Safety and efficacy of drug‐coated balloon for peripheral artery revascularization—A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: The relative merits of the drug-coated balloon (DCB) versus uncoated balloon (UCB) angioplasty in endovascular intervention for patients with symptomatic lower extremity peripheral arterial disease (PAD) remains controversial. METHODS: Online databases were queried with various combinations of keywords to identify relevant articles. Net adverse events (NAEs) and its components were compared using a random effect model to calculate unadjusted odds ratios (ORs). RESULTS: A total of 26 studies comprising 26,845 patients (UCB: 17,770 and DCB: 9075) were included. On pooled analysis, DCB was associated with significantly lower odds of NAE (OR: 0.47, 95% confidence interval [CI]: 0.36-0.61), vessel restenosis (OR: 0.46, 95% CI: 0.37-0.57), major amputation (OR: 0.68, 95% CI: 0.47-99), need for repeat target lesion (OR: 0.38, 95% CI: 0.31-0.47) and target vessel revascularization (OR: 0.62, 95% CI: 0.47-0.81) compared with UCB. Similarly, the primary patency rate was significantly higher in patients undergoing DCB angioplasty (OR: 1.44, 95% CI: 1.19-1.75), while the odds for all-cause mortality (OR: 0.96, 95% CI: 0.85-1.09) were not significantly different between the two groups. A subgroup analysis based on follow-up duration (6 months vs. 1 vs. 2 years) followed the findings of the pooled analysis with few exceptions. CONCLUSIONS: The use of DCB in lower extremity PAD intervention is associated with higher primary patency, lower restenosis, lower amputation rate, and decreased need for repeat revascularization with similar all-cause mortality as compared to UCB.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.030 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".