Risk of congestive heart failure with nonsteroidal antiinflammatory drugs and selective Cyclooxygenase 2 inhibitors: A class effect?
Bibliographic record
Abstract
OBJECTIVE: Nonsteroidal antiinflammatory drugs (NSAIDs) as a class have been shown to increase the risk of congestive heart failure (CHF) compared with celecoxib. The magnitude of the risk for individual NSAIDs is not known. METHODS: Using administrative databases, we performed a nested case-control study in a population-based cohort of patients ages >or=66 years admitted for CHF between January 1998 and March 2003. Cases were patients readmitted for CHF after cohort entry (index date). Four controls were matched to each case on date of cohort entry and time between cohort entry and index date. Exposure was the current use of an NSAID or a coxib in the 7 days prior to CHF readmission. Using conditional logistic regression, we calculated the odds of readmission for CHF in patients exposed to naproxen, diclofenac, ibuprofen, indomethacin, or rofecoxib compared with celecoxib, after adjusting for possible confounding variables. RESULTS: We identified 8,512 cases and 34,048 controls. The baseline characteristics between the groups were similar in general. The odds of being readmitted for CHF were higher in patients currently exposed to indomethacin (odds ratio [OR] 2.04, 95% confidence interval [95% CI] 1.16-3.58) or rofecoxib (OR 1.58, 95% CI 1.19-2.11) compared with celecoxib. There was no difference between naproxen, diclofenac, and ibuprofen compared with celecoxib, although the numbers of exposed cases and controls were small. CONCLUSION: In elderly patients with known CHF, indomethacin and rofecoxib are associated with a greater risk of recurrent CHF compared with celecoxib. Alternatives should be considered for patients with CHF who require antiinflammatory drugs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".