P1932Predictors of DAPT use in patients beyond 1 year post myocardial infarction: Insights from the TIGRIS observational study
Bibliographic record
Abstract
Abstract Background International guidelines vary in their recommendations for dual antiplatelet therapy (DAPT) use beyond 1 year post-myocardial infarction (MI). Purpose To identify predictors of DAPT use in patients ≥1 year post-MI prior to the publication of the DAPT score and the 2017 European Society of Cardiology (ESC) guidelines for DAPT in coronary artery disease. Methods TIGRIS (NCT01866904) was a prospective, multi-center (369 centers in 25 countries), observational study of patients 1 to 3 years post-MI between June 2013 and November 2014. We performed a multivariable logistic regression analysis to identify independent predictors of DAPT use at 396 days post-MI (365 + 31 days overrun period to allow intended DAPT discontinuation at 1 year). Patients on oral anticoagulation were excluded. Results Of 8464 patients enrolled (mean age 66 years, women 24%, ST-elevation MI 53%), 40% were on DAPT at 396 days post-MI (Figure). In the subset of patients on DAPT at 396 days post-MI, aspirin was combined with clopidogrel in 84%, prasugrel in 12%, and other antiplatelet agents in 4%. DAPT use at 396 days post-MI was independently associated with geographic region, age, PCI for the index MI, and a history of multivessel disease or angina (Table). Several variables included in the DAPT score and ESC guideline recommendations (diabetes, second prior MI, hypertension, peripheral artery disease, heart failure, smoking, and renal insufficiency) were not independent predictors of DAPT use at 396 days. Independent predictors of DAPT @396 days Variable at enrolment Patients Odds ratio (95% CI) P-value Region: Europe 3813 Reference group 0.01 North America 923 1.65 (0.56, 4.86) Latin America 1084 2.55 (1.19, 5.47) Asia and Australia 2644 3.01 (1.42, 6.36) Age <65 years 3274 1.15 (1.04, 1.28) 0.005 PCI for index MI 6925 2.08 (1.82, 2.38) <0.0001 Multi-vessel disease 5598 1.37 (1.24, 1.52) <0.0001 History of angina 829 1.46 (1.24, 1.71) <0.0001 DAPT use at 396 days post-MI by region Conclusion During the study period, DAPT use ≥1 year post-MI was prevalent and appeared to be influenced by regional practices. Further research is needed to determine whether the DAPT score and the 2017 ESC guidelines for dual antiplatelet therapy have changed long-term DAPT use practices. Acknowledgement/Funding AstraZeneca AB, Södertälje, Sweden
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".