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 Of these 8 episodes of thromboembolism, 6 occurred in patients who had warfarin deferred or withdrawn because of bleeding.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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".