Thrombolytic Administration for Acute Ischemic Stroke
Bibliographic record
Abstract
Background: The therapeutic benefit of tissue plasminogen activator (tPA) for acute ischemic stroke is provenbut extremely time-dependent. Current guidelines recommend a <60 minute door-to-needle time. We identify here factors affecting door-to-needle time of tPA administration for acute ischemic stroke. Methods: We conducted a retrospective chart review of an emergency department from 2010 to 2013. Inclusion criteria were discharge diagnosis of acute ischemic stroke and tPA administration within 4.5 hours of onset. Exclusion criteria were non-ischemic strokes (transient ischemic attacks, subarachnoid hemorrhage, intracerebral hemorrhage) or those given tPA >4.5 hours. We used a linear regression model to quantify factor influence and compared tPA administration benchmark times to target benchmark times (median + quartiles). Results: Among the 71 ischemic stroke patients included, 38 (54%) received tPA within ≤ 60 minutes. Female sex was associated with a door-to-needle time delay of 13.97 minutes (95% CI 3.412 to 27.111). Median benchmark times did not show evidence of delay in any benchmark in comparison with target benchmark times. Conclusion: Female sex was associated with increased door-to-needle time. Further investigation of these areas may enable optimized workflow, decreased door-to-needle times, and improved patient outcomes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".