Global Approach to High Bleeding Risk Patients With Polymer-Free Drug-Coated Coronary Stents
Bibliographic record
Abstract
Background: High bleeding risk (HBR) patients undergoing percutaneous coronary intervention have been widely excluded from randomized device registration trials. The LF study (LEADERS FREE) reported superior outcomes of HBR patients receiving 30-day dual antiplatelet therapy after percutaneous coronary intervention with a polymer-free drug-coated stent (DCS). LFII was designed to assess the reproducibility and generalizability of the benefits of DCS observed in LF to inform the US Food and Drug Administration in a device registration decision. Methods: LFII was a single-arm study using HBR inclusion/exclusion criteria and 30-day dual antiplatelet therapy after percutaneous coronary intervention with DCS, identical to LF. The 365-day rates of the primary effectiveness (clinically indicated target lesion revascularization) and safety (composite cardiac death and myocardial infarction) end points were reported using a propensity-stratified analysis compared with the LF bare metal stent arm patients as controls. Results: A total of 1203 LFII patients were enrolled with an average 1.7 HBR criteria per patient, including 60.7% >75 years of age, 34.1% on anticoagulants, and 14.7% with renal failure. Propensity-adjusted 365-day clinically indicated target lesion revascularization was significantly lower with DCS (7.2% versus 9.2%; hazard ratio, 0.72 [95% CI, 0.52–0.98]; P =0.0338 for superiority), as was the primary safety (cardiac death and myocardial infarction) composite (9.3% versus 12.4%; hazard ratio, 0.72 [95% CI, 0.55–0.94]; P =0.0150 for superiority). Stent thrombosis rates were 2.0% DCS and 2.2% bare metal stent. Major bleeding at 1 year occurred in 7.2% DCS patients and 7.2% bare metal stent. Conclusions: LFII reproduces the results of the DCS arm of LF in an independent, predominantly North American cohort of HBR patients.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".