian sleep cycles, with high sleep pressure leading to longer NREM sleep in the first cycle, and low sleep pressure leading to longer REM sleep episodes. Positive correlations were observed between N2 and NREM duration, and between N1 and REM duration. Weak intrasleep REM sleep homeostasis was also evident in our data set. CONCLUSIONS We conclude that ultradian sleep cycles are endogenous biological rhythms modulated by age, sex, and sleep homeostasis, but not directly responsive to (moderate levels of) environmental cues in healthy good sleepers.
Collapse
Affiliation(s)
- Christian Cajochen
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences (MCN), University of Basel, Basel, Switzerland.
| | - Carolin Franziska Reichert
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences (MCN), University of Basel, Basel, Switzerland
| | - Mirjam Münch
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences (MCN), University of Basel, Basel, Switzerland
| | | | - Oliver Stefani
- Centre for Chronobiology, Psychiatric Hospital of the University of Basel, Basel, Switzerland; Research Cluster Molecular and Cognitive Neurosciences (MCN), University of Basel, Basel, Switzerland
| | - Sarah Laxhmi Chellappa
- School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, United Kingdom
| | - Christina Schmidt
- Sleep & Chronobiology Group, GIGA-CRC-In Vivo Imaging Research Unit, University of Liège, Liège, Belgium; Psychology and Neuroscience of Cognition Research Unit (PsyNCog), Faculty of Psychology, Speech and Language, University of Liège, Liège, Belgium
| |
Collapse
|
7
|
Aellen FM, Van der Meer J, Dietmann A, Schmidt M, Bassetti CLA, Tzovara A. Disentangling the complex landscape of sleep-wake disorders with data-driven phenotyping: A study of the Bernese center. Eur J Neurol 2024; 31:e16026. [PMID: 37531449 PMCID: PMC11235675 DOI: 10.1111/ene.16026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 07/05/2023] [Accepted: 07/31/2023] [Indexed: 08/04/2023]
Abstract
BACKGROUND AND PURPOSE The diagnosis of sleep-wake disorders (SWDs) is challenging because of the existence of only few accurate biomarkers and the frequent coexistence of multiple SWDs and/or other comorbidities. The aim of this study was to assess in a large cohort of well-characterized SWD patients the potential of a data-driven approach for the identification of SWDs. METHODS We included 6958 patients from the Bernese Sleep Registry and 300 variables/biomarkers including questionnaires, results of polysomnography/vigilance tests, and final clinical diagnoses. A pipeline, based on machine learning, was created to extract and cluster the clinical data. Our analysis was performed on three cohorts: patients with central disorders of hypersomnolence (CDHs), a full cohort of patients with SWDs, and a clean cohort without coexisting SWDs. RESULTS A first analysis focused on the cohort of patients with CDHs and revealed four patient clusters: two clusters for narcolepsy type 1 (NT1) but not for narcolepsy type 2 or idiopathic hypersomnia. In the full cohort of SWDs, nine clusters were found: four contained patients with obstructive and central sleep apnea syndrome, one with NT1, and four with intermixed SWDs. In the cohort of patients without coexisting SWDs, an additional cluster of patients with chronic insomnia disorder was identified. CONCLUSIONS This study confirms the existence of clear clusters of NT1 in CDHs, but mainly intermixed groups in the full spectrum of SWDs, with the exception of sleep apnea syndromes and NT1. New biomarkers are needed for better phenotyping and diagnosis of SWDs.
