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Record W2590555427 · doi:10.3389/fphys.2017.00082

Advances in the Evaluation of Respiratory Pathophysiology during Exercise in Chronic Lung Diseases

2017· review· en· W2590555427 on OpenAlexafffund
Denis E. O’Donnell, Amany F. Elbehairy, Danilo Cortozi Berton, Nicolle J. Domnik, J. Alberto Neder

Bibliographic record

VenueFrontiers in Physiology · 2017
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsKingston General HospitalQueen's University
FundersQueen's University
KeywordsMedicineExercise intoleranceCOPDIntensive care medicineQuality of life (healthcare)Respiratory physiologyAsthmaInterstitial lung diseaseRespiratory systemLungPhysical therapyAerobic exerciseRespiratory diseaseDiseaseCardiologyPulmonary hypertensionPathophysiologyInternal medicineHeart failure

Abstract

fetched live from OpenAlex

Dyspnea and exercise limitation are among the most common symptoms experienced by patients with various chronic lung diseases and are linked to poor quality of life. Our understanding of the source and nature of perceived respiratory discomfort and exercise intolerance in chronic lung diseases has increased substantially in recent years. These new mechanistic insights are the primary focus of the current review. Cardiopulmonary exercise testing (CPET) provides a unique opportunity to objectively evaluate the ability of the respiratory system to respond to imposed incremental physiological stress. In addition to measuring aerobic capacity and quantifying an individual's cardiac and ventilatory reserves, we have expanded the role of CPET to include evaluation of symptom intensity, together with a simple "non-invasive" assessment of relevant ventilatory control parameters and dynamic respiratory mechanics during standardized incremental tests to tolerance. This review explores the application of the new advances in the clinical evaluation of the pathophysiology of exercise intolerance in chronic obstructive pulmonary disease (COPD), chronic asthma, interstitial lung disease (ILD) and pulmonary arterial hypertension (PAH). We hope to demonstrate how this novel approach to CPET interpretation, which includes a quantification of activity-related dyspnea and evaluation of its underlying mechanisms, enhances our ability to meaningfully intervene to improve quality of life in these pathologically-distinct conditions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.401
Teacher spread0.347 · 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

Citations99
Published2017
Admission routes2
Has abstractyes

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