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Record W2038450952 · doi:10.1097/mcp.0b013e328341004c

The addition of long-acting beta-agonists to inhaled corticosteroids in asthma

2010· review· en· W2038450952 on OpenAlexaff
Malcolm R. Sears

Bibliographic record

VenueCurrent Opinion in Pulmonary Medicine · 2010
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineInhalerAsthmaIntensive care medicineAdverse effectInhaled corticosteroidsFood and drug administrationFormoterolFluticasone propionateB2 receptorCorticosteroidMEDLINEDrugInternal medicinePharmacologyBudesonide

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: although long-acting beta-agonists (LABAs) have been used for two decades, with many studies showing benefit versus increasing inhaled corticosteroid (ICS), controversy regarding safety has resulted in the United States Food and Drug Administration (FDA) recently mandating label changes restricting LABA use. This review addresses these safety concerns together with clinical studies and meta-analyses assessing the appropriate use of LABAs. RECENT FINDINGS: effective use of LABAs requires sufficient ICS to control inflammation. Underuse of ICS, which is often manifest by exacerbations, may reflect undue emphasis on alleged steroid-sparing effects of LABAs. The FDA meta-analysis found that LABA with mandatory ICS was not associated with increased risks of serious adverse events. The role of LABA with ICS as initial therapy in steroid-naïve patients is debated, as is LABA use in children, with data indicating less benefit than in adults. The FDA recommendation that LABA be withdrawn once control is achieved remains problematic, as greater ICS reduction can be achieved when LABA is continued. SUMMARY: the safe use of LABAs, which are clearly effective in many patients with moderate to severe asthma, requires high compliance with ICS therapy, which is best assured if ICS and LABA are provided in a single inhaler.

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)
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)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.096
GPT teacher head0.418
Teacher spread0.322 · 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

Citations19
Published2010
Admission routes1
Has abstractyes

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