Prior Antithrombotic Use Is Associated With Favorable Mortality and Functional Outcomes in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Antithrombotics are the mainstay of treatment in primary and secondary prevention of stroke, and their use before an acute event may be associated with better outcomes. METHODS: Using data from Get With The Guidelines-Stroke with over half a million acute ischemic strokes recorded between October 2011 and March 2014 (n=540 993) from 1661 hospitals across the United States, we examined the unadjusted and adjusted associations between previous antithrombotic use and clinical outcomes. RESULTS: There were 250 104 (46%) stroke patients not receiving any antithrombotic before stroke; of whom approximately one third had a documented previous vascular indication. After controlling for clinical and hospital factors, patients who were receiving antithrombotics before stroke had better outcomes than those who did not, regardless of whether a previous vascular indication was present or not: adjusted odds ratio (95% confidence intervals) were 0.82 (0.80-0.84) for in-hospital mortality, 1.18 (1.16-1.19) for home as the discharge destination, 1.15 (1.13-1.16) for independent ambulatory status at discharge, and 1.15 (1.12-1.17) for discharge modified Rankin Scale score of 0 or 1. CONCLUSIONS: Previous antithrombotic therapy was independently associated with improved clinical outcomes after acute ischemic stroke. Ensuring the use of antithrombotics in appropriate patient populations may be associated with benefits beyond stroke prevention.
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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 | 0.001 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".