Short dual antiplatelet therapy duration after percutaneous coronary intervention in high bleeding risk patients: Systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Dual antiplatelet therapy (DAPT) following percutaneous coronary intervention (PCI) reduces major adverse cardiovascular events (MACE) and stent thrombosis. However, DAPT duration is a concern in high bleeding risk (HBR) patients. We evaluated the effect of short DAPT (1-3 months) compared to standard DAPT (6-12 months) on bleeding and ischemic events in HBR PCI. METHODS: We searched MEDLINE, Embase and CENTRAL up to August 18, 2022. Randomized controlled trials (RCTs) comparing short DAPT (1-3 months) versus standard DAPT in HBR PCI were included. We assessed risk of bias (RoB) using the Cochrane RoB2 tool, and certainty of evidence using GRADE criteria. Outcomes included MACE, all-cause death, stent thrombosis, major bleeding, and the composite of major or clinically-relevant non-major bleeding. We estimated risk ratios (RR) and 95% confidence intervals (CI) using a random-effects model. RESULTS: From 503 articles, we included five RCTs (n = 7,242) at overall low risk of bias with median follow-up of 12-months. Compared to standard DAPT, short DAPT did not increase MACE (RR 1.02, 95% CI 0.84-1.23), all-cause death (RR 0.92, 95% CI 0.71-1.20) or stent thrombosis (RR 1.47, 95% CI 0.73-2.93). Short DAPT reduced major bleeding (RR 0.34, 95% CI 0.13-0.90) and the composite of major or clinically-relevant non-major bleeding (RR 0.60, 95% CI 0.44-0.81), translating to 21 and 34 fewer events, respectively, per 1000 patients. CONCLUSIONS: In HBR PCI, DAPT for 1-3 months compared to 6-12 months reduced clinically-relevant bleeding events without jeopardizing ischemic risk. Short DAPT should be considered in HBR patients receiving PCI.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.028 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".