Femoral vascular closure device use, bivalirudin anticoagulation, and bleeding after primary angioplasty for STEMI: Results from the <scp>HORIZONS</scp>‐<scp>AMI</scp> trial
Bibliographic record
Abstract
OBJECTIVE: To assess the relationship of femoral vascular closure device (VCD) use to bleeding and ischemic events in patients undergoing primary percutaneous coronary intervention (PCI) for ST-segment elevation myocardial infarction (STEMI) via different anticoagulation strategies. BACKGROUND: It is unknown whether femoral VCD reduce major bleeding after primary PCI for STEMI using bivalirudin anticoagulation. METHODS: We compared VCD-treated patients with propensity-matched controls in the HORIZONS-AMI trial with respect to net adverse clinical events (NACE), defined as the composite of major bleeding unrelated to coronary artery bypass graft surgery (CABG) and major adverse cardiac events (comprised of death, reinfarction, ischemia-driven target vessel revascularization, and stroke), at 30 days and 1 year. RESULTS: Among 3,602 patients enrolled in HORIZONS-AMI, 2,948 underwent primary PCI via femoral arterial access and 896 (30%) received VCDs, of whom 642 were included in our model along with 642 propensity-matched controls. At 30 days, VCD-treated patients had significantly less NACE (6.7% vs. 10.8%, HR: 0.61, 95% CI: 0.42-0.89, P = 0.009), driven by a lower rate of non-CABG related major bleeding (5.0% vs. 8.1%, HR: 0.61, 95% CI: 0.39-0.94, P = 0.02). Bleeding reduction was maintained at one year and consistent in magnitude regardless of randomization to bivalirudin or unfractionated heparin plus a glycoprotein IIb/IIIa inhibitor (P for interaction = 0.84). CONCLUSION: In patients undergoing transfemoral primary PCI for STEMI, VCD use was associated with significantly lower non-CABG major bleeding irrespective of anticoagulation strategy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".