Prolonged Infusion of Eptifibatide as Bridge Therapy Between Bare‐Metal Stent Insertion and Cardiovascular Surgery: Case Report and Review of the Literature
Bibliographic record
Abstract
Dual antiplatelet therapy with aspirin and clopidogrel is the standard of care after coronary artery stent insertion. Clopidogrel, however, has been associated with an increased risk of bleeding if it is used before coronary artery bypass grafting (CABG), and current guidelines recommend that it be discontinued at least 5 days before surgery. Compared with dual antiplatelet therapy, single antiplatelet therapy or the combination of an antiplatelet agent and an anticoagulant is associated with an increased risk of subacute stent thrombosis. Management of patients who require semiurgent CABG after stent insertion presents a clinical challenge. Intravenous glycoprotein IIb-IIIa inhibitors provide antiplatelet coverage with a shorter duration of action; thus, in theory, they may be useful for these clinical situations. We describe a 47-year-old man who came to the emergency department with sudden-onset, retrosternal chest pain. An electrocardiogram confirmed a diagnosis of ST-segment elevation myocardial infarction. The patient underwent angioplasty and received a bare-metal stent. Because significant disease was revealed in other arteries, CABG was scheduled. Clopidogrel was discontinued in preparation for surgery, and the patient received an infusion of eptifibatide 2 microg/kg/minute as bridging therapy to surgery for a total of 9 days. No major hemorrhagic or clinically evident thrombotic complications occurred before or after the surgery. Eptifibatide may be safe and effective as bridging therapy for patients with intracoronary stents who require CABG.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".