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Record W4385739881 · doi:10.1016/j.pulmoe.2023.07.006

Dynamic hyperinflation in patients with severe asthma compared to healthy adults

2023· letter· en· W4385739881 on OpenAlexaff
Thomas E. Dolmage, S. Majd, Peter Bradding, SJ Singh, R.H. Green, Rachael A Evans

Bibliographic record

VenuePulmonology · 2023
Typeletter
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsWest Park Healthcare Centre
FundersNIHR Leicester Biomedical Research CentreNational Institute for Health and Care Research
KeywordsMedicineDynamic hyperinflationAsthmaHyperinflationIntensive care medicinePhysical therapyInternal medicineLungLung volumes

Abstract

fetched live from OpenAlex

<p>Despite current medical management, exertional breathlessness is commonly experienced by adults with severe asthma limiting their exercise tolerance. A <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/cardiopulmonary-exercise-test" target="_blank">cardiopulmonary exercise test</a> may help identify the reasons for these symptoms to guide appropriate management and evaluate new interventions. For instance, exhalation can be interrupted by the next inspiration resulting in an increased end <a href="https://www.sciencedirect.com/topics/medicine-and-dentistry/expiratory-reserve-volume" target="_blank">expiratory lung volume</a>. Increasing end expiratory lung volume as ventilation increases is defined as dynamic hyperinflation.<a href="https://www.sciencedirect.com/science/article/pii/S2531043723001319?via=ihub#bib0001" target="_blank">1</a> Although there are reports of dynamic hyperinflation in asthma,<a href="https://www.sciencedirect.com/science/article/pii/S2531043723001319?via=ihub#bib0002" target="_blank">2</a>, <a href="https://www.sciencedirect.com/science/article/pii/S2531043723001319?via=ihub#bib0003" target="_blank">3</a>, <a href="https://www.sciencedirect.com/science/article/pii/S2531043723001319?via=ihub#bib0004" target="_blank">4</a> the frequency, severity and impact by exercise platform is unknown. </p>

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.249
Teacher spread0.240 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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