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Record W1979585673 · doi:10.1055/s-0035-1544789

Lung function improvements with twice-daily aclidinium/formoterol fixed-dose combination in two 24-week studies in patients with COPD

2015· article· en· W1979585673 on OpenAlexaff
Dave Singh, Anthony D’Urzo, Paul Jones, Cristina Helena dos Reis Serra, Victor Mergel

Bibliographic record

VenuePneumologie · 2015
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFormoterolMedicineFixed-dose combinationCOPDBronchodilationPlaceboFormoterol FumarateBronchodilatorAnesthesiaInternal medicineInhalationAsthma

Abstract

fetched live from OpenAlex

BACKGROUND: Fixed-dose combinations (FDC) of different bronchodilators improve lung function through complementary mechanisms. AIM: To assess bronchodilation with an FDC comprising aclidinium bromide and formoterol fumarate in patients with moderate to severe COPD. METHODS: In 2 phase 3 trials, ACLIFORM COPD (S1) and AUGMENT COPD (S2), patients were randomized to 24 weeks of twice-daily inhaled aclidinium/formoterol 400µg/12µg (FDC 400/12), 400µg/6µg (FDC 400/6), aclidinium 400µg (ACL), formoterol 12µg (FOR), or placebo (PBO). Lung function coprimary outcomes were change from baseline to week 24 for 1-hr morning postdose FEV 1 (FDC vs ACL) and morning predose (trough) FEV 1 (FDC vs FOR). RESULTS: Baseline mean FEV 1 were 1.38L (S1) and 1.36L (S2) (54.2% and 53.5% predicted). At the first time point assessed, treatment with either FDC resulted in significant improvements in the coprimary endpoints that were generally maintained at study end (Table). Each FDC showed clinically significant improvements in both endpoints vs PBO that were evident as early as 5 min postdose on day 1 (range: 100–128 mL, p CONCLUSIONS: Fixed-dose combination of aclidinium/formoterol showed rapid and sustained improvements in bronchodilation compared with each monotherapy and placebo, with numerically greater improvements observed with FDC 400/12 vs FDC 400/6.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.068
GPT teacher head0.324
Teacher spread0.256 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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