The Appropriate Use of Dual Antiplatelet Therapy After Coronary Artery Bypass Grafting Surgery
Bibliographic record
Abstract
Dual antiplatelet therapy (DAPT) is a combination of acetylsalicylic acid (ASA) and a P2Y12 inhibitor recommended for patients suffering from an acute coronary syndrome (ACS). Guidelines now recommend the use of ticagrelor – instead of clopidogrel – in combination with ASA to treat ACS patients, regardless of management strategy. Unfortunately, at a rate of approximately 80%, clopidogrel remains the most commonly prescribed P2Y12 inhibitor across Canada, while ticagrelor lags far behind at only 9%. More specifically, while cardiac surgeons appropriately stop DAPT pre-operatively to reduce risk of bleeding, they remain hesitant to resume the regimen post-operatively. \nThis thesis comprises five chapters that use the practicing knowledge translation (PKT) framework to address the lack of uptake and guideline adherence around antiplatelet therapy amongst coronary artery bypass grafting (CABG) patients. It demonstrates that DAPT with ASA and ticagrelor is the best regimen to reduce mortality and major adverse cardiovascular events (MACE), and discusses the next steps required – as per the PKT framework – to highlight the gaps in evidence and practice that exist across the province of Ontario. \nChapter 1 is a preface that provides the rationale for this thesis, and how it fits into the PKT framework. \nChapter 2 has been published in the journal Canadian Journal of Cardiology. A review of the current literature is presented, highlighting that although available guidelines recommend DAPT with ASA and ticagrelor for ACS patients undergoing CABG, the evidence for this is limited and generated from small randomized controlled trials (RCTs) with significant heterogeneity or sub-studies of larger RCTs. \nChapter 3 has been accepted for publication in the journal Medicine. A protocol for a systematic review and network meta-analysis is presented, evaluating various antiplatelet regimens for CABG patients. \nChapter 4 will be published as an abstract in the journal Canadian Journal of Cardiology and presented at the Canadian Cardiovascular Congress 2019. The manuscript will be submitted to the journal Journal of the American College of Cardiology. It is a systematic review and network meta-analysis of over 15 511 CABG patients demonstrating the efficacy and safety of DAPT with ASA and ticagrelor in reducing mortality, MACE, and graft obstruction. By performing a network meta-analysis, a narrower confidence in the efficacy and safety estimates of DAPT with ASA and ticagrelor was developed. \nChapter 5 presents the conclusions of my thesis, and the next steps that must be taken as per the PKT framework.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".