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Leukotriene receptor antagonists: Efficacy and safety in children with asthma

2000· article· en· W1975176727 on OpenAlexaff
Allan Becker

Bibliographic record

VenuePediatric Pulmonology · 2000
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMontelukastMedicineLeukotriene receptorPlaceboAsthmaQuality of life (healthcare)Adverse effectLeukotriene E4Internal medicineAntagonistLeukotrieneAnesthesiaPediatricsReceptor

Abstract

fetched live from OpenAlex

To date, only one study of chronic use of a leukotriene receptor antagonist in children has been published. The efficacy and safety of montelukast in children 6-14 years of age with asthma (n = 336) was studied during an 8-week, double-blind, placebo-controlled trial. There was significantly greater improvement in forced expired volume in 1 sec (FEV(1)) from baseline for the montelukast group (8. 23%) compared to the placebo group (3.58%). There was a significant decrease in use of beta agonists for symptom relief and a significant decrease in the percentage of days and percentage of patients with asthma exacerbations. An asthma-specific quality of life questionnaire revealed significant overall improvement in quality of life and significant improvement in the quality of life domains for symptoms, activity, and emotions. Adverse effects were not significantly different for montelukast than for placebo, with the exception of allergic rhinitis which was more prevalent in the placebo group. A 6-month open follow-up of patients from the above study was undertaken. Effects of montelukast on FEV(1) were consistent over the 6 months, with the increase in FEV(1) not significantly different from a small control group treated with beclomethasone. Quality of life remained significantly improved throughout the open treatment period. In conclusion, leukotriene receptor antagonists are of value for the treatment of children with asthma.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.770

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.226
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2000
Admission routes1
Has abstractyes

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