Use of Intravenous Recombinant Tissue Plasminogen Activator in Patients With Acute Ischemic Stroke Who Take Non–Vitamin K Antagonist Oral Anticoagulants Before Stroke
Bibliographic record
Abstract
Background: Intravenous rt-PA (recombinant tissue-type plasminogen activator) is effective in improving outcomes in ischemic stroke; however, there are few data on the use of rt-PA in patients who are receiving a non–vitamin K antagonist oral anticoagulant (NOAC). Methods: Using data from the American Heart Association Get With The Guidelines-Stroke Registry, we examined the outcomes of use of thrombolytic therapy in patients with ischemic stroke who received anticoagulation with NOACs versus those on warfarin (international normalized ratio <1.7) or not on anticoagulation from 1289 registry hospitals between October 2012 and March 2015. Results: Of 42 887 patients with ischemic stroke treated with intravenous rt-PA within 4.5 hours, 251 were taking NOACs (dabigatran 87, rivaroxaban 129, and apixaban 35) before their stroke, 1500 were taking warfarin, and 41 136 were on neither. Patients on NOACs or warfarin were older, had more comorbid conditions, and experienced more severe strokes than did those who were not on anticoagulation (median National Institutes of Health Stroke Scale 12, 13, and 9, respectively). Unadjusted rates of symptomatic intracranial hemorrhage in the NOAC, warfarin, and none groups were 4.8%, 4.9%, and 3.9%, respectively ( P =0.11). In comparison with those not on anticoagulation, the adjusted odds ratio for symptomatic intracranial hemorrhage for those on NOACs was 0.92 (95% confidence interval, 0.51–1.65) and for those on warfarin the adjusted odds ratio was 0.85 (95% confidence interval, 0.66–1.10). There were also no significant differences in the risk for life-threatening/serious systemic hemorrhage, any rt-PA complication, in-hospital mortality, and modified Rankin Scale at discharge across 3 groups. Similar results were also found after propensity score matching. Conclusions: Although experience of using rt-PA in patients with ischemic stroke on a NOAC is limited, these preliminary observations suggest that rt-PA appears to be reasonably well tolerated without prohibitive risks for adverse events among selected NOAC-treated patients. Future studies should evaluate the safety and efficacy of intravenous rt-PA in patients with ischemic stroke who are taking NOACs.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".