MétaCan
Menu
Back to cohort
Record W4386843554 · doi:10.1111/jsr.14033

Abnormal prefrontal functional network in adult obstructive sleep apnea: A resting‐state <scp>fNIRS</scp> study

2023· article· en· W4386843554 on OpenAlexaboutno aff
Wenhong Chen, Mo Xiaoying, Jianrong Yang, Howe Liu, Shi Lingli, Ma Hongwu

Bibliographic record

VenueJournal of Sleep Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPrefrontal cortexObstructive sleep apneaResting state fMRIFunctional near-infrared spectroscopyFunctional connectivityAbnormalityMontreal Cognitive AssessmentCognitionPolysomnographyCognitive impairmentDefault mode networkAudiologyCardiologyInternal medicineMedicinePsychologyNeuroscienceApneaPsychiatry

Abstract

fetched live from OpenAlex

To assess prefrontal brain network abnormality in adults with obstructive sleep apnea (OSA), resting-state functional near infrared spectroscopy (rs-fNIRS) was used to evaluate 52 subjects, including 27 with OSA and 25 healthy controls (HC). The study found that patients with OSA had a decreased connection edge number, particularly in the connection between the right medial frontal cortex (MFG-R) and other right-hemisphere regions. Graph-based analysis also revealed that patients with OSA had a lower global efficiency, local efficiency, and clustering coefficient than the HC group. Additionally, the study found a significant positive correlation between the Montreal Cognitive Assessment (MoCA) score and both the connection edge number and the graph-based indicators in patients with OSA. These preliminary results suggest that prefrontal rs-fNIRS could be a useful tool for objectively and quantitatively assessing cognitive function impairment in patients with OSA.

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)0.004
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.046
GPT teacher head0.372
Teacher spread0.326 · 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

Citations14
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sleep ResearchSame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207