Optimal Antithrombotic Therapy after Implantation of a Transcatheter Aortic Valve: Warfarin, Aspirin, or Non-Vitamin K Antagonist Oral Anticoagulants? A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Abstract Objective: Diverse antithrombotic strategies were applied to patients undergoing aortic valve replacement. However, the optimal therapeutic regimen for patients undergoing transcatheter aortic valve implantation/replacement (TAVI/TAVR) remains unclear. The purpose of this study was to compare the efficacy and safety of various antithrombotic therapies following TAVI/TAVR. Methods: Relevant clinical trials evaluating the effect of anticoagulation or antiplatelet regimens on patients after TAVI/TAVR from inception to September 2020 were identified using the PubMed, EMBASE, and the Cochrane Library databases. The inclusion criteria including (1) all patients underwent TAVI/TAVR; (2) the interventions were antithrombotic strategies that prevent the occurrence of thrombotic events in patients; (3) randomized controlled trials or prospective observational studies; and (4) investigation of at least 1 outcome with a follow-up period of ≥3 months. The exclusion criteria including (1) research content was identical or irrelevant to the purpose of the present study; (2) lack of the required outcome index or availability of fragmentary original information; and (3) the full text is not available. The major outcomes were all-cause mortality, thromboembolic complications, and bleeding events. The Cochrane Collaboration's tool and the Newcastle-Ottawa Scale were used for assessing the risk of bias in included studies. Results: Thirteen studies (3 randomized controlled trials and 10 non-randomized studies) were identified, with a total of 23,497 patients. Four studies compared direct oral anticoagulants (DOACs) with warfarin, 1 study compared aspirin with warfarin, 6 studies compared aspirin plus clopidogrel (dual antiplatelet therapy (DAPT)) with aspirin monotherapy, and 2 studies compared DAPT and aspirin monotherapy with warfarin concurrently. There were no significant differences found between the DOAC and warfarin groups regarding all-cause mortality (risk ratio (RR): 1.03; 95% confidence interval (CI): 0.65–1.64; P = 0.909; P het = 0.105), clinical adverse events (RR: 1.59; 95% CI: 0.99–2.58; P = 0.057; P het = 0.738), or bleeding events (RR: 0.93; 95% CI: 0.78–1.11; P = 0.437; P het = 0.338). The rates of all-cause mortality (RR: 0.71; 95% CI: 0.54–0.93; P = 0.012; P het = 0.845) and bleeding events (RR: 0.43; 95% CI: 0.22–0.83; P = 0.012; P het = 0.569) were lower in the aspirin group versus the warfarin group; however, there was no difference in the rate of clinical adverse events (RR: 0.38; 95% CI: 0.14–1.07; P = 0.068; P het = 0.593). The DAPT group had an advantage versus the aspirin group in all-cause mortality (RR: 0.89; 95% CI: 0.82–0.98; P = 0.013; P het = 0.299); however, the incidence of bleeding events (RR: 2.06; 95% CI: 1.39–3.07; P < 0.001; P het = 0.001) exhibited an increasing trend. Notably, there was a slight decrease in the incidence of clinical adverse events (RR: 1.09; 95% CI: 0.94–1.26; P = 0.268; P het = 0.554). Conclusion: The present meta-analysis integrates the latest published results on antithrombotic strategies in patients after TAVI/TAVR. Aspirin showed a favorable risk-benefit profile versus warfarin, with lower rates of all-cause mortality and bleeding events. Although DAPT was also associated with a significantly lower rate of all-cause mortality, it was linked to a higher incidence of bleeding events. The DOACs did not show significant benefits compared with warfarin. Some certain limitations should be noted, such as different types of trails produce heterogeneity and finite inclusion of TAVI/TAVR patients increased selection bias.
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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 | 0.014 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.030 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".