Dual versus single antiplatelet therapy after transcatheter aortic valve replacement: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Transcatheter aortic valve replacement (TAVR) is the intervention of choice for patients with severe symptomatic aortic stenosis who have high or intermediate surgical risk. TAVR valves are at risk of thrombosis and serious sequelae including stroke, peripheral embolism, and valve dysfunction requiring intervention. The optimal method of antithrombotic therapy to reduce risk of thrombosis with an acceptable increase in risk of bleeding is uncertain. Objectives This systematic review and meta-analysis assesses the effects of dual antiplatelet therapy (DAPT) versus single antiplatelet therapy (SAPT) on mortality, thrombosis and bleeding in patients undergoing TAVR. Methods We systematically searched EMBASE, MEDLINE and CENTRAL from January 1, 2002 until February 9, 2021 for randomized trials comparing DAPT to SAPT after TAVR. Two reviewers independently screened titles and abstracts, and then the full text of potentially relevant articles in duplicate. Data abstraction and risk of bias was also performed in duplicate. Risk ratios and 95% confidence intervals were pooled using the Mantel-Haenzel method and random effects modelling. We assessed the certainty of the evidence for each outcome using the Grading of Recommendations, Assessments, Development and Evaluation (GRADE) approach. Results We included 4 randomized controlled trials of 1086 patients. Risk of bias was low or somewhat concerning for all studies. We found no difference in mortality (risk ratio (RR) 1.02, 95% confidence interval (CI), 0.63 to 1.63) or stroke (RR 1.03, 95% CI 0.57–1.84), but a significant increase in major bleeding (RR 2.04, 95% CI, 1.31–3.19), with DAPT compared to SAPT. There were too few events to conduct meta-analysis for clinical valve thrombosis, subclinical valve thrombosis, transvalvular gradients on echocardiography, or aortic valve reintervention. The certainty of the evidence was low or very low due to risk of bias, inconsistency, and imprecision. Conclusions There is very low certainty evidence that DAPT has little to no effect compared to SAPT on mortality and stroke. There is low certainty evidence that DAPT likely causes more major bleeding than SAPT. Funding Acknowledgement Type of funding sources: None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.034 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".