Abstract TP240: Safety of Dabigatran in Patients With Acute Minor Non-Cardioembolic Ischemic Stroke or Transient Ischemic Attack and Cerebral Microbleeds: A Post Hoc Analysis of the DATAS-II Randomized Trial
Bibliographic record
Abstract
Introduction: Cerebral microbleeds are reported to predict risk of hemorrhagic transformation (HT) in patients with acute ischemic stroke. We aimed to investigate whether the effect of dabigatran (vs. aspirin) in patients with acute minor non-cardioembolic ischemic stroke/TIA is modified by baseline microbleeds on MRI. Methods: This is a post hoc analysis of the DATAS-II trial that randomized 305 patients with acute minor non-cardioembolic ischemic stroke/TIA to dabigatran (150/110 mg twice daily) or aspirin (81 mg daily) for 30 days. MRIs of patients with T2*-weighted sequences on their baseline scans underwent blinded central adjudication for microbleeds. Results: A total of 251 participants (mean age=66±13 years, 36% women, median [IQR] time from symptom onset to randomization 40 [27-55] hours; mean NIHSS=1.5±1.9) were included in these analyses, of whom 82 (33%) had baseline microbleeds. On 30-day MRI, 6% (n=14) developed HT, and 80% (n=191) achieved mRS 0-1 at 90 days. In multivariable logistic regression analyses, we found no association between microbleeds and HT (adjusted odds ratio [aOR], 0.76; 95% CI, 0.18-3.23) on 30-day MRI or mRS 0-1 at 90 days (aOR, 1.54; 95% CI, 0.70-3.41). The rates of HT and mRS 0-1 in patients with microbleeds were 3% on dabigatran and 4% on aspirin (OR, 0.71; 95% CI, 0.06-8.17), and 74% on dabigatran and 84% on aspirin (OR, 0.54; 95% CI, 0.18-1.64), respectively. The presence, severity, or location of microbleeds did not modify the effect of dabigatran on these outcomes (p-interaction>0.05). Conclusions: Early dabigatran treatment appears safe in patients with acute minor non-cardioembolic ischemic stroke/TIA and hemorrhage-prone cerebral small vessel disease marked by microbleeds on MRI.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".