Bibliographic record
Abstract
BACKGROUND: Asthma is the most common chronic disease of childhood and a major source of childhood health burden worldwide. These burdens are particularly marked when children experience characteristic 'symptom flare-ups' or acute asthma exacerbations (AAEs). AAE are associated with significant health and economic impacts, including acute Emergency Department visits, occasional hospitalizations, and rarely, death. To treat children with AAE, several medications have been studied and used. METHODS: We conducted a narrative review of the literature with the primary objective of understanding the evidence of their efficacy. We present this efficacy evidence in the context of a general stepwise management pathway for paediatric AAEs. This framework is developed from the combined recommendations of eight established (inter)national paediatric guidelines. DISCUSSION: Management of paediatric AAE centres around four major care goals: (1) immediate and objective assessment of AAE severity; (2) prompt and effective medical interventions to decrease respiratory distress and improve oxygenation; (3) appropriate disposition of patient; and (4) safe discharge plans. Several medications are currently recommended with varying efficacies, including heliox, systemic corticosteroids, first-line bronchodilators (salbutamol/albuterol), adjunctive bronchodilators (ipratropium bromide, magnesium sulfate) and second-line bronchodilators (aminophylline, i.v. salbutamol, i.v. terbutaline, epinephrine, ketamine). Care of children with AAE is further enhanced using clinical severity scoring, pathway-driven care and after-event discharge planning. CONCLUSIONS: AAEs in children are primarily managed by medications supported by a growing body of literature. Continued efforts to study the efficacy of second-line bronchodilators, integrate AAE management with long-term asthma control and provide fair/equitable care are required.
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 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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".