Hospitalization for gastrointestinal bleeding associated with non-steroidal anti-inflammatory drugs among elderly patients using low-dose aspirin: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVES: Many elderly patients are prescribed both low-dose aspirin (ASA), for cardiovascular protection and non-steroidal anti-inflammatory drugs (NSAIDs) for pain control. Compared with non-selective NSAIDs (NS-NSAIDs), celecoxib has a superior gastrointestinal (GI) safety profile in general. It is unclear, however, whether this fact holds good among patients taking ASA. We compared GI hospitalization rates among elderly patients taking celecoxib, NS-NSAIDs, celecoxib and ASA or NS-NSAIDs and ASA. METHODS: This was a retrospective cohort study using Quebec government databases. All patients 65 yrs of age or older who filled a prescription for celecoxib or an NS-NSAID between April 1999 and December 2002 were included. Cox regression models were used to compare the GI hospitalization rates between the four exposure categories adjusting for potential confounders. RESULTS: A total of 332 491 patients were included. Among 1 522 307 celecoxib prescriptions, 430 214 were filled by patients concurrently receiving ASA (celecoxib and ASA); 195 369 of 863 646 NS-NSAID prescriptions were filled by patients receiving ASA (NS-NSAID and ASA). Celecoxib without ASA was less likely than NS-NSAID without ASA to be associated with GI hospitalization [hazard ratio (HR) 0.41, 95% confidence interval (CI) 0.33-0.50]; celecoxib and ASA was also less likely to be associated with GI hospitalization than NS-NSAID and ASA (HR 0.62, 95% CI 0.48-0.80); GI hospitalization rates were similar for celecoxib and ASA and NS-NSAID without ASA (HR 1.01, 95% CI 0.81-1.25). CONCLUSION: Among elderly patients receiving cardiovascular protection with ASA and pain control with anti-inflammatory drugs, celecoxib may be safer with regards to GI toxicity than NS-NSAIDs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".