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Record W2889947327 · doi:10.1111/jsr.12761

Effects of continuous positive airway pressure on neurocognitive and neuropsychiatric function in obstructive sleep apnea

2018· article· en· W2889947327 on OpenAlexaboutno aff
Veronika Dostálová, Sandra Kolečkárová, Martin Kuška, Martin Pretl, Ondřej Bezdíček

Bibliographic record

VenueJournal of Sleep Research · 2018
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
FundersUniverzita Karlova v Praze
KeywordsNeurocognitiveObstructive sleep apneaContinuous positive airway pressureAirwayMedicineSleep apneaApneaSleep (system call)CardiologyAnesthesiaPsychiatryCognitionComputer science

Abstract

fetched live from OpenAlex

The aim of this study was to determine the neurocognitive and neuropsychiatric effects of continuous positive airway pressure treatment on patients with obstructive sleep apnea. This cross-sectional, prospective, observational study included 126 patients with sleep apnea. The following tests were performed: the Montreal Cognitive Assessment for the evaluation of cognitive impairment, the Beck Depression Inventory, and the State-Trait Anxiety Inventory, together with the Epworth Sleepiness Scale for the evaluation of neuropsychiatric symptoms and a person's general level of daytime sleepiness. The first measurement did not show neurocognitive impairment or a higher level of depressive and anxiety symptoms in 126 patients with obstructive sleep apnea in comparison to normative standards. After the 3-month treatment indicated for 43 patients with obstructive sleep apnea, we did not find any significant improvement in cognitive performance (p = .213). However, patients with sleep apnea with continuous positive airway pressure treatment did show significantly less daytime sleepiness, anxiety and depressive symptoms (all p < .001). In conclusion, short-term (3 months) treatment of patients with obstructive sleep apnea can substantially alleviate their daytime sleepiness, as well as depressive and anxiety symptoms.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.314
Teacher spread0.300 · 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

Citations19
Published2018
Admission routes1
Has abstractyes

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