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A clinical research of rapid eye movement sleep without atonia in patients with narcolepsy

2016· article· en· W3029545144 on OpenAlexaboutno aff
Pei-Cheng He, Kangping Xiong, Junying Huang, Yun Shen, Jie Li, Chengjie Mao, Jinru Zhang, Yi Wang, Fei Han

Bibliographic record

VenueChin J Neurol · 2016
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsnot available
Fundersnot available
KeywordsNarcolepsyPolysomnographyMultiple Sleep Latency TestEpworth Sleepiness ScaleChinArousalPsychologyRapid eye movement sleepSleep StagesAnesthesiaElectromyographyNeurologyEye movementMedicineAudiologyOphthalmologySleep disorderApneaExcessive daytime sleepinessInsomniaPsychiatryNeuroscience

Abstract

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Objective To quantitatively research the chin electromyography (EMG) increasing level of narcolepsy in rapid eye movement(REM) period, and analyze its association with clinical features and rapid eye movement sleep without atonia (RSWA). Methods Sixty-six patients with narcolepsy underwent video-polysomnography (video-PSG) and multiple sleep latency test (MSLT), and were grouped by quantitative research of the chin EMG levels during overnight REM (patients with elevated level belongs to RSWA group(n=31)). The data from general clinical data, video-PSG and MSLT and neuro-psychological assessment (Epworth Sleepiness Scale (ESS) and Montreal Cognitive Assessment) were analyzed statistically. Results Compared with narcolepsy without RSWA group (n=35), narcolepsy with RSWA group showed higher ESS score (17.9±4.1 vs 15.4±4.9, t=2.236, P=0.029), longer average time (min) per drowsiness (38.3±28.4 vs 19.2±11.2, t=2.931, P=0.030), higher incidence of cataplexy (58.1%(18/31) vs 28.6%(10/35); χ2=6.281, P=0.012). In the polysomnography parameters, narcolepsy with RSWA group had shorter sleep latency (2.00(0.50, 3.50) min vs 3.00(1.75, 9.50) min; Z=3.007, P=0.003), higher total arousal index (31.4±14.4 vs 22.9±13.1; t=2.368, P=0.021), and micro arousal index ((13.0±7.19)/h vs (9.2±6.5)/h; t=2.080, P=0.042) and spontaneous arousal index((11.9±7.1)/h vs(8.1±5.4)/h; t=2.500, P=0.015). There was no significant difference in sleep structure between the narcolepsy with RSWA group and narcolepsy without RSWA group. In MSLT parameters, shorter average REM sleep latency (min) appeared in narcolepsy with RSWA group(3.5±1.7 vs 5.3±4.5, t=-2.190, P=0.027). Logistic regression analysis showed that the phase of the chin EMG (OR=1.103, 95% CI 1.008-1.207, P=0.033) and tension chin EMG (OR=1.339, 95% CI 1.111-1.615, P=0.002)were significantly associated with cataplexy. Conclusions Narcolepsy with RSWA group showed sleep fragmentation, severer daytime sleepiness, and higher risk of cataplexy. Therefore, narcolepsy patients with high chin EMG had a higher prevalence of cataplexy. Key words: Narcolepsy; Electrophysiology; Polysomnography; Rapid eye movement sleep without atonia

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.082
GPT teacher head0.393
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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