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Record W3199302302 · doi:10.21307/aoj-2021.025

The risk for paediatric obstructive sleep apnoea in rural Queensland

2021· article· en· W3199302302 on OpenAlexaff
Marguerite A. Fischer, Ersan İlsay Karadeniz, Carlos Flores‐Mir, Daniel Lindsay, Carmen Karadeniz

Bibliographic record

VenueAustralasian Orthodontic Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of Alberta
FundersFar North Queensland Hospital Foundation
KeywordsMedicineOverweightDemographicsPediatricsObesityObstructive sleep apneaPhysical therapyDemographyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The importance of assessing patients for paediatric obstructive sleep apnoea (OSA) cannot be more highly stressed and orthodontists may play an essential role in risk screening. The Paediatric Sleep Questionnaire (PSQ) is a validated tool to identify whether a child is at risk for paediatric OSA. Objectives The likelihood of paediatric OSA in school-aged children residing in Far North Queensland (FNQ) will be assessed using the PSQ. Methods Parents of children aged between 4 and 18 years were invited to participate through schools and social media messaging to complete an online PSQ questionnaire to assess their OSA risk and demographics. Results The final sample consisted of 404 school-aged children of whom 62.5% were found to be at a high-risk for paediatric OSA. The high risk was significantly associated with males and those of overweight/obese BMI status ( p < 0.001). Race and age were not significant associations ( p > 0.05). Conclusions Within the contributing sample of school-aged children in FNQ, a significant number were found to be at high-risk of paediatric OSA. Males and overweight/obese children were measured risk factors.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.116
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.018
GPT teacher head0.301
Teacher spread0.284 · 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
Published2021
Admission routes1
Has abstractyes

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