Use of anti-inflammatory therapy and asthma mortality in Japan
Bibliographic record
Abstract
Asthma treatment guidelines were introduced in Japan in the 1990s, insisting as elsewhere, on the importance of anti-inflammatory therapy. The present study assessed whether use of anti-inflammatory medications was associated with a decrease in asthma mortality in Japan, the first country to use leukotriene receptor antagonists. A population-based ecological study was conducted, spanning the period 1987-1999, among people aged 5-34 yrs in Japan. The association between the yearly rate of asthma death and sales of inhaled corticosteroids and leukotriene receptor antagonists was estimated using Poisson regression. The yearly asthma death rate was stable at 6-7 deaths per million before the introduction of leukotriene receptor antagonists in 1995 and decreased by 23% thereafter, reaching 3.5 per million in 1999. The rate of asthma death was found to decrease with increasing use of both leukotriene receptor antagonists and inhaled corticosteroids. The rate ratio of asthma death was 0.96 per 1 million 25-day treatment courses of inhaled corticosteroids and 0.80 for every 1 million 25-day treatment courses of leukotriene receptor antagonists, consumed per year in Japan. The increasing use of inhaled corticosteroids and leukotriene receptor antagonists may have contributed to the significant reduction in asthma mortality among young asthmatics in Japan.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".