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Record W2526311816 · doi:10.1038/npjpcrm.2016.68

Appropriate use of inhaled corticosteroids in COPD: the candidates for safe withdrawal

2016· review· en· W2526311816 on OpenAlexaff
Barbara P. Yawn, Samy Suissa, Andrea P. Rossi

Bibliographic record

Venuenpj Primary Care Respiratory Medicine · 2016
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill UniversityJewish General Hospital
FundersNovartis PharmaChiesi FarmaceuticiNovartisAstraZeneca
KeywordsMedicineExacerbationCOPDInhaled corticosteroidsIntensive care medicineBronchodilatorAdverse effectCopd exacerbationClinical trialAsthmaInternal medicineAcute exacerbation of chronic obstructive pulmonary disease

Abstract

fetched live from OpenAlex

International guidance on chronic obstructive pulmonary disease (COPD) management recommends the use of inhaled corticosteroids (ICS) in those patients at increased likelihood of exacerbation. In spite of this guidance, ICS are prescribed in a large number of patients who are unlikely to benefit. Given the evidence of the risks associated with ICS and the limited indications for their use, there is interest in understanding the effects of withdrawing ICS when prescribed inappropriately. In this review, we discuss the findings of large ICS withdrawal trials, with primary focus on the more recent trials using active comparators. Data from these trials indicate that ICS may be withdrawn without adverse impact on exacerbation risk and patient-reported outcomes in patients with moderate COPD and no history of frequent exacerbations. Considering the safety concerns associated with ICS use, these medications should be withdrawn in patients for whom they are not recommended, while maintaining adequate bronchodilator therapy.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.058
GPT teacher head0.351
Teacher spread0.294 · 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 designNot applicable
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

Citations31
Published2016
Admission routes1
Has abstractyes

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