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Record W2171647346 · doi:10.1164/ajrccm.162.3.9907120

Computed Tomographic Measurements of Airway Dimensions and Emphysema in Smokers

2000· article· en· W2171647346 on OpenAlexaff
Yasutaka Nakano, Shigeo Muro, Hiroaki Sakai, Toyohiro Hirai, Kazuo Chin, Mitsuhiro Tsukino, Koichi Nishimura, Harumi Itoh, Peter D. Paré, James C. Hogg, Michiaki Mishima

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2000
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineAirwayCOPDComputed tomographicAirway obstructionPulmonary function testingRadiologyLungAir trappingComputed tomographyInternal medicineSurgery

Abstract

fetched live from OpenAlex

Chronic obstructive pulmonary disease (COPD) is characterized by the presence of airflow obstruction caused by emphysema or airway narrowing, or both. Low attenuation areas (LAA) on computed tomography (CT) have been shown to represent macroscopic or microscopic emphysema, or both. However CT has not been used to quantify the airway abnormalities in smokers with or without airflow obstruction. In this study, we used CT to evaluate both emphysema and airway wall thickening in 114 smokers. The CT measurements revealed that a decreased FEV(1) (%predicted) is associated with an increase of airway wall area and an increase of emphysema. Although both airway wall thickening and emphysema (LAA) correlated with measurements of lung function, stepwise multiple regression analysis showed that the combination of airway and emphysema measurements improved the estimate of pulmonary function test abnormalities. We conclude that both CT measurements of airway dimensions and emphysema are useful and complementary in the evaluation of the lung of smokers.

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)0.001
metaresearch head score (Gemma)0.005
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.029
GPT teacher head0.330
Teacher spread0.302 · 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

Citations692
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Respiratory and Critical Care MedicineSame topicChronic Obstructive Pulmonary Disease (COPD) ResearchFrench-language works237,207