The Impact of Antithrombotic Regimens on Clinical Outcomes After Endovascular Intervention and Bypass Surgery for Infrapopliteal Artery Disease
Bibliographic record
Abstract
Endovascular intervention and bypass surgery are the main options of treatments for infrapopliteal artery disease. Although post-intervention treatment with antiplatelet (AP) and/or anticoagulant (AC) drugs has reduced morbidity and mortality rates from cardiovascular complications; the ideal antithrombotic treatment regimen is unknown. The aim of this review was to compare the efficacy and safety of various anticoagulation and/or AP therapy regimens in patients undergoing below-knee endovascular treatment for infrapopliteal artery disease. We reviewed published literature in PubMed and Google Scholar, and Cochrane, evaluating efficacy and safety outcomes after antithrombotic treatment following endovascular intervention or bypass surgery in patients with infrapopliteal artery disease. We extracted relevant efficacy and safety data with related statistics from each study. We found that AP treatment should be administered to patients receiving endovascular therapy or bypass. We did not find superior effects for dual AP treatment (DAPT) over mono-AP therapy (MAPT) for endovascular intervention or bypass surgery with venous graft, suggesting that MAPT suffices for these groups. Also, aspirin + clopidogrel was effective over aspirin alone for prosthetic, but not venous graft, albeit higher non-severe bleeding incidences, suggesting a potential benefit of this regime for below-knee prosthetic graft. AP + AC yielded superior results compared to AP following endovascular procedure and bypass surgery, suggesting the potential benefit of this regime in the absence of contraindications. More prospective studies with large number of patients are warranted to identify the best treatment for infrapopliteal artery diseases.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".