Reduction in IV t-PA Door to Needle Times Using an Acute Stroke Triage Pathway
Bibliographic record
Abstract
OBJECTIVE: To determine the effectiveness of an Acute Stroke Triage Pathway in reducing door to needle times in acute stroke treatment with IV t-PA. BACKGROUND: A previous study at our tertiary referral centre, examining IV t-PA door to needle times, was completed in 2000. The median door to needle time was beyond the recommended National Institute for Neurological Disorders and Stroke (NINDS) standard of 60 minutes. In November 2001, an Acute Stroke Triage Pathway was introduced in the emergency room (ER) to address this issue. The goal of this pathway was to rapidly identify patients eligible for treatment for IV t-PA, so that CT scans and lab studies could be arranged immediately upon ER arrival. Our hypothesis was that the Triage Pathway would shorten door to CT and door to needle times. DESIGN/METHODS: Using retrospective data, pre (n=87) and post (n=47) triage pathway times were compared. The door to CT time was reduced by 11 minutes (p=0.015) and door to needle time was reduced by 18 minutes (p=0.0036) in a subgroup of patients that presented directly to our hospital. CONCLUSIONS: These results indicate that the Acute Stroke Triage Pathway is effective in reducing Door to CT and Door to Needle Times in patients presenting directly to our ER. However, a majority of treatment times were still beyond NINDS recommendations. Stroke Centers require periodic review of their efficiency to ensure that target times are being obtained and may benefit from the use of an Acute Stroke Triage Pathway.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".