Postoperative pneumonia in elderly patients receiving acid suppressants: a retrospective cohort analysis
Bibliographic record
Abstract
OBJECTIVE: To test whether gastric acid suppressants are associated with an increased risk of postoperative pneumonia in patients undergoing elective surgery. DESIGN: Population-wide retrospective cohort analysis. SETTING: Canadian acute care hospitals between 1 April 1992 and 31 March 2008. Patients Consecutive patients aged >65 years admitted for an elective operation. OUTCOME MEASURE: Postoperative pneumonia recorded in inpatient postoperative notes. RESULTS: A total of 593 265 patients were included, of whom about 21% were taking an acid suppressant (most commonly omeprazole or ranitidine). Overall, 6389 patients developed postoperative pneumonia, with a rate significantly higher for those taking acid suppressants (13 per 1000) than controls (10 per 1000), equivalent to a 30% increase in frequency (odds ratio 1.30 (95% confidence interval 1.23 to 1.38), P<0.001). However, no increase in risk was observed after adjustment for duration of surgery, site of surgery, and other confounders (odds ratio 1.02 (0.96 to 1.09), P=0.48). The general safety of acid suppressants extended to those patients prescribed proton pump inhibitors, experiencing long term treatment, receiving high doses, and undergoing high risk procedures. CONCLUSION: After adjustment for patient and surgical characteristics, acid suppressants are not associated with an increased risk of postoperative pneumonia among elderly patients admitted for elective surgery.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".