Inhaled Corticosteroids and Risk of Recurrent Pneumonia: A Population-Based, Nested Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Studies have suggested an increased risk of pneumonia with inhaled corticosteroid (ICS) use, although this association is inconsistent. We evaluated the risk of recurrent pneumonia associated with ICS use in a high-risk population of individuals who survived an episode of pneumonia. METHODS: Clinical and 5-year follow-up data were collected on all adults aged ≥ 65 years with pneumonia over a period of 2 years. Using a nested case-control design, first cases (patients with recurrent pneumonia ≥ 30 days after initial episode) and then controls (free of pneumonia and matched on age, sex, and chronic obstructive pulmonary disease [COPD]) were identified. ICS use was classified as never, past (remote, only before initial pneumonia), or current. Our primary outcome measure was recurrent pneumonia assessed using conditional multivariate logistic regression after adjustment of demographics and clinical data. RESULTS: During 5 years of follow-up, 653 recurrent pneumonia cases were matched with 6244 controls; mean age was 79 (SD, 8) years, 3577 (52%) were male, 2652 (38%) had COPD, and 2294 (33%) ever used ICS. Overall, 123 of 870 (14%) current ICS users had recurrent pneumonia compared to 395 of 4603 (9%) never-users (adjusted odds ratio, 1.90; 95% confidence interval, 1.45-2.50; P < .001; number need to harm = 20). Conversely, there was no association between past (remote) use of ICS and pneumonia: 9% of past users versus 9% never-users (P = .36). CONCLUSIONS: ICS use was associated with a 90% relative increase in the risk of recurrent pneumonia among high-risk pneumonia survivors. This should be considered when prescribing ICS and when deciding which patients might need more intensive follow-up.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".