Direct Oral Anticoagulants Compared with Vitamin K Antagonists for Left VentricularThrombus: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Direct oral anticoagulants (DOACs) are the guideline-recommended therapy for some hypercoagulable diseases but are used off-label for left ventricular thrombus (LVT) owing to a paucity of evidence. We performed a meta-analysis to assess the safety and efficacy of DOACs compared with vitamin K antagonists (VKAs) for LVT treatment. METHODS: We comprehensively searched PubMed, EMBASE, Cochrane Library, and Web of Science databases for studies that compared DOACs with VKAs for LVT treatment. Outcome indicators included stroke or systemic embolism (SSE), thrombus resolution, bleeding, and death. The Newcastle-Ottawa scale was used to evaluate the quality of included studies. Data were analyzed using Review Manager 5.3, and the meta-analysis is registered at PROSPERO (CRD 42020211376). RESULTS: We included 12 observational studies (n = 2262 patients). SSE was similar for DOACs and VKAs groups (odds ratio (OR) = 1.01, 95% confidence interval (CI) 0.66-1.54, P = 0.95). For thrombus resolution, DOACs were not significantly different to VKAs (OR = 1.15, 95% CI 0.54-2.45, P = 0.71). DOACs and VKAs had a similar bleeding risk (OR = 0.78, 95% CI 0.45-1.35, P = 0.37). DOACs and VKAs groups had a comparable mortality (OR = 0.91, 95% CI 0.50-1.65, P = 0.76). Subgroup analysis showed that post-acute myocardial infarction (AMI) patients using DOACs had a lower risk of SSE (OR = 0.24, 95% CI 0.07-0.87, P = 0.03) and bleeding (OR = 0.38, 95% CI 0.18-0.81, P = 0.01). CONCLUSION: DOACs and VKAs showed no difference in the safety and efficacy of patients with LVT. DOACs might be superior to VKAs for LVT treatment in post-AMI patients.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.045 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".