Electroclinical Features of Sleep-Related Head Jerk

Hu, Gengyao; Ni, Yuan; Pan, Yuanhang; Bi, Wang; Wang, Xiaoli; Wang, Zezhi; Chen, Ze; Liu, Yonghong

doi:10.2147/nss.s331893

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…In literature, SRHJs are associated with leg movements, respiratory effort, and micro-arousal. 1,3,4,7 This is the first case report of SRHJs associated with DEB during REM sleep.…”

Section: Discussionmentioning

confidence: 77%

Sleep-Related Head Jerk Presenting With Dream Enactment Behavior: A Case Report

Shin

2022

J Sleep Med

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Sleep-related head jerk (SRHJ) is conceived as a physiological motor phenomenon, which is mostly seen during rapid eye movement (REM) sleep. It should be distinguished from movements during REM sleep, mainly REM sleep behavior disorder (RBD). A 25-year-old male complained of daytime sleepiness with snoring and dream enactment behavior (DEB). Video polysomnography (PSG) excluded RBD and obstructive sleep apnea; frequent SRHJs during REM sleep with or without respiratory effort-related arousals, and SRHJs followed by one episode of DEB was observed. On PSG with continuous positive airway pressure titration, SRHJ with arousal events still remained but DEB symptom was resolved. REM without atonia unrelated to head jerks was not observed on all PSG data. Excessive SRHJs with arousal related to a sleep disturbance could indicate an SRHJ disorder, which might be a novel sleep-related movement disorder. In addition, clinicians should be careful in diagnosing young patients with RBD.

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“…In literature, SRHJs are associated with leg movements, respiratory effort, and micro-arousal. 1,3,4,7 This is the first case report of SRHJs associated with DEB during REM sleep.…”

Section: Discussionmentioning

confidence: 77%

Sleep-Related Head Jerk Presenting With Dream Enactment Behavior: A Case Report

Shin

2022

J Sleep Med

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“…The PSG equipment and assessment process were consistent with our previous study. 16 Briefly, all patients were admitted to the separate sleeping ward at 4pm and underwent nocturnal PSG at habitual bedtimes based on their regular sleep–wake cycle on a XLTEK Natus system (Bio-Logic, USA). Video-PSG included electroencephalograms (EEG), electrocardiogram (ECG), electromyography (EMG, surface EMG of chin and limbs), electro-oculogram (EOG).…”

Section: Methodsmentioning

confidence: 99%

Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness

Pan,

Zhao,

Zhang

et al. 2024

NSS

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Background Excessive daytime sleepiness (EDS) forms a prevalent symptom of obstructive sleep apnea (OSA) and narcolepsy type 1 (NT1), while the latter might always be overlooked. Machine learning (ML) models can enable the early detection of these conditions, which has never been applied for diagnosis of NT1. Objective The study aimed to develop ML prediction models to help non-sleep specialist clinicians identify high probability of comorbid NT1 in patients with OSA early. Methods Totally, clinical features of 246 patients with OSA in three sleep centers were collected and analyzed for the development of nine ML models. LASSO regression was used for feature selection. Various metrics such as the area under the receiver operating curve (AUC), calibration curve, and decision curve analysis (DCA) were employed to evaluate and compare the performance of these ML models. Model interpretability was demonstrated by Shapley Additive explanations (SHAP). Results Based on the analysis of AUC, DCA, and calibration curves, the Gradient Boosting Machine (GBM) model demonstrated superior performance compared to other machine learning (ML) models. The top five features used in the GBM model, ranked by feature importance, were age of onset, total limb movements index, sleep latency, non-REM (Rapid Eye Movement) sleep stage 2 and severity of OSA. Conclusion The study yielded a simple and feasible screening ML-based model for the early identification of NT1 in patients with OSA, which warrants further verification in more extensive clinical practices.

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Electroclinical Features of Sleep-Related Head Jerk

Cited by 2 publications

References 18 publications

Sleep-Related Head Jerk Presenting With Dream Enactment Behavior: A Case Report

Sleep-Related Head Jerk Presenting With Dream Enactment Behavior: A Case Report

Machine learning-Based model for prediction of Narcolepsy Type 1 in Patients with Obstructive Sleep Apnea with Excessive Daytime Sleepiness

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