Use of acid-suppressive drugs and risk of pneumonia: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Observational studies and randomized controlled trials have yielded inconsistent findings about the association between the use of acid-suppressive drugs and the risk of pneumonia. We performed a systematic review and meta-analysis to summarize this association. METHODS: We searched three electronic databases (MEDLINE [PubMed], Embase and the Cochrane Library) from inception to Aug. 28, 2009. Two evaluators independently extracted data. Because of heterogeneity, we used random-effects meta-analysis to obtain pooled estimates of effect. RESULTS: We identified 31 studies: five case-control studies, three cohort studies and 23 randomized controlled trials. A meta-analysis of the eight observational studies showed that the overall risk of pneumonia was higher among people using proton pump inhibitors (adjusted odds ratio [OR] 1.27, 95% confidence interval [CI] 1.11-1.46, I(2) 90.5%) and histamine(2) receptor antagonists (adjusted OR 1.22, 95% CI 1.09-1.36, I(2) 0.0%). In the randomized controlled trials, use of histamine(2) receptor antagonists was associated with an elevated risk of hospital-acquired pneumonia (relative risk 1.22, 95% CI 1.01-1.48, I(2) 30.6%). INTERPRETATION: Use of a proton pump inhibitor or histamine(2) receptor antagonist may be associated with an increased risk of both community- and hospital-acquired pneumonia. Given these potential adverse effects, clinicians should use caution in prescribing acid-suppressive drugs for patients at risk.
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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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".