Clinical outcomes after multilesion percutaneous coronary intervention: comparison between exclusive and selective use of drug-eluting stents.
Bibliographic record
Abstract
OBJECTIVES: This study compared acute and late outcomes following a strategy of selective drug-eluting stent (DES) use guided by a set of 4 criteria defining higher risk of in-stent restenosis compared to an exclusive DES strategy in 362 patients with multilesion (n = 900) percutaneous coronary interventions. RESULTS: At a mean follow up of 412 +/- 110 days, major adverse cardiac events (death, myocardial infarction, revascularization) were 16.8% in the exclusive DES group compared to 18.4% in the selective DES group (p = 0.78). By univariate analysis, revascularization rates (9.9% in the exclusive DES group versus 10.5% in the selective DES group; p = 1.0) and target lesion revascularization (TLR) rates (5.5% versus 6.2%; p = 0.77) were similar in the 2 groups. By multivariate analysis adjusted by propensity score to account for differences in baseline characteristics, the strategy of exclusive DES use was not associated with lower risks of revascularization (hazard ratio [HR]: 0.91, 95% confidence interval [CI] 0.64-1.29) or TLR (HR: 0.81, 95% CI 0.59-1.08) compared with selective DES use. Using the Academic Research Consortium criteria, stent thrombosis occurred in 6/161 (3.7%) cases in the exclusive DES group and in 1/201 (0.5%) case in the selective DES group (p = 0.03). CONCLUSIONS: In patients with multiple coronary lesions, a selective DES strategy for lesions at higher risk of restenosis and bare-metal stents for other lesions was safe and effective when compared to the exclusive use of DES. A large, prospective, randomized trial is required to validate a criteria-based selective DES strategy compared to systematic DES use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".