Ticagrelor use and practice patterns among Canadian cardiac surgeons
Bibliographic record
Abstract
BACKGROUND AND AIM: The P2Y12 platelet receptor inhibitor ticagrelor is widely used in patients following acute coronary syndromes or in those who have received coronary stents. Bentracimab is a monoclonal antibody-based reversal agent that is being formally evaluated in a Phase 3 clinical trial. Here, we probe the knowledge, attitudes, and practice patterns of cardiac surgeons regarding their perioperative management of ticagrelor and potential application of a ticagrelor reversal agent. METHODS: A questionnaire was developed by a working group of cardiac surgeons to inquire into participants' practices and beliefs regarding ticagrelor and disseminated to practicing, Canadian-trained cardiac surgeons. RESULTS: A total of 70 Canadian-trained cardiac surgeons participated. Bleeding risk was identified as the most significant consideration when surgically revascularizing ticagrelor-treated patients (90%). There is variability in the duration of withholding ticagrelor before coronary artery bypass graft procedure in a stable patient; 44.3% wait 3 days and 32.9% wait 4 days or longer. Currently, 15.7% of cardiac surgeons prophylactically give platelet transfusions and fresh frozen plasma intraoperatively following protamine infusion in patients who have recently received ticagrelor. Interestingly, 47.1% of surveyed surgeons were aware of a reversal agent for ticagrelor, 91.4% of cardiac surgeons would consider utilizing a ticagrelor reversal agent if available, and 51.4% acknowledged that the introduction of such an agent would be a major advance in clinical practice. CONCLUSIONS: The present survey identified ticagrelor-related bleeding as a major concern for cardiac surgeons. Surgeons recognized the significant unmet need that a ticagrelor reversal agent would address.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".