Combining Intravenous Thrombolysis and Dual Antiplatelet Treatment in Patients With Minor Ischemic Stroke: A Propensity Matched Analysis of the READAPT Study Cohort
Bibliographic record
Abstract
Background The optimal treatment for acute minor ischemic stroke is still undefined. and options include dual antiplatelet treatment (DAPT), intravenous thrombolysis (IVT), or their combination. We aimed to investigate benefits and risks of combining IVT and DAPT versus DAPT alone in patients with MIS. Methods and Results This is a prespecified propensity score‐matched analysis from a prospective multicentric real‐world study (READAPT [Real‐Life Study on Short‐Term Dual Antiplatelet Treatment in Patients With Ischemic Stroke or Transient Ischemic Attack]). We included patients with MIS (National Institutes of Health Stroke Scale score at admission ≤5), without prestroke disability (modified Rankin scale [mRS] score ≤2). The primary outcomes were 90‐day mRS score of 0 to 2 and ordinal mRS distribution. The secondary outcomes included 90‐day risk of stroke and other vascular events and 24‐hour early neurological improvement or deterioration (≥2‐point National Institutes of Health Stroke Scale score decrease or increase from the baseline, respectively). From 1373 patients with MIS, 240 patients treated with IVT plus DAPT were matched with 427 patients treated with DAPT alone. At 90 days, IVT plus DAPT versus DAPT alone showed similar frequency of mRS 0 to 2 (risk difference, 2.3% [95% CI −2.0% to 6.7%]; P =0.295; risk ratio, 1.03 [95% CI 0.98–1.08]; P =0.312) but more favorable ordinal mRS scores distribution (odds ratio, 0.57 [95% CI 0.41–0.79]; P <0.001). Compared with patients treated with DAPT alone, those combining IVT and DAPT had higher 24‐hour early neurological improvement (risk difference, 20.9% [95% CI 13.1%–28.6%]; risk ratio, 1.59 [95% CI 1.34–1.89]; both P <0.001) and lower 90‐day risk of stroke and other vascular events (hazard ratio, 0.27 [95% CI 0.08–0.90]; P =0.034). There were no differences in safety outcomes. Conclusions According to findings from this observational study, patients with MIS may benefit in terms of better functional outcome and lower risk of recurrent events from combining IVT and DAPT versus DAPT alone without safety concerns. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05476081.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".