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Record W2937850300 · doi:10.1093/sleep/zsz067.326

0327 Relation between Speed of Wake-Sleep Transitions and Wake Time in Polysomnograms.

2019· article· en· W2937850300 on OpenAlexaff
Magdy Younes, Eleni Giannouli

Bibliographic record

VenueSLEEP · 2019
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWakefulnessPolysomnographyArousalSleep (system call)Sleep onsetApneaPsychologyObstructive sleep apneaAnesthesiaSleep apneaSleep StagesNon-rapid eye movement sleepInsomniaAudiologyMedicineCardiologyElectroencephalographyPsychiatryNeuroscience

Abstract

fetched live from OpenAlex

The immediate neurophysiological mechanism for excessive wake time (W) during polysomnography is unknown. Switching from wakefulness to stable sleep involves progression from full wakefulness to dozing, to light sleep to progressively deeper sleep. We hypothesized that the rate at which sleep depth increases may be an important determinant of W since the slower the rate, the longer the brain lingers in a highly arousable state, increasing the probability that the process is reversed soon after it starts. We determined rate of progression of sleep depth at wake-sleep transitions using the Odds-Ratio-Product (ORP), a validated continuous index of sleep depth ranging from 0 (deep sleep) to 2.5 (full wakefulness). Probability of spontaneous arousal occurring within 30 seconds increases directly with current ORP (r2=0.98). We analyzed 145 PSGs of patients referred for investigation of a sleep disorder, mostly sleep apnea. As controls, we analyzed PSGs of all Sleep-Heart-Health-Study (visit-2) subjects who had no sleep apnea (AHI<5 hr-1) or complaints of insomnia or restless legs (RLS), (n=46). Time course of ORP from onset of wake-sleep transition was determined for all transitions in each PSG and average time course was calculated. Speed of transitions was expressed by average ORP 2-minutes after onset of transitions (ORP2.0). Wake time was 116±80 and 56±44 minutes in patients and controls, respectively. ORP2.0 was 1.54±0.28 and 1.05±0.26, respectively, indicating slower wake-sleep transition in patients (p=E-20). There was a significant correlation in patients (n=145) between ORP2.0 and natural logarithm of wake time in minutes (ln(W) = 1.15*ORP2.0 + 2.74; r2=0.19, p=E-07) and this improved further, with little change in slope and intercept, when control subjects were added (n=191): (ln(W) = 1.32*ORP2.0 + 2.44; r2=0.29, p=E-15). Using multiple regression with ln(W) as the dependent variable and age, gender, BMI, AHI, RLS, and ORP2.0 as independent variables, the most significant variable was ORP2.0 (p=E-12) with age (p<0.01) and RLS (p<0.05) as distant second and third. Slow rate of sleep depth progression at wake-sleep transitions is an important risk factor for excessive wake time. None

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.274
Teacher spread0.248 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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