Comparison of Systematic Ticagrelor-Based Dual Antiplatelet Therapy to Selective Triple Antithrombotic Therapy for Left Ventricle Dysfunction Following Anterior STEMI
Bibliographic record
Abstract
Antithrombotic management of STEMI patients with apical dysfunction, but without demonstrable thrombus, is controversial. Triple antithrombotic therapy (TATT, defined as the addition of oral anticoagulation to dual antiplatelet therapy, or DAPT) may be associated with increased bleeding, while DAPT alone may not adequately protect against cardio-embolic events. We undertook a dual-center study of anterior STEMI patients treated with primary PCI (pPCI) from 2013 to 2015 and presenting presumed new apical dysfunction. The Centre hospitalier de l'Université de Montréal (CHUM) uses a strategy of selective TATT, whereas the Centre hospitalier universitaire de Sherbrooke (CHUS) has favored ticagrelor-based DAPT for all patients since 2013. The primary composite outcome consisted of death, MI, stroke, revascularization, and BARC 3 to 5 bleeding up to 4-months follow-up. We identified 177 cases (69 CHUM; 108 CHUS). Baseline characteristics were similar and procedural success was high (97%). There was no difference in post-procedure LVEF (39 ± 9% vs 37 ± 9%) or the extent of apical dysfunction. The primary composite outcome occurred in 27% with the selective TATT strategy compared to 19% with ticagrelor-DAPT (p = 0.342). Thus, this retrospective dual-center analysis does not support a strategy of conventional TATT over ticagrelor-based DAPT for patients with apical dysfunction following anterior STEMI treated with pPCI. A pragmatic randomized trial is needed to provide a definitive answer to this clinical conundrum.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".