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Record W203326925 · doi:10.1155/2001/360169

Comparing Pressures Required to Abolish Snoring and Sleep Apnea

2001· article· en· W203326925 on OpenAlexaffabout
V. Hoffstein, Zoe Oliver

Bibliographic record

VenueCanadian Respiratory Journal · 2001
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSleep apneaApneaSleep apnea syndromesSleep (system call)AnesthesiaPolysomnography

Abstract

fetched live from OpenAlex

OBJECTIVE: Snoring and obstructive sleep apnea share similar pathogenesis and similar response to treatment with continuous positive airway pressure (CPAP). The purpose of this study was to compare pressures required to abolish apneas (POSA) with pressures required to abolish snoring (PSNOR). DESIGN: Cross-sectional, nonrandomized cohort study. SETTING: Sleep disorders clinic at St Michael's Hospital - a tertiary referral centre and a teaching hospital of the University of Toronto, Toronto, Ontario. POPULATION STUDIED: Unselected consecutive 441 patients with confirmed sleep apnea who were undergoing a CPAP titration study in the sleep laboratory. INTERVENTIONS: Nocturnal polysomnography using CPAP titration protocol, which required incremental increases in pressure until snoring and apnea were abolished or a maximum pressure of 16 cm H2O was attained. PSNOR and POSA were recorded and compared. RESULTS: Mean (+/- SD) pressures required to abolish snoring and apnea were: PSNOR 8.3+/-2.57 cm H2O and POSA 7.9+/-2.72 cm H2O (P<0.0001). In 75% of patients, the PSNOR was within +/-1 cm H2O of the POSA; in 92%, it was within +/-2 cm H2O; and in 97%, it was within +/-3 cm H2O. CONCLUSIONS: Empirically increasing pressure by 2 cm H2O in patients on CPAP who continue to snore may abolish snoring and apnea without the necessity of another titration study.

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)0.000
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 score0.290
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.051
GPT teacher head0.307
Teacher spread0.256 · 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

Citations8
Published2001
Admission routes2
Has abstractyes

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