Clinical effectiveness and safety of montelukast in asthma. What are the conclusions from clinical trials and meta-analyses?
Bibliographic record
Abstract
Kam Lun Ellis Hon,1 Ting Fan Leung,1 Alexander KC Leung21Department of Paediatrics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong; 2Department of Pediatrics, The University of Calgary, Calgary, AB, CanadaAbstract: Asthma is a common childhood atopic disease associated with chronicity and impaired quality of life. As there is no cure for this disease, treatment relies on avoidance of triggers such as food and aeroallergens, the use of inhaled bronchodilators/corticosteroids and antiallergic or immunomodulating therapies. Inhaled corticosteroids (ICSs) and bronchodilators have been the mainstay. However, in Asia, myths and fallacies regarding Western medicine and corticosteroids are prevalent and lead to nonadherence to treatment. Also, use of traditional and proprietary herbal medicines is popular. In the past decades, a novel class of nonsteroidal immunomodulating montelukasts has become available. This article reviews the evidence for the effectiveness and clinical efficacy of these medications. A number of randomized and controlled trials have been performed over the years. The majority of studies confirm the usefulness of montelukast as monotherapy and add-on therapy to ICS in mild to moderate childhood asthma across all age groups. ICSs are generally superior to montelukasts for asthma management. However, montelukast has a place in the treatment of young children with viral-triggered wheezing diseases, exercise-induced asthma, and in children whose parents are steroid-phobic and find ICS unacceptable.Keywords: cysteinyl leukotriene receptor antagonist, inhaled corticosteroid, randomized control trial, meta analysis
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.061 | 0.095 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.061 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".