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Record W2593509478 · doi:10.1136/thoraxjnl-2016-209770

MRI ventilation abnormalities predict quality-of-life and lung function changes in mild-to-moderate COPD: longitudinal TINCan study

2017· letter· en· W2593509478 on OpenAlexafffund
Miranda Kirby, Rachel L. Eddy, Damien Pike, Sarah Svenningsen, Harvey O. Coxson, Don D. Sin, David G. McCormack, Grace Párraga

Bibliographic record

VenueThorax · 2017
Typeletter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsRobarts Clinical TrialsWestern UniversityUniversity of British Columbia
FundersInstitute of Circulatory and Respiratory HealthReseau canadien de recherche respiratoireCanadian Thoracic SocietyCanadian Lung AssociationBritish Columbia Lung AssociationCanadian Institutes of Health ResearchAstraZeneca CanadaAstraZeneca
KeywordsMedicineCOPDLongitudinal studyLung functionQuality of life (healthcare)Ventilation (architecture)Internal medicineClinical trialLongitudinal dataCardiologyLungPhysical therapyPathologyData mining

Abstract

fetched live from OpenAlex

worsening over 30 months. Among imaging biomarkers, only the longitudinal change in MRI ventilation defect percent (VDP) was greater in ever-smoker (n=34/p<0.05) and COPD (n=48/p<0.0001) subgroups compared with never-smokers (n=42). Only the longitudinal change in VDP was correlated with change in SGRQ (r=0.26/p=0.03), and only baseline VDP predicted longitudinal change in SGRQ>minimum clinically important difference (p=0.047) in mild-to-moderate COPD. These data strongly support the use of MRI intermediate endpoints in COPD studies. TRIAL REGISTRATION NUMBER: NCT02723474; Status: Recruiting.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0030.002
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 head0.071
GPT teacher head0.368
Teacher spread0.297 · 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

Citations24
Published2017
Admission routes2
Has abstractyes

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