Review: selective COX 2 inhibitors increase vascular events more than placebo and naproxen but not more than other NSAIDs
Bibliographic record
Abstract
Kearney PM, Baigent C, Godwin J, et al . Do selective cyclo-oxygenase-2 inhibitors and traditional non-steroidal anti-inflammatory drugs increase the risk of atherothrombosis? Meta-analysis of randomised trials. BMJ 2006;332:1302–8. [OpenUrl][1][Abstract/FREE Full Text][2] Q Do selective cyclo-oxygenase-2 (COX 2) inhibitors increase risk of serious vascular events more than placebo or traditional non-steroidal anti-inflammatory drugs (NSAIDs)? Clinical impact ratings GP/FP/Primary care ★★★★★☆☆ IM/Ambulatory care ★★★★★★★ Haematology ★★★★★☆☆ Rheumatology ★★★★★★★ ### ![Graphic][3]</img>Data sources: Medline and EMBASE/Excerpta Medica (1966 to April 2005), US Food and Drug Administration website, and drug manufacturers. ### ![Graphic][4]</img>Study selection and assessment: randomised controlled trials (RCTs) ⩾4 weeks in duration that compared a selective COX 2 inhibitor with placebo or a traditional NSAID. 138 RCTs (n = 145 373) met the selection criteria. Investigators and manufacturers provided details on the number of vascular events and person time at risk. ### ![Graphic][5]</img>Outcomes: myocardial infarction (MI), stroke, and vascular death, and a composite end point of all vascular events. Selective COX 2 inhibitors increased risk … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft.stitle%253DBMJ%26rft.issn%253D0007-1447%26rft.aulast%253DKearney%26rft.auinit1%253DP.%2BM%26rft.volume%253D332%26rft.issue%253D7553%26rft.spage%253D1302%26rft.epage%253D1308%26rft.atitle%253DDo%2Bselective%2Bcyclo-oxygenase-2%2Binhibitors%2Band%2Btraditional%2Bnon-steroidal%2Banti-inflammatory%2Bdrugs%2Bincrease%2Bthe%2Brisk%2Bof%2Batherothrombosis%253F%2BMeta-analysis%2Bof%2Brandomised%2Btrials.%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.332.7553.1302%26rft_id%253Dinfo%253Apmid%252F16740558%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=332/7553/1302&atom=%2Febmed%2F11%2F6%2F171.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".