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Record W2106333232 · doi:10.1080/15412550600651339

Safety of Sputum Induction in Moderate-to-Severe Smoking-Related Chronic Obstructive Pulmonary Disease

2006· article· en· W2106333232 on OpenAlexaff
Andrew M. Wilson, Richard Leigh, Frederick E. Hargreave, Márcia Margaret Menezes Pizzichini, Emílio Pizzichini

Bibliographic record

VenueCOPD Journal of Chronic Obstructive Pulmonary Disease · 2006
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversity of Calgary
Fundersnot available
KeywordsPulmonary diseaseMedicineSputumInternal medicineIntensive care medicineDiseasePathologyTuberculosis

Abstract

fetched live from OpenAlex

BACKGROUND: Investigation of the safety of sputum induction in patients with moderate-to-severe chronic obstructive pulmonary disease (COPD) has been limited. OBJECTIVE: to evaluate this issue in 100 patients with a mean FEV1 of 1.2 (0.4) L. After 200 microg inhaled salbutamol, sputum induction was performed with inhaled saline in increasing and tailored concentrations (0.9% to 5%) until an adequate sample of sputum was obtained or the FEV1 fell by >20%. MAIN FINDINGS: Sputum induction was successful in 92% of occasions. The mean (SD) fall in FEV1 was 13.5 (8.6)%. Five patients had a fall >20% but all recovered to 10% of baseline after inhaled salbutamol. The magnitude of fall in FEV1 correlated weakly with salbutamol reversibility (r = 0.37, p < 0.001), baseline FEV1/VC (r = -0.32, p = 0.001) and baseline FEV1% predicted (r = -0.36, p = 0.003) but not with age, smoking history or post-Salbutamol FEV1. Principle CONCLUSION: Sputum induction can be performed safely using a patient-tailored approach in patients with moderate-to-severe COPD, supporting its use in research and clinical practice.

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)0.003
metaresearch head score (Gemma)0.010
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 score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
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 integrity0.0010.000
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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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

Citations22
Published2006
Admission routes1
Has abstractyes

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