Intravenous Thrombolysis in Patients on Direct Oral Anticoagulants: Analysis of the Get With The Guidelines Stroke Registry
Bibliographic record
Abstract
BACKGROUND: Intravenous thrombolysis for acute ischemic stroke (AIS) is a proven effective treatment. Whether thrombolysis in patients with AIS with recent direct oral anticoagulant (DOAC) use is safe and efficacious is not well established. We aimed to compare outcomes of patients with AIS and recent DOAC use who received thrombolysis to those otherwise eligible but excluded due to recent DOAC use. METHODS: This study included patients for the GWTG (Get With The Guidelines) registry with a diagnosis of AIS within 4.5 hours from last known normal, on a DOAC, and either (1) received intravenous thrombolysis, or (2) were excluded from thrombolysis with coagulopathy being the only reason for exclusion. We used univariate and adjusted binary logistic regression models with clustering by site to compare the 2 groups' functional status (ambulation on discharge and discharge disposition) and reported rates of safety outcomes in the thrombolysis group. RESULTS: The study sample included 48 907 patients with AIS using a DOAC; 4702 received thrombolysis and 44 205 did not. In adjusted logistic regression models, patients with recent DOAC use receiving thrombolysis had increased odds of independent ambulation at discharge (odds ratio [OR], 1.35[ 95% CI, 1.21-1.50]) and home discharge (OR, 1.33 [95% CI, 1.22-1.46]). The rate of symptomatic intracranial hemorrhage with intravenous thrombolysis in patients with recent DOAC use was 3.5% (95% CI, 3.0%-4.1%). CONCLUSIONS: In this study, intravenous thrombolysis was associated with improved functional outcomes in patients with recent DOAC use and appeared safe. Given the study limitations, findings require validation by prospective trials.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".