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Record W4386595145 · doi:10.1055/s-0043-1772805

The Importance of Sleep for Successful Neurorehabilitation after Stroke

2023· article· en· W4386595145 on OpenAlexaff
Cristina Frange, Brian J. Murray, Fernando Morgadinho Santos Coelho

Bibliographic record

VenueSleep Science · 2023
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsNeurorehabilitationSleep (system call)Stroke (engine)Context (archaeology)Physical medicine and rehabilitationRehabilitationNeuroplasticityPsychologyPhysical therapySleep hygieneMedicineCognitionSleep qualityPsychiatryComputer science

Abstract

fetched live from OpenAlex

Sleep has important clinical implications for neurorehabilitation after stroke. We aimed to systematically explore sleep (including naps) as an essential factor in the neurorehabilitation of patients after stroke. After titles and abstracts were screened, 49 full texts were reviewed, and 7 were included in this review. Data were extracted and assessed for quality and risk of bias. We looked at any neurorehabilitation setting, and compared sleep with no sleep and explored these factors in stroke patients versus healthy individuals. Rehabilitation is critical for many activities that may need to be learned or re-learned following stroke and for returning to everyday life. In this context, sleep is essential in neurorehabilitation and physical therapy practice as it supports neuroplasticity, memory, and learning. The available data suggest that sleep should be considered in the treatment plan for successfully targeted physiotherapy to optimize cognitive and motor learning. Physical therapists should advise about sleep hygiene and therapies to improve sleep, both quality and quantity.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.660

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.032
GPT teacher head0.332
Teacher spread0.299 · 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 designBench or experimental
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".

Quick stats

Citations10
Published2023
Admission routes1
Has abstractyes

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