Abstract WP247: Facilitating Pre-hospital Communication between Neurology and Witness Reduces IV Alteplase Initiation Times
Bibliographic record
Abstract
Introduction: American Stroke Association guidelines recommend pre-hospital stroke code notification via EMS to facilitate prompt treatment decision for acute ischemic stroke (AIS) patients. Despite pre-notification to the stroke team, treatment decisions are often delayed until medical history and last known well times are established. Hypothesis: We hypothesized that screening for IV Alteplase candidacy and obtaining pertinent medical history from a witness or patient during a pre-hospital stroke code activation prior to hospital arrival would decrease door to needle (DTN) times. Methods: A retrospective analysis was conducted on 193 patients presenting to the emergency department (ED) at a Comprehensive Stroke Center (CSC) from February 2016 through July 2016. A process improvement (PI) event was initiated between the CSC and two fire stations with a catchment time of > 10 minutes. For pre-hospital activated stroke codes, the witness or patient was provided the contact card and encouraged to call the centralized number to the Neurologist. Inclusion criteria: All patients presenting to the ED with EMS pre-hospital stroke code activation. Exclusion criteria: Patients presenting to the ED with stroke code initiated after arrival, or medic response events which did not lead to a pre-hospital stroke code activation. Results: After applying criteria, 126 met inclusion and exclusion criteria. A total of 19 patients arrived via the 2 fire stations with pre-hospital stroke code initiations and serve as our intervention group, while 107 patients underwent standard of care. Contact cards were provided to 11 patients (58%) in the intervention group prior to arrival. IV Alteplase was initiated for 3 of 11 patients (27.3%) in the intervention group vs. 19 of 107 patients (17.8%) in the standard of care group. Mean and median DTN times in the intervention group was 36 minutes as compared to a mean of 46.1 minutes and median time of 40 minutes receiving standard of care. Conclusions: Preliminary data suggest that DTN times can be decreased when medical history is obtained prior to hospital arrival to screen for IV Alteplase eligibility. This study warrants further investigation in pre-acquisition of history for pre-hospital stroke code patients.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".