Early Dabigatran Treatment After Transient Ischemic Attack and Minor Ischemic Stroke Does Not Result in Hemorrhagic Transformation
Bibliographic record
Abstract
OBJECTIVES: The optimal timing of anticoagulation after ischemic stroke in atrial fibrillation (AF) patients is unknown. Our aim was to demonstrate the feasibility and safety of initiating dabigatran therapy within 14 days of transient ischemic attack (TIA) or minor stroke in AF patients. PATIENTS AND METHODS: A prospective, multi-center registry (NCT02415855) in patients with AF treated with dabigatran within 14 days of acute ischemic stroke/TIA (National Institutes of Health Stroke Scale (NIHSS) ≤ 3) onset. Baseline and follow-up computed tomography (CT) scans were assessed for hemorrhagic transformation (HT) and graded by using European Cooperative Acute Stroke Study criteria. RESULTS: One hundred and one patients, with a mean age of 72.4 ± 11.5 years, were enrolled. Median infarct volume was 0 ml. Median time from index event onset to dabigatran initiation was 2 days, and median baseline NIHSS was 1. Pre-treatment HT was present in seven patients. No patients developed symptomatic HT. On the day 7 CT scan, HT was present in six patients (one progressing from baseline hemorrhagic infarction type 1). Infarct volume was a predictor of incident HT (odds ratio = 1.063 [1.020-1.107], p < 0.003). All six (100%) patients with new/progressive HT were functionally independent (modified Rankin Scale (mRS) = 0-2) at 30 days, which was similar to those without HT (90%, p = 0.422). Recurrent ischemic events occurred within 30 days in four patients, two of which were associated with severe disability and death (mRS 5 and 6, respectively). CONCLUSION: Early dabigatran treatment did not precipitate symptomatic HT after minor stroke. Asymptomatic HT was associated with larger baseline infarct volumes. Early recurrent ischemic events may be clinically more important.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".