The Annual September Peak in Asthma Exacerbation Rates. Still a Reality?
Bibliographic record
Abstract
RATIONALE: Recent research suggests that the asthma epidemic observed in the 1980s and 1990s has stabilized. Changing trends in asthma may have an impact on the well-reported global phenomenon of the "asthma September peak." The 38th week of the year has been identified as the peak time for asthma exacerbations among children. OBJECTIVES: The purposes of this study were to examine the longitudinal trend of the September peak and to see if it changed over time, differed by age groups, or varied across different geographical regions. METHODS: Monthly rates of asthma emergency department (ED) and physician outpatient visits were calculated using data provided by the Ontario Asthma Surveillance Information System from 2003 to 2013 for patients of all ages. The Ontario Asthma Surveillance Information System is a population-based surveillance system with over 2 million individuals with asthma. Age-specific rates were calculated using the prevalent asthma population-asthma individuals with at least one health service claim for asthma in the respective year-as the denominator. Rates were stratified by age group and region of residence. Spatial relationships within the province were tested to examine if the September peak was more prominent in certain regions of Ontario. MEASUREMENTS AND MAIN RESULTS: The highest September peak in ED visits was observed in 2005 for children aged 0-4 years and 5-9 years (18.35 and 8.11 per 1,000 asthma prevalence, respectively). The rate of asthma ED visits of all children was consistently highest in September; however, the spike became marginally less pronounced over time. Since 2005, there has been a 51.7% decrease in the September asthma ED visit rate for all age groups. Monthly physician visits for all age groups usually peaked in October, roughly 4 weeks following the peak in ED visits. Analysis by residence showed that rates throughout Ontario were higher in September than in other months, suggesting that the spike was widespread rather than localized. CONCLUSIONS: While the magnitude of the September peak has decreased over time, the asthma ED visit rate remains significantly higher in September than in other months. Physician visits are also highest in the fall. These findings stress the importance of empowering children and families to maintain good asthma control throughout the year, including hand washing, to minimize respiratory viral infections in September.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".