Secondary Stroke Prevention: A Population‐Based Cohort Study on Anticoagulation and Antiplatelet Treatments, and the Risk of Death or Recurrence
Bibliographic record
Abstract
Using claims databases of a public healthcare program (Quebec) for the years 2010-2013, we conducted a cohort study of patients with acute ischemic stroke (AIS) to describe secondary prevention treatments and determine how they stood against practice guidelines. We compared the risk of death or AIS recurrence over 1 year in patients treated with anticoagulants, antiplatelets, and/or other cardiovascular drugs. In the month after discharge, 44.3% of the patients did not receive the recommended treatment and > 20% did not have any treatment. Untreated patients were younger, had less comorbidities, and a more severe AIS. Anticoagulants and antiplatelets were associated with a reduced risk of death or recurrence (hazard ratio (HR) 0.27; 95% confidence interval (CI) 0.20-0.36 and HR 0.25; 95% CI 0.16-0.38, respectively) compared with the untreated group. Effect size was similar for the other treatments. Findings confirm treatment benefits shown in clinical trials and emphasize the importance of AIS secondary prevention.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".