A Comparison of Bare-Metal and Drug-Eluting Stents for Off-Label Indications
Bibliographic record
Abstract
BACKGROUND: Recent reports suggest that off-label use of drug-eluting stents is associated with an increased incidence of adverse events. Whether the use of bare-metal stents would yield different results is unknown. METHODS: We analyzed data from 6551 patients in the National Heart, Lung, and Blood Institute Dynamic Registry according to whether they were treated with drug-eluting stents or bare-metal stents and whether use was standard or off-label. Patients were followed for 1 year for the occurrence of cardiovascular events and death. Off-label use was defined as use in restenotic lesions, lesions in a bypass graft, left main coronary artery disease, or ostial, bifurcated, or totally occluded lesions, as well as use in patients with a reference-vessel diameter of less than 2.5 mm or greater than 3.75 mm or a lesion length of more than 30 mm. RESULTS: Off-label use occurred in 54.7% of all patients with bare-metal stents and 48.7% of patients with drug-eluting stents. As compared with patients with bare-metal stents, patients with drug-eluting stents had a higher prevalence of diabetes, hypertension, renal disease, previous percutaneous coronary intervention and coronary-artery bypass grafting, and multivessel coronary artery disease. One year after intervention, however, there were no significant differences in the adjusted risk of death or myocardial infarction in patients with drug-eluting stents as compared with those with bare-metal stents, whereas the risk of repeat revascularization was significantly lower among patients with drug-eluting stents. CONCLUSIONS: Among patients with off-label indications, the use of drug-eluting stents was not associated with an increased risk of death or myocardial infarction but was associated with a lower rate of repeat revascularization at 1 year, as compared with bare-metal stents. These findings support the use of drug-eluting stents for off-label indications.
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How this classification was reachedexpand
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".