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Clinical Neurophysiology: Polysomnography

2005· article· en· W4254025068 on OpenAlexaboutno aff

Bibliographic record

VenueEpilepsia · 2005
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsPolysomnographyIctalEpilepsyMedicinePediatricsSleep (system call)NeurologySleep disorderAffect (linguistics)Excessive daytime sleepinessPsychologyPsychiatryPhysical therapyElectroencephalographyCognition

Abstract

fetched live from OpenAlex

1 Shay Menascu, 1 Shelly Weiss, and 1 Ihaon MacLusky ( 1 Neurology, Hospital for Sick Children, Toronto, ON, Canada ) Rationale: Children with epilepsy are reported to have frequent sleep disturbances including sleep fragmentation, and excessive daytime drowsiness. Epilepsy is known to affect a child's cognitive, social, and appears to have important secondary effects on sleep. Seizure disorders can affect both the quality and architecture of sleep and interictal discharges may also cause sleep disruption and affect normal progression through sleep stages.Most of these previous studies reportsed only small series of children undergoing overnight polysomnography(PSG). The objective of this study was to objectively measure sleep architecture and sleep disturbance in a large number of children with epilepsy Methods: A retrospective chart review was carried out of consecutive children with epilepsy who were referred to our center's sleep laboratory for a PSG study between 1998–2004. The data abstracted included epilepsy syndrome and results of the PSG. PSG results were compared to age-matched normative data. The children were referred by their neurologist to evaluate different sleep complaints of the child or the parent/caregiver. Children who had evidence of sleep disordered breathing on the polysomnography were excluded to focus on the changes in sleep caused by the child's seizures, interictal discharges or antiepileptic medications. Children were also excluded if there had been a change in antiepileptic medication within one month prior to the sleep study due to the possible sedating effect of the medication change. Results: 54 children were identified. The children were divided into two groups, primary generalized and partial epilepsy. There were 21of children with primary generalized and 33 with partial epilepsy. The ages was 1–17 years. Significant differences were found for sleep efficiency (time asleep/time in bed) and amount of rapid eye movement (REM) sleep. There were no significant difference in NREM sleep. The average sleep efficiency for all children irrespective of epilepsy type was low compared to normative data (p = 0.0005) Comparing the two groups, the average sleep efficiency was lower in the children with generalized epilepsy. The average percentage of time spent in REM sleep was decreased for children in both groups. Conclusions: The results in this study which used overnight polysomnography as an objective measure of sleep demonstrates changes in sleep architecture in children with primary generalized and partial epilepsy. These changes were independent of sleep related breathing disorder (which will cause additional problems if present) as these children were excluded from the analysis. As children were on a variety of AED combinations, the influence of individual medications could not be evaluated. These results demonstrate the importance of evaluating sleep in children with epilepsy as it is established that poor sleep will exacerbate seizures. Further research regarding the evaluation of sleep disorders, disrupted sleep architecture and the treatment of these problems is warranted.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.002

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 head0.037
GPT teacher head0.372
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2005
Admission routes1
Has abstractyes

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