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The Link between Reduced Inspiratory Capacity and Exercise Intolerance in Chronic Obstructive Pulmonary Disease

2017· review· en· W2607317232 on OpenAlexaff
Denis E. O’Donnell, Amany F. Elbehairy, Katherine A. Webb, J. Alberto Neder

Bibliographic record

VenueAnnals of the American Thoracic Society · 2017
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsKingston General HospitalQueen's University
Fundersnot available
KeywordsMedicineDynamic hyperinflationHyperinflationExercise intoleranceObstructive lung diseaseCardiologyInternal medicinePulmonary function testingLung volumesLungPhysical therapyIntensive care medicinePulmonary diseaseHeart failure

Abstract

fetched live from OpenAlex

Low inspiratory capacity (IC), chronic dyspnea, and reduced exercise capacity are inextricably linked and are independent predictors of increased mortality in chronic obstructive pulmonary disease. It is no surprise, therefore, that a major goal of management is to improve IC by reducing lung hyperinflation to improve respiratory symptoms and health-related quality of life. The negative effects of lung hyperinflation on respiratory muscle and cardiocirculatory function during exercise are now well established. Moreover, there is growing appreciation that a key mechanism of exertional dyspnea in chronic obstructive pulmonary disease is critical mechanical constraints on tidal volume expansion during exercise when resting IC is reduced. Further evidence for the importance of lung hyperinflation comes from multiple studies, which have reported the clinical benefits of therapeutic interventions that reduce lung hyperinflation and increase IC. A reduced IC in obstructive pulmonary disease is further eroded by exercise and contributes to ventilatory limitation and dyspnea. It is an important outcome for both clinical and research studies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.001
Science and technology studies0.0010.006
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
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 head0.170
GPT teacher head0.444
Teacher spread0.274 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations73
Published2017
Admission routes1
Has abstractyes

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