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Record W2155650191 · doi:10.1183/09031936.00181608

Airway smooth muscle thickness in asthma is related to severity but not duration of asthma

2009· article· en· W2155650191 on OpenAlexafffund
Alan James, T R Bai, Thaís Mauad, Michael J. Abramson, Marisa Dolhnikoff, Karen McKay, Peta S. Maxwell, John Elliot, F. H. Green

Bibliographic record

VenueEuropean Respiratory Journal · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Calgary
FundersNational Health and Medical Research CouncilMedical Research CouncilCanadian Institutes of Health Research
KeywordsMedicineAsthmaAirwayDuration (music)CardiologyInternal medicineAnesthesiaAcoustics

Abstract

fetched live from OpenAlex

Asthma is characterised by an increased airway smooth muscle (ASM) area (ASM(area)) within the airway wall. The present study examined the relationship of factors including severity and duration of asthma to ASM(area). The perimeter of the basement membrane (PBM) and ASM(area) were measured on transverse sections of large and small airways from post mortem cases of fatal (n = 107) and nonfatal asthma (n = 37) and from control subjects (n = 69). The thickness of ASM (ASM(area)/PBM) was compared between asthma groups using multivariate linear regression. When all airways were considered together, ASM(area)/PBM (in millimetres) was increased in nonfatal (median 0.04; interquartile range 0.013-0.051; p = 0.034) and fatal cases of asthma (0.048; 0.025-0.078; p<0.001) compared with controls (0.036; 0.024-0.042). Compared with cases of nonfatal asthma, ASM(area)/PBM was greater in cases of fatal asthma in large (p<0.001) and medium (p<0.001), but not small, airways. ASM(area)/PBM was not related to duration of asthma, age of onset of asthma, sex or smoking. No effect due to study centre, other than that due to sampling strategy, was found. The thickness of the ASM layer is increased in asthma and is related to the severity of asthma but not its duration.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.866
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.271
Teacher spread0.254 · 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

Citations176
Published2009
Admission routes2
Has abstractyes

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