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Record W2056006860 · doi:10.1097/spc.0b013e3283392788

The dyspnea target: can we zero in on opioid responsiveness in advanced chronic obstructive pulmonary disease?

2010· review· en· W2056006860 on OpenAlexaff
Robert Horton, Graeme Rocker, David C. Currow

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2010
Typereview
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsDalhousie UniversityQueen Elizabeth II Health Sciences CentreCapital District Health AuthorityHealth Sciences Centre
Fundersnot available
KeywordsMedicinePulmonary diseaseOpioidIntensive care medicineCardiologyMEDLINEDiseaseChronic diseaseInternal medicineReceptor

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Despite recognition that opioids alleviate dyspnea in chronic obstructive pulmonary disease, many clinicians remain reluctant to use them outside of the final days of life. This article defines the term 'opioid responsiveness' as it pertains to dyspnea, and poses that it may be possible to predict more accurately the patients with chronic obstructive pulmonary disease and refractory dyspnea who might benefit from opioid treatment for either short-term use during episodes of dyspnea crisis or for long-term use for chronic dyspnea on minimal exertion. RECENT FINDINGS: This article highlights recent evidence of known dimensions contributing to the sensation of dyspnea in chronic obstructive pulmonary disease and builds on clinical observational experience to generate a conceptual model of opioid responsiveness. The 'dyspnea target' and 'opioid responsiveness score' are proposed as a means of defining more clearly the sensations encountered by a given patient and the likelihood of symptomatic improvement in response to opioids. SUMMARY: The 'dyspnea target' or similar conceptual models that attempt to predict how specific aspects of dyspnea may affect response to treatments offer clinicians the potential to more effectively target interventions. The model is presented in its theoretical stage in order to stimulate further discussion and research in an area of current interest.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.063
GPT teacher head0.401
Teacher spread0.339 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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