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Record W3159971272 · doi:10.1093/sleep/zsab072.562

564 Patient Charactarestics With Normal to Mild Apnea Hypopnea Index Undergoing Polysomnography to Diagnose Obstructive Sleep Apnea

2021· article· en· W3159971272 on OpenAlexaffabout
Majid AlTeneiji, Leah Schmalz, Adetayo Adeleye

Bibliographic record

VenueSLEEP · 2021
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsAlberta Children's Hospital
Fundersnot available
KeywordsMedicinePolysomnographyObstructive sleep apneaApnea–hypopnea indexReferralTriageMedical diagnosisAsthmaPediatricsSleep apneaPhysical therapyEmergency medicineApneaInternal medicine

Abstract

fetched live from OpenAlex

Abstract Introduction Polysomnography (PSG) testing is expensive and not easily accessible. Waiting time for a routine PSG at the Alberta Children’s Hospital (ACH) can be up to a year. Majority of PSG studies performed are for diagnosis of obstructive sleep apnea (OSA). A previous quality improvement (QI) project conducted at the ACH showed that two-thirds of children who had undergone initial PSG testing had an apnea hypopnea index (AHI) in the normal or mild range. Given our limited resources, better characterization of patient referral characteristics and process factors as documented on the PSG requisition will inform our triage process, decrease wait time, improve resource allocation and information provided to referral sources. Methods Retrospective review of PSG’s performed for the initial diagnosis of OSA was completed between January 2018 and March 2020 at the ACH. Patient referral characteristics (age, sex, growth parameters, medical diagnosis, indication for PSG, previous airway surgery), process factors (source of referral, PSG referral and completion date, triage status) and AHI were recorded. Patients were divided into two groups (group A: normal and mild; group B: moderate and severe) based on AHI. Data obtained from the groupings were compared and analyzed descriptively. PSG triage to completion time was also calculated for each group. Results A total of 798 initial PSG studies were completed between January 2018 and March 2020. Of the PSG’s reviewed 64.8% were in group A and 35.2% were in group B. Common medical diagnoses in group A included ADHD, Asthma and Autism, whereas group B had T21 and Enuresis. History of previous airway surgery did not differ between groups. Conclusion Further clarification of the patient’s underlying medical diagnosis (referral characteristic) may help inform our triage process. The implication of previous airway surgery (process factor) on AHI severity is unclear at this point. More data is actively being collected to further interrogate these preliminary findings. Support (if any):

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.263
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), 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 routes2
Has abstractyes

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