Oral anticoagulation in patients with left ventricular thrombus: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Direct oral anticoagulants (DOACs) are increasingly used off-label to treat patients with left ventricular thrombus (LVT). We analysed available meta-data comparing DOACs and vitamin K antagonists (VKAs) for efficacy and safety. METHODS: We conducted a systematic search and meta-analysis of observational and randomized data comparing DOACs vs. VKAs in patients with LVT. Endpoints of interest were stroke or systemic embolism, thrombus resolution, all-cause death, and a composite bleeding endpoint. Estimates were pooled using a random-effects model meta-analysis, and their robustness was investigated using sensitivity and influential analyses. RESULTS: We identified 22 articles (18 observational studies, 4 small randomized clinical trials) reporting on a total of 3587 patients (2489 VKA vs. 1098 DOAC therapy). The pooled estimates for stroke or systemic embolism [odds ratio (OR): 0.81; 95% confidence interval (CI): 0.57, 1.15] and thrombus resolution (OR: 1.12; 95% CI: 0.86, 1.46) were comparable, and there was low heterogeneity overall across the included studies. The use of DOACs was associated with lower odds of all-cause death (OR: 0.65; 95% CI: 0.46, 0.92) and a composite bleeding endpoint (OR: 0.67; 95% CI: 0.47, 0.97). A risk of bias was evident particularly for observational reports, with some publication bias suggested in funnel plots. CONCLUSION: In this comprehensive analysis of mainly observational data, the use of DOACs was not associated with a significant difference in stroke or systemic embolism, or thrombus resolution, compared with VKA therapy. The use of DOACs was associated with a lower rate of all-cause death and fewer bleeding events. Adequately sized randomized clinical trials are needed to confirm these findings, which could allow a wider adoption of DOACs in patients with LVT.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.016 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".