Optimal duration of dual antiplatelet therapy following percutaneous coronary intervention: protocol for an umbrella review
Bibliographic record
Abstract
INTRODUCTION: Although dual antiplatelet therapy (DAPT) is routinely given to patients after percutaneous coronary intervention (PCI) with stenting, the optimal duration is unknown. Recent evidence indicates there may be benefits in extending the duration beyond 12 months but such decisions may increase the risk of bleeding. Our objective is to provide a comprehensive overview of the literature for clinicians and policymakers via an umbrella review assessing the optimal duration of DAPT. METHODS AND ANALYSIS: We will perform a comprehensive search of the published and grey literature for systematic reviews involving randomised controlled trials (RCTs) assessing the optimal duration of DAPT following PCI with stenting. The intervention of interest is extended DAPT (beyond 12 months) compared with short-term DAPT (6-12 months). Studies will be selected for inclusion by two reviewers, and the quality will be assessed. The primary outcomes of interest are all-cause mortality and cardiovascular mortality. Secondary outcomes will be bleeding (major, minor and gastrointestinal), urgent target vessel revascularisation, major adverse cardiovascular events, myocardial infarction, stroke and stent thrombosis. Outcomes will be assessed while on DAPT and after withdrawal of DAPT. Data will be summarised with respect to the number of included RCTs, number of participants, effect estimates and heterogeneity. Data will be reported separately based on patient demographics, procedural parameters (eg, stent types, lesion complexity and concurrent disease) and clinical presentation (eg, acute coronary syndromes, infarct type). ETHICS AND DISSEMINATION: Our umbrella review aims to provide a comprehensive overview of the benefits and harms associated with extending DAPT beyond 12 months following PCI with stenting. The results of this review will inform clinical and policy decisions regarding the optimal treatment duration and reimbursement of DAPT following PCI with stenting. Results will be disseminated through a peer-reviewed publication and conference presentations. Ethics approval is not required for this study. TRIAL REGISTRATION NUMBER: CRD42016047735.
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 | 0.121 | 0.162 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.016 | 0.021 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.055 | 0.011 |
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".