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Record W3121451230 · doi:10.46747/cfp.670121

Continuous positive airway pressure for obstructive sleep apnea in children

2021· article· en· W3121451230 on OpenAlexvenueno aff
Jessie J. Wang, Toshihiro Imamura, James Lee, Marie Wright, Ran D. Goldman

Bibliographic record

VenueCanadian Family Physician · 2021
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood Institute
KeywordsContinuous positive airway pressureObstructive sleep apneaMedicineTonsillectomyPediatricsSleep (system call)AdenoidectomyPositive pressureAirwayAnesthesia

Abstract

fetched live from OpenAlex

QUESTION: A 12-year-old child underwent adenotonsillectomy for treatment of obstructive sleep apnea (OSA) but continues to snore at night and struggles with attentiveness at school. The child's parent uses a continuous positive airway pressure (CPAP) machine at night and wonders whether the same therapy could be used in children. ANSWER: Unlike in adults, pediatric OSA is commonly related to adenotonsillar hypertrophy and is often amenable to treatment with adenotonsillectomy. As an alternative to surgery or in cases of postsurgical persistence of OSA, CPAP has shown effectiveness in improving both polysomnographic parameters and daytime neurobehavioural symptoms in children with OSA. Adherence to CPAP therapy is a challenge in children and requires parental education and special considerations such as a mask acclimatization period.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.811
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.247
Teacher spread0.238 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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