Association of Selective and Conventional Nonsteroidal Antiinflammatory Drugs with Acute Renal Failure: A Population-based, Nested Case-Control Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Conventional nonsteroidal antiinflammatory drugs (NSAIDs) are associated with acute renal failure, but cyclooxygenase-2 inhibitors have not been comparatively evaluated. The authors conducted a nested case-control study to assess the association between exposure to NSAIDs, including cyclooxygenase-2 inhibitors, and hospitalization for acute renal failure. They identified 121,722 new NSAID users older than age 65 years from the administrative health care databases of Quebec, Canada, in 1999-2002. Data for 4,228 cases and 84,540 controls matched on age and follow-up time were analyzed by using conditional logistic regression, adjusted for sex, age, health status, health care utilization measures, exposure to contrast agents, and nephrotoxic medications. The risk of acute renal failure for all NSAIDs combined was highest within 30 days of treatment initiation (adjusted rate ratio (RR) = 2.05, 95% confidence interval (CI): 1.61, 2.60) and receded thereafter. The association with acute renal failure within 30 days of therapy initiation was comparable for rofecoxib (RR = 2.31, 95% CI: 1.73, 3.08), naproxen (RR = 2.42, 95% CI: 1.52, 3.85), and nonselective, non-naproxen NSAIDs (RR = 2.30, 95% CI: 1.60, 3.32) but was borderline lower for celecoxib (RR =1.54, 95% CI: 1.14, 2.09; test for interaction comparing celecoxib with rofecoxib, p = 0.057). There was a significant association for both selective and nonselective NSAIDs with acute renal failure, but confirmatory studies are required.
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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 | 0.001 | 0.001 |
| 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 it