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Record W2094863929 · doi:10.2147/copd.2006.1.1.65

Is there a role for mask continuous positive airway pressure in acute respiratory failure due to COPD? Lessons from a retrospective audit of 3 different cohorts

2006· article· en· W2094863929 on OpenAlexaff
Sandra Dial, Dick Menzies

Bibliographic record

VenueInternational Journal of COPD · 2006
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineContinuous positive airway pressureCOPDIntubationRetrospective cohort studyMechanical ventilationOdds ratioRespiratory failureIntensive care unitConfoundingConfidence intervalAnesthesiaIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Exacerbations of COPD that result in acute respiratory failure requiring intubation and mechanical ventilation have high morbidity and mortality. This study is a retrospective observational study that compared the outcomes of 237 patients with COPD and acute respiratory failure requiring intensive care unit (ICU) admission according to modality of initial therapy: mask continuous positive airway pressure (CPAP), medical therapy, or intubation. Of the patients treated with CPAP initially, only 16% failed and required intubation compared with 62% of those treated medically (p = 0.001). The median length of ICU stay was 5 days in those treated with CPAP, compared with 7 days for those medically treated, and 8.5 days for intubated patients (p = 0.001). When compared with mask CPAP, and after adjusting for potentially confounding differences, mortality was significantly higher if patients were initially intubated (adjusted odds ratios [OR] 15.7; 95% confidence interval [CI] 4.2, 59) or given medical therapy (OR 5.1; CI 1.2, 20.8). In COPD patients with acute respiratory failure, initial treatment with mask CPAP was associated with significantly better outcomes than other treatment modalities, even after adjusting for potentially confounding differences in disease severity.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.633

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.282
Teacher spread0.273 · 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
Published2006
Admission routes1
Has abstractyes

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