Risk of pocket hematoma in patients on chronic anticoagulation with warfarin undergoing electrophysiological device implantation: a comparison of different peri-operative management strategies.
Bibliographic record
Abstract
OBJECTIVE: Periprocedural management of warfarin remains challenging in patients requiring electrophysiological device surgery. For patients at high risk of thromboembolic events, guidelines recommend bridging therapy with heparin; however, this strategy is associated with a high risk of pocket hematoma. This paper systematically reviews studies appraising the risk of pocket hematoma with different perioperative anticoagulation strategies. METHODS: All relevant studies identified in MEDLINE/PubMed, The Cochrane Collaboration CENTRAL, clinicaltrials.org and in bibliographies of key articles. Estimates were combined using a fixed effects model. Heterogeneity was assessed by p values of χ2 statistics and I2. Publication bias was assessed by visual examination of funnel plots and by Egger test. Fifteen studies enrolling 5911 patients met all inclusion criteria and were included in this review. RESULTS: Heparin bridging compared with no heparin was associated with increased risk of pocket hematoma (OR = 4.47, 95% CI 3.21-6.23, p < 0.00001), and prolonged hospital stay (9.13 ± 1.9 days vs. 5.11 ± 1 .39 days, p < 0.00001). Warfarin continuation was not associated with increased pocket hematoma compared to warfarin discontinuation (p = 0.38), but was associated with reduced risk of pocket hematoma compared with heparin bridging (OR = 0.37, 95% CI 0.2-0.69, p = 0.002). Thromboembolic complications were reduced with heparin bridging vs. no heparin (0.50% vs.1.07%, p = 0.02), and no significant differences were reported between heparin bridging vs. warfarin continuation (p = 0.83). CONCLUSIONS: Heparin bridging is associated with a higher risk of pocket hematoma and a prolonged hospital stay. Perioperative continuation of warfarin reduces the occurrence of pocket hematoma compared with heparin bridging without any significant differences in thromboembolic complications.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".