Use of Strategies to Improve Door-to-Needle Times With Tissue-Type Plasminogen Activator in Acute Ischemic Stroke in Clinical Practice
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Bibliographic record
Abstract
BACKGROUND: The implementation of Target: Stroke Phase I, the first stage of the American Heart Association's national quality improvement initiative to accelerate door-to-needle (DTN) times, was associated with an average 15-minute reduction in DTN times. TARGET: Stroke phase II was launched in April 2014 with a goal of promoting further reduction in treatment times for tissue-type plasminogen activator (tPA) administration. METHODS AND RESULTS: We conducted a second survey of Get With The Guidelines-Stroke hospitals regarding strategies used to reduce delays after Target: Stroke and quantify their association with DTN times. A total of 16 901 ischemic stroke patients were treated with intravenous tPA within 4.5 hours of symptom onset from 888 surveyed hospitals between June 2014 and April 2015. The patient-level median DTN time was 56 minutes (interquartile range, 42-75), with 59.3% of patients receiving intravenous tPA within 60 minutes and 30.4% within 45 minutes after hospital arrival. Most hospitals reported routinely using a majority of Target: Stroke key practice strategies, although direct transport of patients to computed tomographic/magenetic resonance imaging scanner, premix of tPA ahead of time, initiation of tPA in brain imaging suite, and prompt data feedback to emergency medical services providers were used less frequently. Overall, we identified 16 strategies associated with significant reductions in DTN times. Combined, a total of 20 minutes (95% confidence intervals 15-25 minutes) could be saved if all strategies were implemented. CONCLUSIONS: Get With The Guidelines-Stroke hospitals have initiated a majority of Target: Stroke-recommended strategies to reduce DTN times in acute ischemic stroke. Nevertheless, certain strategies were infrequently practiced and represent a potential immediate target for further improvements.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it