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Record W2159276720 · doi:10.1183/09031936.00128914

Inhaled corticosteroids in COPD: the clinical evidence

2014· review· en· W2159276720 on OpenAlexaff
Pierre Ernst, Nathalie Saad, Samy Suissa

Bibliographic record

VenueEuropean Respiratory Journal · 2014
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineCOPDIntensive care medicineInhaled corticosteroidsAsthmaClinical trialAdverse effectEosinophilicInternal medicinePathology

Abstract

fetched live from OpenAlex

In this article, we focus on the scientific evidence from randomised trials supporting treatment with inhaled corticosteroids (ICS) in chronic obstructive pulmonary disease (COPD), including treatment with combinations of long-acting β-agonist (LABA) bronchodilators and ICS. Our emphasis is on the methodological strengths and limitations that guide the conclusions that may be drawn. The evidence of benefit of ICS and, therefore, of the LABA/ICS combinations in COPD is limited by major methodological problems. From the data reviewed herein, we conclude that there is no survival benefit independent of the effect of long-acting bronchodilation and no effect on FEV1 decline, and that the possible benefit on reducing severe exacerbations is unclear. Our interpretation of the data is that there are substantial adverse effects from the use of ICS in patients with COPD, most notably severe pneumonia resulting in excess deaths. Currently, the most reliable predictor of response to ICS in COPD is the presence of eosinophilic inflammation in the sputum. There is an urgent need for better markers of benefit and risk that can be tested in randomised trials for use in routine specialist practice. Given the overall safety and effectiveness of long-acting bronchodilators in subjects without an asthma component to their COPD, we believe use of such agents without an associated ICS should be favoured.

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)0.011
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.970
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0010.002

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 head0.196
GPT teacher head0.448
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 teacher head, not a consensus.

Study designOther design
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

Citations161
Published2014
Admission routes1
Has abstractyes

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