Abstract 159: Trends in Dual Antiplatelet Therapy Prescription Patterns for Secondary Prevention in Patients With Noncardioembolic Ischemic Stroke
Bibliographic record
Abstract
Background: The recommendations for dual antiplatelet (DAPT aspirin + clopidogrel) for secondary stroke prevention has evolved over time. Following the publication of CHANCE trial (07/2013), the AHA/ASA updated the DAPT recommendations from Class III harm (10/2010) for patient with noncardioembolic ischemic stroke, to Class IIb benefit ≥ risk (02/2014), and Class IIa benefit >> risk (03/2018) for a subgroup of patients with minor stroke (NIHSS≤3). Subsequent to the last guideline update, the POINT trial (05/2018) provided further support for the effectiveness of DAPT. Methods: We evaluated antiplatelet prescription patterns of 1,024,074 noncardioembolic ischemic stroke survivors (median age 65 years and 46% women) eligible for antiplatelet therapy (no contraindications) and discharged from the Get With The Guidelines-Stroke Hospitals between Q1 2011 and Q1 2019. Results: Baseline patient characteristics were similar within the four periods: pre-CHANCE (01/2011-07/2013), pre-2014 guideline update (08/2013-02/2014), pre-POINT/2018 guideline update (03/2014-05/2018), and post-POINT (06/2018-03/2019). Use of DAPT gradually increased from 16.7% in the pre-CHANCE period, to 19.4% pre-2014 guideline update, 23.3% pre-POINT/2018 guideline update, and 29.8% post-POINT period (p<0.001, Figure). Yet increase in DAPT use was observed over time for individuals with NIHSS≤3 (17.1%, 19.9%, 24.1%, and 31.4%, p<0.001) and those with NIHSS>3 (18.7%, 22.8%, 28.3%, and 28.3%, p<0.001). Conclusions: A sustained increase in DAPT use for secondary stroke prevention was observed after publication of pivotal trials and AHA guideline updates. While recommended for minor strokes or TIA only, such increase was also observed in ischemic stroke patients with NIHSS>3, where the risk-benefit ratio of DAPT remains to be established.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".