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Record W4214892740 · doi:10.1097/wnp.0000000000000821

Stroke: What's Sleep Got to Do With It?

2022· article· en· W4214892740 on OpenAlexaff

Bibliographic record

VenueJournal of Clinical Neurophysiology · 2022
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThrombolysisStroke (engine)Sleep apneaEveningPulse oximetryObstructive sleep apneaRisk factorMorning

Abstract

fetched live from OpenAlex

SUMMARY: Ischemic strokes most often occur between 6 am and 12 am after awakening from sleep but up to 30% occur during sleep. Wake-up strokes (WUS) are new focal neurological deficit(s) persisting for ≥ 24 hours attributable to an ischemic event present on patient awakening. Obstructive sleep apnea (OSA) is a major risk factor for WUS because it compounds the instability of the morning environment and increases the likelihood of cardiovascular events, including hypertension, atrial fibrillation, right-to-left shunts, and stroke. Circadian-driven alterations in structural, homeostatic, and serological factors also predispose to WUS. Also, WUS patients are often not considered candidates for time-dependent intravenous thrombolysis therapy because of an uncertain onset time. However, using the tissue clock (positive diffusion weighted imaging-negative fluid-attenuated inversion recovery mismatch) dates the WUS as 3 to 4.5 hours old and permits consideration for intravenous thrombolysis and if needed mechanical thrombectomy. Given the high prevalence of moderate/severe OSA in stroke patients and its impact on stroke outcomes, screening with overnight pulse oximetry and home sleep apnea test is needed. Treating OSA poststroke remains challenging. Polysomnographic changes in sleep architecture following acute/subacute stroke may also impact upon stroke outcome.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.406
Teacher spread0.352 · 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.

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

Citations3
Published2022
Admission routes1
Has abstractyes

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