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Record W2609793586 · doi:10.1093/sleepj/zsx050.648

0649 STRUCTURAL BRAIN ABNORMALITIES IN IDIOPATHIC HYPERSOMNIA

2017· article· en· W2609793586 on OpenAlexaffabout
Florence B. Pomares, Soufiane Boucetta, Jacques Montplaisir, F. Lachapelle, Jungho Cha, H Kim, Thien Thanh Dang‐Vu

Bibliographic record

VenueSLEEP · 2017
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalUniversité de MontréalHôpital du Sacré-Cœur de MontréalConcordia University
Fundersnot available
KeywordsEpworth Sleepiness ScalePrecuneusPsychologyNarcolepsyExcessive daytime sleepinessDefault mode networkAnterior cingulate cortexPremotor cortexAudiologyInternal medicineMedicinePolysomnographyNeuroscienceSleep disorderFunctional magnetic resonance imagingNeurologyElectroencephalographyAnatomyCognition

Abstract

fetched live from OpenAlex

Idiopathic hypersomnia (IH) is characterized by excessive daytime sleepiness but, in contrast with narcolepsy, does not involve cataplexy, rapid REM sleep onset (at the multiple sleep latency test, MSLT), or any consistent hypocretin-1 deficiency. The pathophysiological mechanisms of IH remain unclear, and no neuroimaging study has been conducted in IH. We hypothesize that IH is characterized by cortical alterations within networks involved in alertness. We conducted magnetic resonance imaging (MRI) on a 3T scanner in 12 participants with IH (mean age 33, range 22–59 years, 6 males, 10 females) and 16 good sleepers (mean age 31, range 22–53 years, 3 males, 9 females). High-resolution T1-weighted anatomical images were used to perform voxel-based morphometry (VBM) to measure regional volume and cortical thickness analyses. Daytime mean sleep latency from MSLT and Epworth sleepiness score were collected to measure respectively objective and self-reported scores of daytime sleepiness. Student t-tests were used to compare groups, and regression analyses were conducted on sleepiness scores, controlling for total intracranial volume (only for VBM), age and sex (threshold T>2.5, equivalent to p<0.01). Participants with IH had thicker and larger cortical structures, mainly within the default-mode network, compared to good sleepers: the anterior cingulate cortex, precuneus extending to posterior cingulate cortex, lateral parietal cortex bilaterally, and right premotor cortex were larger in IH. These larger volumes and thickness in IH were correlated with increased levels of subjective daytime sleepiness. The present results show that IH is associated with structural brain alterations, mainly located within the default-mode network and changing in proportion of clinical severity. Larger volume and thickness in these structures might reflect compensatory changes to chronic daytime sleepiness. Supported by the Sleep Research Society Foundation, the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Fonds de Recherche du Québec - Santé (FRQ-S), and the Canada Foundation for Innovation (CFI).

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 score0.005
Threshold uncertainty score0.018

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)0.0050.000

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 head0.056
GPT teacher head0.333
Teacher spread0.277 · 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
Published2017
Admission routes2
Has abstractyes

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