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Record W2171489490 · doi:10.1001/jama.2013.276185

Does This Patient Have Obstructive Sleep Apnea?

2013· review· en· W2171489490 on OpenAlexaff
Kathryn Myers, Marko Mrkobrada, David L. Simel

Bibliographic record

VenueJAMA · 2013
Typereview
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineObstructive sleep apneaPolysomnographySleep apneaApneaApnea–hypopnea indexBody mass indexPediatricsPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

IMPORTANCE: Obstructive sleep apnea is a common disease, responsible for daytime sleepiness. Prior to referring patients for definitive testing, the likelihood of obstructive sleep apnea should be established in the clinical examination. OBJECTIVE: To systematically review the clinical examination accuracy in diagnosing obstructive sleep apnea. DATA SOURCES: MEDLINE and reference lists from articles were searched from 1966 to June 2013. Titles and abstracts (n = 4449) were reviewed for eligibility and appraised for evidence levels. STUDY SELECTION: For inclusion, studies must have used full, attended nocturnal polysomnography for the reference standard (n = 42). MAIN OUTCOMES AND MEASURES: Community and referral-based prevalence of obstructive sleep apnea; accuracy of symptoms and signs for the diagnosis of obstructive sleep apnea. RESULTS: The prevalence of sleep apnea in community-screened patients is 2% to 14% (sample sizes 360-1741) and 21% to 90% (sample sizes 42-2677) for patients referred for sleep evaluation. The prevalence varies based on the apnea-hypopnea index (AHI) threshold used for the evaluation (≥5 events/h, prevalence 14%; ≥15/h, prevalence 6%) and whether the disease definition requires symptoms in addition to an abnormal AHI (≥5/h with symptoms, prevalence 2%-4%). Among patients referred for sleep evaluation, those with sleep apnea weighed more (summary body mass index, 31.4; 95% CI, 30.5-32.2) than those without sleep apnea (summary BMI, 28.3; 95% CI, 27.6-29.0; P < .001 for the comparison). The most useful observation for identifying patients with obstructive sleep apnea was nocturnal choking or gasping (summary likelihood ratio [LR], 3.3; 95% CI, 2.1-4.6) when the diagnosis was established by AHI ≥10/h). Snoring is common in sleep apnea patients but is not useful for establishing the diagnosis (summary LR, 1.1; 95% CI, 1.0-1.1). Patients with mild snoring and body mass index lower than 26 are unlikely to have moderate or severe obstructive sleep apnea (LR, 0.07; 95% CI, 0.03-0.19 at threshold of AHI ≥15/h). CONCLUSIONS AND RELEVANCE: Nocturnal gasping or choking is the most reliable indicator of obstructive sleep apnea, whereas snoring is not very specific. The clinical examination of patients with suspected obstructive sleep apnea is useful for selecting patients for more definitive testing.

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)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.003

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 head0.034
GPT teacher head0.331
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations257
Published2013
Admission routes1
Has abstractyes

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