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Record W2224542136

Actigraphy assessments of circadian sleep-wake cycles in the Vegetative and Minimally Conscious States

2013· article· en· W2224542136 on OpenAlexaff
Damian Cruse, Aurore Thibaut, Athéna Demertzi, Julia C. Nantes, Marie‐Aurélie Bruno, Olivia Gosseries, Audrey Vanhaudenhuyse, Tristán Bekinschtein, Adrian M. Owen, Steven Laureys

Bibliographic record

VenueApollo (University of Cambridge) · 2013
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsWestern University
Fundersnot available
KeywordsActigraphyCircadian rhythmMedicineDark therapyPhysical medicine and rehabilitationPsychologyChronobiologyAudiologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: The Vegetative and Minimally Conscious States (VS; MCS) are characterized by absent or highly disordered signs of awareness alongside preserved sleep-wake cycles. According to international diagnostic guidelines, sleep-wake cycles are assessed by means of observations of variable periods of eye-opening and eye-closure. However, there is little empirical evidence for true circadian sleep-wake cycling in these patients, and there have been no large-scale investigations of the validity of this diagnostic criterion. METHODS: We measured the circadian sleep-wake rhythms of 55 VS and MCS patients by means of wrist actigraphy, an indirect method that is highly correlated with polysomnographic estimates of sleeping/waking. RESULTS: Contrary to the diagnostic guidelines, a significant proportion of patients did not exhibit statistically reliable sleep-wake cycles. The circadian rhythms of VS patients were significantly more impaired than those of MCS patients, as were the circadian rhythms of patients with non-traumatic injuries relative to those with traumatic injuries. The reliability of the circadian rhythms were significantly predicted by the patients' levels of visual and motor functioning, consistent with the putative biological generators of these rhythms. CONCLUSIONS: The high variability across diagnoses and etiologies highlights the need for improved guidelines for the assessment of sleep-wake cycles in VS and MCS, and advocates the use of actigraphy as an inexpensive and non-invasive alternative.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score0.445

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.231
Teacher spread0.216 · 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 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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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