Abstract TP314: Current Use of Strategies to Improve Door-to-Needle Times With Tissue Plasminogen Activator in Acute Ischemic Stroke: Findings From the Target: Stroke Phase II Survey
Bibliographic record
Abstract
Background: The benefits of intravenous tissue plasminogen activator (IV tPA) in acute ischemic stroke are time-dependent. The implementation of Target: Stroke Phase I, the first stage of the American Heart Association’s national quality improvement initiative to accelerate door-to-need (DTN) times, was associated with an average 15 minutes reduction in DTN times. To further reduce DTN delays, Target: Stroke Phase II was launched in 2014 and disseminated additional new best practice strategies. Methods: All active Get With The Guidelines-Stroke hospitals (n=1701) were invited to participate in Target: Stroke Phase II and completed an online survey regarding their use of DTN strategies. Hospital respondents reported the use of specific strategies in the 6 months preceding the survey as a binary yes/no or a continuous 0 to 100% of the time scale. Results: A total of 1034 hospitals (61% response rate) completed the survey between Dec 2014 and Apr 2015. The majority of participating hospitals reported routine use of Target: Stroke key practice strategies, although direct transfer to CT scanner, point of care testing, pre-mix of tPA ahead of time, tPA stored in Emergency Department (ED), or initiation of tPA bolus in the imaging suite were used less frequently (Table). Brain imaging located within the ED was reported by 44% of hospitals and 78% had access to an in-house stroke expert 24/7. Among those who did not have stroke expertise at all times, a majority of hospitals used telestroke systems for imaging interpretation (78%) or clinical evaluation (58%). Conclusions: GWTG-Stroke hospitals reported moderate to extensive use of most Target: Stroke key practice strategies to evaluate acute stroke cases for tPA eligibility and reduce DTN times. Nevertheless, use of point of care testing, pre-mixing of tPA, ED storage of tPA, initiation of tPA in the imaging suite, and direct transfer to CT scanner remained low, representing potential targets for additional improvements.
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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 | 0.016 |
| 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 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".