Abstract 5986: Drug-Eluting Stent versus Bare Metal Stent Use: Meta-Analysis of Randomized Trials and Observational Studies
Bibliographic record
Abstract
Background: The safety and efficacy of drug-eluting stents (DES) among more generalized patient populations than typically enrolled in pivotal randomized controlled trials (RCTs), including for “off-label” indications, is controversial. Objectives: We sought to perform a systematic review and meta-analysis of published/presented DES studies in order to estimate the relative impact of DES vs. BMS particularly outside of USFDA labeled indications, and to specifically assess differences between data derived from RCTs and observational (Obs) analyses. Methods: Studies with >=100 total pts comparing DES to BMS and reporting mortality data with cumulative follow-up of >=1 year that were published and/or presented through 2/2008 were abstracted. Fixed effects and random effects models were used to generate summary estimates of the relative impact of DES vs. BMS upon all-cause mortality, myocardial infarction (MI), and target vessel revascularization (TVR). Data from 9,470 pts enrolled in 22 RCTs and from 182,901 pts studied in 34 Obs studies were included; RCT and Obs data were analyzed separately. Results: Data from “off-label” RCTs demonstrated non-significant reductions in mortality with DES vs. BMS, with a significant reduction in TVR (Table ). The Obs studies (in which pts were treated for both on-label and off-label indications) demonstrated significant reductions in mortality and TVR with DES vs. BMS use (Table ). Conclusions: Use of DES compared to BMS does not appear to be associated with adverse safety outcomes such as death or MI in either off-label RCTs or non-randomized Obs studies, and was associated with a significant and comparable reduction in TVR. In the absence of definitive large-scale randomized data directly comparing DES to BMS in unselected pts, these findings, derived from more than 190,000 total pts treated in 56 studies, suggest that DES are safe and have comparable efficacy in both RCTs and in the “real-world”.
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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 | 0.044 | 0.082 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.049 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".