Collapse
Affiliation(s)
- Florence M. Aellen
- Institute of Computer ScienceUniversity of BernBernSwitzerland
- Center for Experimental Neurology, Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
| | - Julia Van der Meer
- Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
| | - Anelia Dietmann
- Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
| | - Markus Schmidt
- Center for Experimental Neurology, Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
| | - Claudio L. A. Bassetti
- Center for Experimental Neurology, Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
| | - Athina Tzovara
- Institute of Computer ScienceUniversity of BernBernSwitzerland
- Center for Experimental Neurology, Department of NeurologyInselspital, Bern University Hospital and University of BernBernSwitzerland
- Sleep Wake Epilepsy Center–NeuroTec, Department of NeurologyInselspital, Bern University Hospital, University of BernBernSwitzerland
| |
Collapse
|
8
|
Wang J, Zhao S, Zhou Y, Jiang H, Yu Z, Li T, Li S, Pan G. Narcolepsy Diagnosis With Sleep Stage Features Using PSG Recordings. IEEE Trans Neural Syst Rehabil Eng 2023; 31:3619-3629. [PMID: 37672382 DOI: 10.1109/tnsre.2023.3312396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
Narcolepsy is a sleep disorder affecting millions of people worldwide and causes serious public health problems. It is hard for doctors to correctly and objectively diagnose narcolepsy. Polysomnography (PSG) recordings, a gold standard for sleep monitoring and quality measurement, can provide abundant and objective cues for the narcolepsy diagnosis. There have been some studies on automatic narcolepsy diagnosis using PSG recordings. However, the sleep stage information, an important cue for narcolepsy diagnosis, has not been fully utilized. For example, some studies have not considered the sleep stage information to diagnose narcolepsy. Although some studies consider the sleep stage information, the stages are manually scored by experts, which is time-consuming and subjective. And the framework using sleep stages scored automatically for narcolepsy diagnosis is designed in a two-phase learning manner, where sleep staging in the first phase and diagnosis in the second phase, causing cumulative error and degrading the performance. To address these challenges, we propose a novel end-to-end framework for automatic narcolepsy diagnosis using PSG recordings. In particular, adopting the idea of multi-task learning, we take the sleep staging as our auxiliary task, and then combine the sleep stage related features with narcolepsy related features for our primary task of narcolepsy diagnosis. We collected a dataset of PSG recordings from 77 participants and evaluated our framework on it. Both of the sleep stage features and the end-to-end fashion contribute to diagnosis performance. Moreover, we do a comprehensive analysis on the relationship between sleep stages and narcolepsy, correlation of different channels, predictive ability of different sensing data, and diagnosis results in subject level.
Collapse
|
9
|
Dworetz A, Trotti LM, Sharma S. Novel Objective Measures of Hypersomnolence. CURRENT SLEEP MEDICINE REPORTS 2023; 9:45-55. [PMID: 37193087 PMCID: PMC10168608 DOI: 10.1007/s40675-022-00245-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/15/2022] [Indexed: 01/11/2023]
Abstract
Purpose of review To provide a brief overview of current objective measures of hypersomnolence, discuss proposed measure modifications, and review emerging measures. Recent findings There is potential to optimize current tools using novel metrics. High-density and quantitative EEG-based measures may provide discriminative informative. Cognitive testing may quantify cognitive dysfunction common to hypersomnia disorders, particularly in attention, and objectively measure pathologic sleep inertia. Structural and functional neuroimaging studies in narcolepsy type 1 have shown considerable variability but so far implicate both hypothalamic and extra-hypothalamic regions; fewer studies of other CDH have been performed. There is recent renewed interest in pupillometry as a measure of alertness in the evaluation of hypersomnolence. Summary No single test captures the full spectrum of disorders and use of multiple measures will likely improve diagnostic precision. Research is needed to identify novel measures and disease-specific biomarkers, and to define combinations of measures optimal for CDH diagnosis.
Collapse
Affiliation(s)
- Alex Dworetz
- Sleep Disorders Center, Atlanta Veterans Affairs Medical Center, Atlanta, GA
| | - Lynn Marie Trotti
- Sleep Center, Emory Healthcare, Atlanta, GA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA
| | - Surina Sharma
- Sleep Center, Emory Healthcare, Atlanta, GA
- Deparment of Medicine, Emory University School of Medicine, Atlanta, GA
| |
Collapse
|
10
|
Klaus S, Carolan A, O'Rourke D, Kennedy B. What respiratory physicians should know about narcolepsy and other hypersomnias. Breathe (Sheff) 2022; 18:220157. [PMID: 36865656 PMCID: PMC9973529 DOI: 10.1183/20734735.0157-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
Narcolepsy and related central disorders of hypersomnolence may present to the sleep clinic with excessive daytime sleepiness. A strong clinical suspicion and awareness of the diagnostic clues, such as cataplexy, are essential to avoid unnecessary diagnostic delay. This review provides an overview of the epidemiology, pathophysiology, clinical features, diagnostic criteria and management of narcolepsy and related disorders, including idiopathic hypersomnia, Kleine-Levin syndrome (recurrent episodic hypersomnia) and secondary central disorders of hypersomnolence.
Collapse
Affiliation(s)
- Stephen Klaus
- Department of Sleep Medicine, St James's Hospital, Dublin, Ireland
| | - Aoife Carolan
- Department of Sleep Medicine, St James's Hospital, Dublin, Ireland
| | - Deirdre O'Rourke
- Department of Sleep Medicine, St James's Hospital, Dublin, Ireland
| | - Barry Kennedy
- Department of Sleep Medicine, St James's Hospital, Dublin, Ireland,Corresponding author: Barry Kennedy ()
| |
Collapse
|