Periprocedural Heparin Bridging in Patients Receiving Vitamin K Antagonists
Bibliographic record
Abstract
BACKGROUND: Periprocedural bridging with unfractionated heparin or low-molecular-weight heparin aims to reduce the risk of thromboembolic events in patients receiving long-term vitamin K antagonists. Optimal periprocedural anticoagulation has not been established. METHODS AND RESULTS: MEDLINE, EMBASE, and Cochrane databases (2001-2010) were searched for English-language studies including patients receiving heparin bridging during interruption of vitamin K antagonists for elective procedures. Data were independently collected by 2 investigators (κ=0.90). The final review included 34 studies with 1 randomized trial. Thromboembolic events occurred in 73 of 7118 bridged patients (pooled incidence, 0.9%; 95% confidence interval [CI], 0.0.0-3.4) and 32 of 5160 nonbridged patients (pooled incidence, 0.6%; 95% CI, 0.0-1.2). There was no difference in the risk of thromboembolic events in 8 studies comparing bridged and nonbridged groups (odds ratio, 0.80; 95% CI, 0.42-1.54). Bridging was associated with an increased risk of overall bleeding in 13 studies (odds ratio, 5.40; 95% CI, 3.00-9.74) and major bleeding in 5 studies (odds ratio, 3.60; 95% CI, 1.52-8.50) comparing bridged and nonbridged patients. There was no difference in thromboembolic events (odds ratio, 0.30; 95% CI, 0.04-2.09) but an increased risk of overall bleeding (odds ratio, 2.28; 95% CI, 1.27-4.08) with full versus prophylactic/intermediate-dose low-molecular-weight heparin bridging. Low-thromboembolic-risk and/or non-vitamin K antagonist patient groups were used for comparison. Study quality was poor with heterogeneity for some analyses. CONCLUSIONS: Vitamin K antagonist-treated patients receiving periprocedural heparin bridging appear to be at increased risk of overall and major bleeding and at similar risk of thromboembolic events compared to nonbridged patients. Randomized trials are needed to define the role of periprocedural heparin bridging.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".