Association between nonnaproxen NSAIDs, COX‐2 inhibitors and hospitalization for acute myocardial infarction among the elderly: a retrospective cohort study
Bibliographic record
Abstract
PURPOSE: To evaluate the association between rofecoxib, celecoxib, diclofenac, and ibuprofen and the risk of hospitalization for acute myocardial infarction (AMI) in an elderly population. METHODS: We conducted a retrospective cohort study, using data from the government of Quebec health insurance agency databases, among patients 65-80 years of age who filled a prescription for any of the study drugs during 1999-2002. Cox regression models with time-dependent exposure were used to compare the incidence rates of hospitalization for AMI adjusting for patients' baseline characteristics. Analyses stratified by dose and number of supplied days were also conducted. RESULTS: At the index date, a total of 91 062 patients were taking rofecoxib, 127 928 celecoxib, 49 193 diclofenac, and 15 601 ibuprofen. The adjusted hazard ratio (HR) (95%CI) of hospitalization for AMI were: celecoxib versus rofecoxib: 0.90 (0.79, 1.01); ibuprofen versus rofecoxib: 0.95 (0.65, 1.37); diclofenac versus rofecoxib: 1.01 (0.84, 1.22). In secondary analyses based on intended duration of use, neither COX-2 selective inhibitor was associated with a higher risk than ibuprofen or diclofenac. The unadjusted risk of AMI for all NSAIDs increased with dose. In the direct two way adjusted comparison of each NSAID stratified by dose, the only statistically significant difference was with rofecoxib >25 mg/day versus celecoxib >200 mg/day. CONCLUSION: In this study there was no difference between AMI occurrence in elderly patients taking rofecoxib or celecoxib at recommended doses for chronic indications versus those taking ibuprofen/diclofenac. However, the risk of AMI was higher among patients using higher doses of rofecoxib (>25 mg/day) compared to patients using higher doses of celecoxib (>200 mg/day).
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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 | 0.006 | 0.001 |
| 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".