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Record W2095618090 · doi:10.1097/mcp.0b013e328334a728

Exertional dyspnea in chronic obstructive pulmonary disease: mechanisms and treatment approaches

2010· review· en· W2095618090 on OpenAlexaff
Josuel Ora, Dennis Jensen, Denis E. O’Donnell

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsQueen's UniversityKingston General Hospital
Fundersnot available
KeywordsMedicineCOPDIntensive care medicineAnxietyDiseasePulmonary diseaseHelioxPhysical therapyInternal medicineAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The purpose of this review is to identify new advances in our understanding of dyspnea in patients with chronic obstructive pulmonary disease (COPD). Specifically, we highlight new scientific discoveries concerning the language of dyspnea, its underlying mechanisms and its clinical management. RECENT FINDINGS: Recent studies have confirmed that dyspnea is multidimensional and that sensory intensity and quality dimensions of the symptom are readily distinguishable by the individual. When respiratory discomfort is sufficiently unpleasant in COPD, an emotive response is evoked which encompasses feelings of fear and anxiety. Such descriptors appear to be unique to the disease state and are rarely reported in health. Recent brain imaging studies have proposed a central role of the limbic and paralimbic systems in the genesis of perceived dyspnea or its affective component. There is new indirect evidence that the elaboration of endogenous opioids may modulate dyspnea intensity during exercise in COPD. New physiological studies in COPD have provided novel insights into mechanisms of dyspnea both in early disease and in the setting of coexistent obesity. SUMMARY: The effective management of dyspnea in COPD remains a significant challenge for caregivers but recent treatment innovations such as helium-oxygen, inhaled furosemide and breathing feedback techniques have yielded early positive results.

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), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.385
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

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

Citations31
Published2010
Admission routes1
Has abstractyes

Explore more

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