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Pharmacologic Treatment Strategies

2011· book-chapter· en· W168884580 on OpenAlexaff
Rachael A Evans, Robert Varadi, Kambiz Mirzaei, Roger Goldstein

Bibliographic record

VenueHumana Press eBooks · 2011
Typebook-chapter
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsWest Park Healthcare Centre
Fundersnot available
KeywordsMedicineCOPDBronchodilatationIntensive care medicineDiabetes mellitusDiseaseOsteoporosisMoodAirway obstructionAirwayPhysical therapyInternal medicineAsthmaAnesthesiaBronchodilatorEndocrinology

Abstract

fetched live from OpenAlex

As COPD is characterized by only partially reversible airway obstruction, respiratory pharmacological agents focus primarily on addressing the airflow limitation, both by bronchodilatation and by reducing airway inflammation. However, the symptoms, morbidity and mortality associated with COPD are also associated with secondary impairments, such as skeletal muscle dysfunction, decreased bone density and alterations of mood. Patient management must also consider common co-morbidities such as cardiovascular disease and diabetes. Therefore pharmacological management must address both the consequences of the pulmonary disease, the secondary impairments and the co-morbidities. This chapter provides discussion of 1) the currently recommended pulmonary pharmacological treatment, 2) the interaction between COPD and cardiovascular disease, and the implications for pharmacological management, 3) an overview of the management of osteoporosis in COPD, 4) the interaction between COPD and diabetes, and the implications for pharmacological management, 5) the management of mood disorders, 6) future treatment directions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.047
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0470.018

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 head0.143
GPT teacher head0.347
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2011
Admission routes1
Has abstractyes

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