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Record W2147288045 · doi:10.1136/thorax.58.12.1007

Outcome measures in chronic obstructive pulmonary disease (COPD)

2003· editorial· en· W2147288045 on OpenAlexaff
Asger Dirksen

Bibliographic record

VenueThorax · 2003
Typeeditorial
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsCOPDMedicineVital capacityObstructive lung diseasePulmonary function testingPulmonary diseaseClinical trialPhysical therapyLung volumesInternal medicineCardiologyLungLung functionIntensive care medicineDiffusing capacity

Abstract

fetched live from OpenAlex

Lung density determined by CT scanning may be a useful outcome measure in COPD Forced expiratory volume in 1 second (FEV1) is by far the most well established outcome variable in obstructive pulmonary disease. Numerous studies have documented the correlation of this parameter with clinical variables such as severity of disease and mortality,1 and spirometric measurements have been standardised by international recommendations on lung function testing.2 Nevertheless, in real life the relevance of a maximal blow through a narrow tube is not always self-evident, and the intuitive clinical meaningfulness of this surrogate parameter is therefore perhaps less obvious. FEV1 has further limitations in chronic obstructive pulmonary disease (COPD). In general, dynamic lung volumes such as FEV1 and forced vital capacity (FVC) are highly effort dependent. However, in emphysematous subjects an abnormally low FEV1 is partly caused by the dynamic collapse of the airways which is also effort dependent. Therefore, in COPD the result of a more moderated manoeuvre is usually superior to the result of a maximal effort. This phenomenon adds to the variability of repeated measurements and, in COPD, the standard deviation of repeated measurements of FEV1 is larger than the annual decline, even in heavy smokers.3 For these reasons there is an increasing interest in other measures such as number of exacerbations or disease specific questionnaire scores as alternative outcome measures for monitoring the progress of emphysema in randomised clinical trials. Another new outcome measure is lung density …

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.091
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.031
GPT teacher head0.338
Teacher spread0.307 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations6
Published2003
Admission routes1
Has abstractyes

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