A Review of the Latest Guidelines for Diagnosing and Managing Asthma in Children in the United States and Canada
Bibliographic record
Abstract
Globally, asthma remains the most widespread chronic respiratory condition in children, with a larger proportion of children being affected by the condition. Regardless of the higher prevalence rates, the outcomes of pediatric asthma have remained inadequate, even as there are numerous preventable deaths (approximately 300 children in the United States and 250 children in Canada, annually). The characteristic symptoms of pediatric asthma include wheezing, cough, and shortness of breath that are characteristically triggered by several potential stimuli. However, several diagnostic challenges exist and have resulted in either overdiagnosis or underdiagnosis, making pediatric asthma diagnosis and management problematic. Effective management of asthma in children entails a holistic approach that encompasses non-pharmacological and pharmacological management, alongside self-management and educational aspects. Working with pediatric asthma patients and their families/caregivers is vital to promoting and realizing better asthma diagnosis and management outcomes. Educational guidelines regarding the best ways for effective treatment, avoidance of triggers, modifiable risk factors, and the actions that should be taken during chronic asthma attacks through individualized action plans are vital. Thus, the objective of this systematic review is to provide an overview of the latest guidelines on pediatric asthma diagnosis and management. In this regard, this review presents several similarities in existing pediatric asthma diagnosis and management guidelines in the United States and Canada. For instance, most guidelines and studies reviewed have proposed the use of objective tests for confirmation of asthma diagnosis, particularly in symptomatic individuals. The peak flow variability measurement, bronchodilator reversibility testing, and spirometry have also been proposed by the guidelines and studies, even as the recommendations regarding the timing and hierarchy of the objective test substantially vary between the guidelines and studies. We hope that the present review will be helpful to physicians and healthcare service providers working within pediatric health contexts.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".