A population based historical cohort study of the mortality associated with nabumetone, Arthrotec, diclofenac, and naproxen.
Bibliographic record
Abstract
OBJECTIVE: To identify the unbiased differences in all cause mortality among populations using 4 non-steroidal antiinflammatory drugs (NSAID): nabumetone, Arthrotec, diclofenac plus a cytoprotective agent dispensed separately (diclofenac+), and naproxen. METHODS: We performed a population based historical cohort study using linked data from several provincial health care databases. Logistic regression was used to produce estimates of the mortality associated with the study drugs unbiased by known confounders. The entire population of the province of Saskatchewan, Canada entitled to drug plan benefits in 1995 was eligible (approximately 91% of 1 million people). Participants were identified if they filled a prescription for one of the 4 study NSAID (18,424 individuals). They were then followed forward in time for 6 months to determine all cause mortality. RESULTS: Compared to nabumetone, the adjusted odds of death for participants taking Arthrotec was 1.4 (95% confidence interval, CI: 0.9-2.1), for diclofenac+ 2.0 (1.3-3.1), and naproxen 3.0 (1.9-4.6). CONCLUSION: The multivariate analysis showed patients taking nabumetone and Arthrotec had significantly lower mortality than those taking other study drugs. Nabumetone had 1/3 to 1/5 the mortality associated with the diclofenac+ and naproxen groups. It appears that inherent gastroprotective strategies in the study NSAID may translate into decreased mortality at the population level.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".