Abstract 50: Shape of the TPA Time - Benefit Curve: Insights From The National US Get With The Guidelines - Stroke Population
Bibliographic record
Abstract
Background: Randomized trials demonstrated benefit of IV tissue plasminogen activator (tPA) is strongly time-dependent, but were underpowered to specify the shape of the time - benefit curve. Large registries can provide insight into how quickly benefits of tPA decay with time. Methods: We analyzed the relationship between onset to treatment (OTT) and 4 outcomes, discharge to home, discharge free of disability (mRS 0-1), discharge ambulatory status, and mortality, in acute ischemic stroke patients treated with tPA within 4.5h in 1456 GWTG-Stroke hospitals from Jan 2009 to Sept 2013. Results: Among the 65,384 tPA-treated patients, median age was 72, 50.5% were female, median OTT was 141 mins (IQR 110-173), and 11.3% (7368) had OTT 0-90m, 71.1% (46,457) had OTT 91-180m, and 17.6% (11,559) had OTT 181-270m. A slight curvilinear relationship was observed between OTT and discharge to home and discharge free of disability, with inflection at 150 minutes (Figure). Discharge free of disability showed rapid decline between 15-150m (11 fewer patients per 1000 treated per 15m delay) and slower decline from 151-270m (5 fewer per 1000 treated per 15m delay). In contrast, a linear relationship with OTT throughout the 15-270 minute window was observed for independent ambulation at discharge (8 fewer per 1000 treated per 15m delay) and in-hospital mortality (2 fewer per 1000 treated per 15m delay). Considering all mRS disability scale transitions, benefit declined more rapidly in the first and second hours (25 and 33 worse outcomes per 1000 treated per 15m delay) compared to 3-4.5 hours (11 worse outcomes per 1000 treated per 15m delay). Conclusions: Rates of excellent, disability-free outcome and of discharge to home after IV tPA decay more rapidly in the first 2.5 hours after stroke onset, while independent ambulation and mortality decline in a linear fashion throughout the 4.5 hour window. Speedier start of tPA treatment within the first 2.5 hours after onset maximizes treatment benefit.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".