Pharmacological treatment of severe, therapy-resistant asthma in children: what can we learn from where?
Bibliographic record
Abstract
There is a lack of high-quality evidence on what treatment should be used in children with properly characterised severe, therapy-resistant asthma. Data have to be largely extrapolated from trials in children with mild asthma, and adults with severe asthma. Therapeutic options can be divided into medications used in lower doses for children with less severe asthma, and those used in other paediatric diseases but not for asthma (for example, methotrexate). In the first category are high-dose inhaled corticosteroids (ICS) (≤ 2,000 μg · day(-1) fluticasone equivalent), oral prednisolone, the anti-immunoglobulin (Ig)E antibody omalizumab, high-dose long-acting β(2)-agonists, low-dose oral theophylline and intramuscular triamcinolone. If peripheral airway inflammation is thought to be a problem, the use of fine-particle ICS or low-dose oral corticosteroids may be considered. More experimental therapies include oral macrolides, cyclosporin, cytotoxic drugs such as methotrexate and azathioprine, gold salts, intravenous infusions of Ig, subcutaneous β(2)-agonist treatment and, in those sensitised to fungi, oral antifungal therapy with itraconazole or voriconazole. Those with recurrent severe exacerbations, particularly in the context of good baseline asthma control, are particularly difficult to treat; baseline control and lung function must be optimised with the lowest possible dose of ICS, and allergen triggers and exposures minimised. The use of high-dose ICS, leukotriene receptor antagonists or both at the time of exacerbations can be considered. There is no evidence regarding which therapeutic option to recommend. Better evidence is required for all these treatment options, underscoring the need for the international and co-ordinated approach which we have previously advocated.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".