Abstract 159: Treatment with Intravenous Tissue Plasminogen Activator in the “Golden Hour” in the National US Get With The Guidelines-Stroke Population
Bibliographic record
Abstract
Background: Innovations in prehospital and Emergency Department systems of care increasingly enable IV tissue plasminogen activator (tPA) delivery in the first 60 minutes after onset, a time window not tested in placebo-controlled clinical trials. We sought to characterize efficacy and safety outcomes when tPA is delivered in the “golden hour.” Methods: We analyzed 65,384 acute ischemic stroke patients treated with tPA within 4.5 hours of symptom onset in 1456 hospitals participating in GWTG-Stroke from Jan 2009 to Sept 2013. Multivariable logistic regression modeling was employed to evaluate the independent impact of treatment within 60 minutes of onset on outcome. Results: 878 patients (1.3%) received lytic therapy within 60 minutes of onset, versus 6490 (9.9%) in 61-90m, 46,457 (71.1%) in 91-180m, and 11,559 (17.7%) in 181-270m. Independent patient-level factors associated with treatment in the golden hour were older age (aOR 1.15 per 5 years over age 65), higher NIHSS (aOR, 1.04 per scale point), non-EMS arrival (aOR 1.59), and arrival during on hours (aOR 1.61). Hospital level predictors were higher tPA volume (aOR 1.08 per 5 cases), non-PSC (aOR 1.27), and Western region (aOR 1.38 vs Northeast). Compared with the 61-270m window, treatment within 0-60m was associated with increased independent ambulation at d/c, aOR 1.22 (95% CI 1.03-1.45); discharge to home, aOR 1.25 (1.07-1.45); and being disability-free at d/c, aOR 1.72 (95% CI 1.21-2.46, mRS 0-1). No differences were noted in in-hospital mortality or SICH. Considering all discharge mRS transitions, golden hour treatment showed greatest impact at mRS 0-1 vs 2-6 (Figure). Conclusions: Ischemic stroke treatment with IV tPA in the golden hour is associated with more frequent independent ambulation at discharge, discharge to home, and, especially, being disability free at discharge. These findings support intensive efforts, including Target: Stroke and prehospital thrombolysis, to speed treatment initiation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".