Inhaled corticosteroid therapy reduces the risk of rehospitalization and all-cause mortality in elderly asthmatics
Bibliographic record
Abstract
Elderly patients with asthma have relatively high rates of hospitalization and mortality. Although inhaled corticosteroids have been shown to improve outcomes among younger patients with asthma, their usefulness in elderly patients has not been established. Therefore, a population-based study of patients 65 yrs of age or older, who have been hospitalized at least once with asthma in Ontario, Canada was conducted to determine the impact of inhaled corticosteroids on rehospitalization for asthma and all-cause mortality rates. Data from the Canadian Institute of Health Information was used to capture all patients 65 yrs of age and older who were hospitalized at least once, with the most responsible diagnosis of asthma in Ontario, Canada between fiscal year 1992 and 1996. This database was then linked with drug claims, physician billing and mortality databases. In total, 6,254 consecutive elderly patients with asthma were identified. Sixty percent of these patients were given at least one prescription for inhaled corticosteroids within 90 days postdischarge from their index hospitalization for asthma. Users of inhaled corticosteroids postdischarge were 29% (95% confidence interval (CI) 20%-38%) less likely to be readmitted to hospital for asthma and 39% (95% CI, 20%-53%) less likely to experience all-cause mortality compared to those who did not receive these drugs postdischarge over a one year follow-up period. These findings suggest that inhaled corticosteroids are beneficial in reducing the risk for rehospitalization and all-cause mortality in elderly patients with asthma who have recently been hospitalized for their disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".