A Meta-Analysis of 3-Year Outcomes of Drug-Coated Balloons Versus Drug-Eluting Stents for Small-Vessel Coronary Artery Disease
Bibliographic record
Abstract
Background: Drug-coated balloons (DCBs) may be a viable alternative to drug-eluting stents (DES) for de novo small caliber coronary artery lesions. However, there remains a lack of data regarding the long-term efficacy of this approach. Objectives: The purpose of this study was to compare the rates of major adverse cardiovascular events (MACE) after 3-year follow-up among patients randomized to DCB versus DES for the treatment of small caliber coronary arteries with reference vessel diameter between 2 and 3 mm. Methods: We systematically searched MEDLINE, EMBASE, and CENTRAL databases from their inception to July 2023 for randomized controlled trials comparing DCB versus DES for small caliber coronary artery disease. The primary end point was MACE at 3-year follow-up. Risk of bias was assessed using the Cochrane Risk of Bias Tool (RoB 2). Pooled risk ratios (RRs) and 95% CIs were estimated using random effects meta-analytic models. Results: Four randomized controlled trials (n = 1,402) were included. In total, 706 patients were randomized to DCB and 696 to DES. Participants were mostly male (74%), with a mean/median age ranging from 60 to 68 years. Pooled data across trials for MACE showed wide CIs, with little indication of DES superiority over DCB (RR: 0.71; 95% CI: 0.36-1.41). Most individual components of MACE were inconclusive. There was a potential signal for a reduction of target vessel thrombosis with DCB compared to DES (RR: 0.25; 95% CI: 0.06-1.08). Conclusions: Although sample sizes are small, 3-year outcomes suggest that DCB may be a reasonable alternative to DES for the treatment of small coronary arteries.
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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 | 0.022 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.069 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".