Strokes and Transient Ischemic Attacks Occurrence During Annual Dual Antiplatelet Therapy
Bibliographic record
Abstract
BACKGROUND: The incidence of stroke/TIA during annual dual antiplatelet therapy (ADAPT) for acute coronary syndrome (ACS) remains high. Some evidence suggests that shorter than ADAPT may diminish such risk, still providing adequate vascular protection. However, the precise timing of strokes/TIA occurrences during ADAPT is unclear but may be important for determining optimal preventive treatment duration. STUDY QUESTION: The precise timing of secondary cerebrovascular events over ADAPT. STUDY DESIGN: Access was gained to the FDA-issued Platelet Inhibition and Outcomes (PLATO) trial data set on which post hoc analyses of stroke/TIA timing after ticagrelor and clopidogrel on top of aspirin was explored. MEASURES AND OUTCOMES: Events were counted and plotted over time from day 1 till day 365 after the index ACS event. RESULTS: Among 18,624 enrollees, 252 strokes and 49 TIAs were reported. After the exclusion of entries with missing dates, unclear randomization codes, and events beyond 1-year follow-up, 238 strokes and 45 TIAs were analyzed. Overall, most frequent strokes/TIAs occurred within the first day after qualifying ACS, with the gradual declines after day 7 and day 40 reaching background counts thereafter. The strokes/TIAs patterns did not differ much between P 2 Y12 inhibitors except for twice more events at day 1 and excess exclusions after day 365 in the ticagrelor arm. CONCLUSIONS: Most cerebrovascular events emerged very early after ACS despite ADAPT. This large hypothesis-generating evidence may justify shorter than the ADAPT duration after ACS. Twice more events at day 1 and excess late ticagrelor exclusions in PLATO deserve further scrutiny. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT00391872.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".