Effect of history of hypertension on efficacy of clopidogrel-aspirin in ischemic stroke
Bibliographic record
Abstract
Background: Patients with different hypertension status could potentially respond differently to the treatment of clopidogrel-aspirin owing to thrombosis, antiplatelet resistance, and platelet reactivity. Aims: The aim of the study is to examine the efficacy and safety of clopidogrel-aspirin in patients with mild ischemic stroke or high-risk transient ischemic attack (TIA) according to different hypertension status. Methods: In the Intensive Statin and Antiplatelet Therapy for Acute High-Risk Intracranial or Extracranial Atherosclerosis (INSPIRES) trial, patients were randomized to either clopidogrel-aspirin or aspirin group. The primary outcome was any new ischemic or hemorrhagic stroke within 90 days. Hypertension status was classified into two categories based on medical history: patients with or without hypertension. Results: Among 6100 patients with complete data of hypertension status, 3915 (64.2%) were men. Clopidogrel-aspirin compared with aspirin was associated with reduced incidence of new stroke in patients without hypertension (hazard ratio (HR): 0.62, 95% confidence interval (CI): 0.44−0.86, p = 0.004), but not in patients with hypertension (HR: 0.87, 95% CI: 0.71−1.07, p = 0.18; p = 0.085 for interaction). Conclusions: In this study, patients without hypertension may have more benefit from receiving treatment with clopidogrel-aspirin than those with hypertension. This finding can be used as an enrichment strategy in the future secondary stroke prevention randomized clinical trials of dual antiplatelet therapy. Trial Registration: The INSPIRES trial was registered at http://www.clinicaltrials.gov (unique identifier: NCT03635749).
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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 | 0.006 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".