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Record W4409795342 · doi:10.15326/jcopdf.2024.0564

Pragmatic Evaluation of an Improvement Program for People Living With Modifiable High-Risk COPD Versus Usual Care: Protocol for the Cluster Randomized PREVAIL Trial

2025· article· en· W4409795342 on OpenAlexaff
Katherine Hickman, Yasir Tarabichi, Andy Dickens, Rachel Pullen, Margee Kerr, Amy Couper, Alexander Evans, J. Christopher Gatenby, Luís Alves, Cono Ariti, Mona Bafadhel, Victoria Carter, James D. Chalmers, Rongchang Chen, Graham Devereux, Michael Drummond, Martin Gibson, David Halpin, Meilan Han, Nicola A. Hanania, John R. Hurst, Alan Kaplan, Κonstantinos Κostikas, Barry J. Make, Douglas W. Mapel, Jonathan Marshall, Fernando Betancourt Martínez, Catherine A. Meldrum, Marije van Melle, Marc Miravitlles, Tamsin Morris, Hana Müllerová, Ruth Murray, Shigeo Muro, Clémentine Nordon, Jill Ohar, Wilson D. Pace, Michael Pollack, JK Quint, Anita Sharma, Dave Singh, Mukesh Singh, Frank Trudo, Dennis Williams, Tonya Winders, David Price

Bibliographic record

VenueChronic Obstructive Pulmonary Diseases Journal of the COPD Foundation · 2025
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsUniversity of TorontoAir Canada
FundersManchester Biomedical Research CentreNational Institutes of HealthGenentechGrifolsNational Institute for Health and Care ResearchTeva Pharmaceutical IndustriesInsmedSunovionGilead SciencesSanofiAstraZenecaAmgenNational Heart, Lung, and Blood InstitutePfizerMylanGlaxoSmithKline
KeywordsMedicineCOPDRandomized controlled trialCluster (spacecraft)GerontologyComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Background: The burden of chronic obstructive pulmonary disease (COPD) is well established, but opportunities for earlier diagnosis and improved management are still missed. Compared to the general COPD population, patients with a history of exacerbations and suboptimal treatment ("modifiable high-risk") are at greater risk of future exacerbations and adverse health outcomes. To date there is no systematic approach for identifying and treating this patient group. Method: Two cluster randomized controlled trials (CRTs) in the United Kingdom and United States will assess the impact of a primary care-based quality improvement program (COllaboratioN on QUality improvement initiative for achieving Excellence in STandards of COPD care [CONQUEST]), compared to routine care. In each trial, 126 primary care clusters will be randomized 1:1 to intervention or control arms. Three groups of modifiable high-risk patients will be identified using electronic medical records: undiagnosed with potential COPD, newly diagnosed COPD, and already diagnosed COPD. Eligible patients will be aged ≥40 years, have experienced ≥2 moderate/≥1 severe exacerbation(s) in the prior 24 months, including ≥1 in the last 12 months, and not be prescribed inhaled triple therapy. Patients in the undiagnosed group will also be required to have a positive smoking history. Primary trial outcomes will be the annual rate of exacerbations and the annual rate of major adverse cardiac or respiratory events, comparing the quality improvement program against routine care. Discussion: These will be the first CRTs assessing such a comprehensive primary care-based COPD quality improvement program. Intention-to-treat analysis of trial outcomes after 24 months will inform its effectiveness in targeting the identification, assessment, treatment, and follow-up of patients with modifiable high-risk COPD. Trial registration: UK trial: ISRCTN15819828; US trial: NCT05306743.

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)0.037
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.063
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.042
Meta-epidemiology (narrow)0.0080.003
Meta-epidemiology (broad)0.0130.009
Bibliometrics0.0020.003
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0040.004
Research integrity0.0080.009
Insufficient payload (model declined to judge)0.0630.010

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 head0.019
GPT teacher head0.351
Teacher spread0.332 · 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 designRandomized trial
Domainnot available
GenreProtocol

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
Published2025
Admission routes1
Has abstractyes

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