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Record W6962359392 · doi:10.17605/osf.io/3kv4c

The Interconnection of Rett Syndrome and Sleep Disturbances: a Scoping Review

2021· other· en· W6962359392 on OpenAlexaff

Bibliographic record

VenueOpen Science Framework · 2021
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRett syndromeSleep (system call)MECP2Sleep disorderNeurodevelopmental disorderNeurological disorderSleep apnea

Abstract

fetched live from OpenAlex

Sleep disturbances are included in supportive Rett syndrome diagnostic criteria as they are highly prevalent in patients with Rett syndrome, however, the link between Rett syndrome and sleep has not been well established (Shelton & Malow 2021). A large study that included 320 families with a child with Rett syndrome reported that 80% of patients experience sleep disturbances. The most common was night screaming and laughing, reported in 49% and 77% of patients, respectively (Wong et al 2015). Other disturbances include insomnia, arousal and movement disorders, gastrointestinal dysfunction, seizures, and sleep disordered breathing (Tarquinio et al 2018). Patients with Rett syndrome have been found to have decreased sleep efficacy and more frequent nighttime awakenings, altered REM and deep sleep, and abnormal gross and twitch movements due to hyper-arousability and hyper-motor restlessness (Ramirez et al 2020). The use of medication as a primary treatment was associated with only 1.7% reduction in reported sleep disturbances in patients with Rett syndrome (Wong et al 2015). The objectives of this scoping review are 1) to investigate the literature on sleep disturbances experienced by patients with Rett syndrome in order to better inform our understanding of how Rett syndrome affects sleep architecture, 2) identify the tools used to assess sleep as a primary or secondary outcome, and 3) determine the effects on sleep of interventions used to treat symptoms of Rett syndrome or sleep disturbances.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.358
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

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

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 head0.016
GPT teacher head0.316
Teacher spread0.301 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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