16-year trends in asthma hospital admissions in Canada
Bibliographic record
Abstract
BACKGROUND: Asthma hospitalizations declined rapidly in many parts of the world, including Canada, in the 1990s and early 2000s. OBJECTIVE: To examine whether the declining trend of asthma hospitalizations persisted in recent years in Canada. METHODS: Using the Canadian comprehensive nationwide hospitalization data (2002-2017), we identified hospital admissions with the main International Classification of Diseases codes for asthma. We analyzed sex-specific age-standardized trends in annual hospitalization rates among pediatric (< 19 years) and adult (19+ years) patients. We used change-point analysis to evaluate any substantial changes in the trends in the sex-age groups. RESULTS: There were 254,672 asthma-related hospital admissions (59% pediatric, 50% female) during the study period. Among children, age-adjusted annual rates per 100,000 decreased by 55% in females (152-69) and by 60% in males (270-108) from 2002 to 2017. Among adults, the rates decreased by 59% in both sexes (females: 61-25; males: 27-11). Change-point analysis indicated a substantial plateauing of the annual rate in both pediatric (from -15.3 [females] and -25.8 [males] before 2010 to -0.6 [females] and -0.8 [males] after 2010) and adult (from -5.4 [females] and -2.6 [males] before 2008 to -0.6 [females] and -0.2 [males] after 2008) groups. CONCLUSION: After a substantial decline in hospital admissions for acute asthma, there has been minimal further decline since 2010 for children and 2008 for adults. In addition to adhering to the contemporary standards of asthma care, novel, disruptive strategies are likely needed to further reduce the burden of asthma.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".