Inhaled corticosteroids in COPD and the risk of serious pneumonia
Bibliographic record
Abstract
BACKGROUND: Inhaled corticosteroids (ICS) are known to increase the risk of pneumonia in patients with chronic obstructive pulmonary disease (COPD). It is unclear whether the risk of pneumonia varies for different inhaled agents, particularly fluticasone and budesonide, and increases with the dose and long-term duration of use. METHODS: We formed a new-user cohort of patients with COPD treated during 1990-2005. Subjects were identified using the Quebec health insurance databases and followed through 2007 or until a serious pneumonia event, defined as a first hospitalisation for or death from pneumonia. A nested case-control analysis was used to estimate the rate ratio (RR) of serious pneumonia associated with current ICS use, adjusted for age, sex, respiratory disease severity and comorbidity. RESULTS: The cohort included 163 514 patients, of which 20 344 had a serious pneumonia event during the 5.4 years of follow-up (incidence rate 2.4/100/year). Current use of ICS was associated with a 69% increase in the rate of serious pneumonia (RR 1.69; 95% CI 1.63 to 1.75). The risk was sustained with long-term use and declined gradually after stopping ICS use, disappearing after 6 months (RR 1.08; 95% CI 0.99 to 1.17). The rate of serious pneumonia was higher with fluticasone (RR 2.01; 95% CI 1.93 to 2.10), increasing with the daily dose, but was much lower with budesonide (RR 1.17; 95% CI 1.09 to 1.26). CONCLUSIONS: ICS use by patients with COPD increases the risk of serious pneumonia. The risk is particularly elevated and dose related with fluticasone. While residual confounding cannot be ruled out, the results are consistent with those from recent randomised trials.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".