Is long-term anticoagulation after acute thromboembolic limb ischemia always necessary?
Bibliographic record
Abstract
OBJECTIVE: After thromboembolectomy, patients with acute limb ischemia often receive anticoagulant therapy to prevent recurrent events. Patients with atrial fibrillation or cardiac thrombus have a higher risk of recurrent emboli than those without these risk factors. This study examines the importance of long-term anticoagulation in these 2 groups. DESIGN: A review of patients presenting with acute limb ischemia over a 5-year period (1994-1999). SETTING: A university-affiliated medical centre. PATIENTS: Fifty patients divided into 2 groups: 19 (38%) patients with atrial fibrillation (group 1) and 31 (62%) patients with no atrial fibrillation or cardiac thrombus (group 2) as confirmed by transthoracic echocardiography. INTERVENTION: All patients underwent surgical thromboembolectomy and received postoperative anticoagulant therapy. OUTCOME MEASURES: Mortality, limb loss, further thromboembolic events and bleeding complications as determined by telephone survey. RESULTS: There was a significant difference in 5-year survival (group 1, 84%; group 2, 64%) and early limb loss (group 1, 0%; group 2, 13%). Further thromboembolic events and bleeding complications were rare but were more common in group 1. In group 2 there were no instances of recurrent thromboemboli and no bleeding complications although only 39% of patients in this group were taking angicoagulants at the end of the study period. CONCLUSIONS: Patients with extremity thromboemboli without atrial fibrillation or cardiac thrombus may not be at the same risk for recurrent events as those with these risk factors, and long-term anticoagulant therapy may not be as necessary in this group.
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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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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".