Emergency Medical Service Hospital Prenotification Is Associated With Improved Evaluation and Treatment of Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND: The benefits of intravenous tissue-plasminogen activator (tPA) in acute ischemic stroke are time-dependent. Emergency medical services (EMS) hospital prenotification of an incoming patient with potential stroke may provide a means of reducing evaluation and treatment times and improving treatment rates; yet, available data are limited. METHODS AND RESULTS: We examined 371 988 patients with acute ischemic stroke transported by EMS and enrolled in Get With The Guidelines-Stroke from April 1, 2003, to March 31, 2011. Prenotification occurred in 249 197 (67.0%) of EMS-transported patients. Among eligible patients arriving by 2 hours, patients with EMS prenotification were more likely to be treated with tPA within 3 hours (82.8% versus 79.2%, absolute difference +3.5%, P<0.0001, the National Institutes of Health Stroke Scale-documented cohort; 73.0% versus 64.0%, absolute difference +9.0%, P<0.0001, overall cohort). Patients with EMS prenotification had shorter door-to-imaging times (26 minutes versus 31 minutes, P<0.0001), shorter door-to-needle times (78 minutes versus 80 minutes, P<0.0001), and shorter symptom onset-to-needle times (141 minutes versus 145 minutes, P<0.0001). In multivariable and modified Poisson regression analyses accounting for the clustering of patients within hospitals, use of EMS prenotification was independently associated with greater likelihood of door-to-imaging times ≤25 minutes, door-to-needle times for tPA ≤60 minutes, onset-to-needle times ≤120 minutes, and tPA use within 3 hours. CONCLUSIONS: EMS hospital prenotification is associated with improved evaluation, timelier stroke treatment, and more eligible patients treated with tPA. These results support the need for initiatives targeted at increasing EMS prenotification rates as a mechanism from improving quality of care and outcomes in stroke.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".