Single-Arm Study of Bridging Therapy With Low-Molecular-Weight Heparin for Patients at Risk of Arterial Embolism Who Require Temporary Interruption of Warfarin
Bibliographic record
Abstract
BACKGROUND: When warfarin is interrupted for surgery, low-molecular-weight heparin is often used as bridging therapy. However, this practice has never been evaluated in a large prospective study. This study was designed to assess the efficacy and safety of bridging therapy with low-molecular-weight heparin initiated out of hospital. METHODS AND RESULTS: This was a prospective, multicenter, single-arm cohort study of patients at high risk of arterial embolism (prosthetic valves and atrial fibrillation with a major risk factor). Warfarin was held for 5 days preoperatively. Low-molecular-weight heparin was given 3 days preoperatively and at least 4 days postoperatively. Patients were followed up for 3 months for thromboembolism and bleeding. Eleven Canadian tertiary care academic centers participated; 224 patients were enrolled. Eight patients (3.6%; 95% CI, 1.8 to 6.9) had an episode of thromboembolism, of which 2 (0.9%; 95% CI, 0.2 to 3.2) were judged to be due to cardioembolism. Of these 8 episodes of thromboembolism, 6 occurred in patients who had warfarin deferred or withdrawn because of bleeding. There were 15 episodes of major bleeding (6.7%; 95% CI, 4.1 to 10.8): 8 occurred intraoperatively or early postoperatively before low-molecular-weight heparin was restarted, 5 occurred in the first postoperative week after low-molecular-weight heparin was restarted, and 2 occurred well after low-molecular-weight heparin was stopped. There were no deaths. CONCLUSIONS: Bridging therapy with subcutaneous low-molecular-weight heparin is feasible; however, the optimal approach for the management of patients who require temporary interruption of warfarin to have invasive procedures is uncertain.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".