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Record W2086413866 · doi:10.1186/1465-9921-9-56

Reliability of home CPAP titration with different automatic CPAP devices

2008· article· en· W2086413866 on OpenAlexafffund
Frédéric Sériès, Julie Plante, Yves Lacasse

Bibliographic record

VenueRespiratory Research · 2008
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersCanadian Institutes of Health ResearchResMed
KeywordsTitrationCrossover studyMedicineContinuous positive airway pressureReliability (semiconductor)WashoutObstructive sleep apneaAnesthesiaInternal medicineChemistryPlaceboPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: CPAP titration may be completed by automatic apparatus. However, differences in pressure behaviour could interfere with the reliability of pressure recommendations. Our objective was to compare pressure behaviour and effective pressure recommendations between three Automatic CPAP machines (Autoset Spirit, Remstar Auto, GK 420). METHODS: Sixteen untreated obstructive sleep apnea patients were randomly allocated to one of the 3 tested machines for a one-week home titration trial in a crossover design with a 10 days washout period between trials. RESULTS: The median pressure value was significantly lower with machine GK 420 (5.9 +/- 1.8 cm H2O) than with the other devices both after one night and one week of CPAP titration (7.4 +/- 1.3 and 6.6 +/- 1.9 cm H2O). The maximal pressure obtained over the one-week titration was significantly higher with Remstar Auto (12.6 +/- 2.4 cm H2O, Mean +/- SD) than with the two other ones (10.9 +/- 1.0 and 11.0 +/- 2.4 cm H2O). The variance in pressure recommendation significantly differed between the three machines after one night and between Autoset Spirit and the two other machines after 1 week. CONCLUSION: Pressure behaviour and pressure recommendation significantly differ between Auto CPAP machines both after one night and one week of home titration.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.041
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.378
Teacher spread0.280 · 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

Citations28
Published2008
Admission routes2
Has abstractyes

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