The use of selective cyclooxygenase‐2 inhibitors and the risk of acute myocardial infarction in Saskatchewan, Canada
Bibliographic record
Abstract
BACKGROUND: Meta-analyses of observational studies show variability in the risk of acute myocardial infarction (AMI) among non-steroidal anti-inflammatory drugs (NSAIDs), with an increase in risk for rofecoxib and diclofenac, and no increase in risk for celecoxib, naproxen, or ibuprofen. METHODS AND RESULTS: We identified a cohort of 364 658 individuals aged 40-84 years who were enrolled in Saskatchewan Health, Canada, from 15 November 1999 to 31 December 2001. A nested case-control analysis compared 3252 incident cases of hospitalized AMI and out-of-hospital CHD deaths with 20 002 controls randomly sampled from the cohort. The incidence of AMI/CHD was 5.1 per 1000 person-years (95%CI: 5.0-5.3). The adjusted ORs (95%CI) of AMI/CHD in current users of individual NSAIDs compared with non-use were: celecoxib (1.11; 0.84-1.47), rofecoxib (1.32; 0.91-1.91), diclofenac (1.02; 0.75-1.38), naproxen (1.57; 0.98-2.52), ibuprofen (1.59; 0.88-2.89), and indomethacin (1.34; 0.81-2.19). Long-term use of rofecoxib was compatible with an increased risk (OR = 1.46; 0.97-2.22) while estimates of other individual NSAIDs were close to unity. Overall NSAID use was associated with a 30% increased risk of nonfatal AMI but was absent for fatal AMI/CHD. CONCLUSIONS: This study showed a modest increased risk of AMI/CHD with various traditional NSAIDs and COX-2 inhibitors. Confidence intervals of estimated ORs included the null value for most comparisons. The study confirmed that the differentiation between traditional NSAIDs and COX-2 inhibitors is not a reliable tool for predicting cardiovascular risk associated with NSAIDs.
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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 | 0.003 | 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".