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Record W2068723943 · doi:10.1177/0194599811415823a466

Turbinate Size and Sleep‐Related Breathing Disorders: Is There a Correlation?

2011· article· en· W2068723943 on OpenAlexaboutno aff
Véronique‐Isabelle Forest, Andrea Benedetti, François Lavigne

Bibliographic record

VenueOtolaryngology · 2011
Typearticle
Languageen
FieldMedicine
TopicNasal Surgery and Airway Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePolysomnographyNoseSleep (system call)BreathingEpworth Sleepiness ScaleRhinomanometryHypopneaApneaAnesthesiaSurgery

Abstract

fetched live from OpenAlex

Objective The tail of the turbinates is a site of nasal obstruction that may be associated with sleep related breathing disorder (SBD). We describe a technique, the trans‐oral nasopharyngoscopy (TON), to evaluate turbinate size and determine if an association exists between turbinate size and the various parameters measured in SBD. Method Thirty‐six patients with SBD completed an Epworth Sleepiness Scale (ESS) and a Quebec Sleep Questionnaire (QSQ). They underwent a nasal examination, allergy skin tests, full night polysomnography, and TON. Turbinate size was divided into two groups: I) turbinate obstructing 1/2. Results Sixteen patients were grade I and 20 patients were grade II. Turbinate size at the choana did not show any statistical significant association with nasal congestion, allergies, ESS and QSQ scores. Among the PSG parameters analyzed, no association was found with the apnea‐hypopnea index (AHI), but the size of the turbinate showed a positive correlation with respiratory event related arousals (RERA; P =. 03). Total sleep time spent snoring showed a weak association with turbinate size. Conclusion TON is a simple technique allowing the evaluation of the size of the turbinates. Turbinate size was associated with RERA and total sleep time spent snoring, but not with AHI.

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 score0.047
Threshold uncertainty score0.896

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.232
Teacher spread0.218 · 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
Published2011
Admission routes1
Has abstractyes

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