A propensity score matched comparative study between paclitaxel‐coated balloon and everolimus‐eluting stents for the treatment of small coronary vessels
Bibliographic record
Abstract
OBJECTIVES: To compare the long-term clinical outcomes of paclitaxel drug-coated-balloons (DCB) and everolimus-eluting-stents (EES) following the treatment of de novo small vessel coronary artery disease. BACKGROUND: It is currently unclear whether treatment of de novo small vessel coronary disease with DCB is comparable to second generation drug-eluting stents, which are the current standard of care. METHODS: The present study enrolled 90 patients with small vessel coronary disease from the DCB treatment arm of the BELLO (Balloon Elution and Late Loss Optimization) trial and 2,000 patients treated with EES at the San Raffaele Scientific Institute. Propensity score matching was performed to adjust for differences in baseline clinical and angiographic characteristics, yielding a total of 181 patients: 90 patients with 94 lesions receiving DCB and 91 patients with 94 lesions receiving EES. Major adverse cardiac events (MACE) were defined as the composite of cardiac death, recurrent non-fatal myocardial infarction, and target vessel revascularization. RESULTS: After propensity score matching, baseline clinical and angiographic characteristics were similar between the two groups. The cumulative MACE rate at 1-year was 12.2% with DCB and 15.4% with EES (P = 0.538). Patients in the DCB group had similar TLR rates as compared to EES over the same interval (4.4% vs. 5.6%; P = 0.720). There were no cases of definite or probable stent or vessel thrombosis. CONCLUSIONS: The use of paclitaxel-DCB appears to be associated with similar clinical outcomes when compared to second-generation-EES in small coronary artery disease. The findings of this study should be confirmed with larger prospective randomized studies with longer follow-up. © 2017 Wiley Periodicals, Inc.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".