Estimated Impact of Emergency Medical Service Triage of Stroke Patients on Comprehensive Stroke Centers
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The American Stroke Association recommends that Emergency Medical Service bypass acute stroke-ready hospital (ASRH)/primary stroke center (PSC) for comprehensive stroke centers (CSCs) when transporting appropriate stroke patients, if the additional travel time is ≤15 minutes. However, data on additional transport time and the effect on hospital census remain unknown. METHODS: Stroke patients ≥20 years old who were transported from home to an ASRH/PSC or CSC via Emergency Medical Service in 2010 were identified in the Greater Cincinnati area population of 1.3 million. Addresses of all patients' residences and hospitals were geocoded, and estimated travel times were calculated. We estimated the mean differences between the travel time for patients taken to an ASRH/PSC and the theoretical time had they been transported directly to the region's CSC. RESULTS: Of 929 patients with geocoded addresses, 806 were transported via Emergency Medical Service directly to an ASRH/PSC. Mean additional travel time of direct transport to the CSC, compared with transport to an ASRH/PSC, was 7.9±6.8 minutes; 85% would have ≤15 minutes added transport time. Triage of all stroke patients to the CSC would have added 727 patients to the CSC's census in 2010. Limiting triage to the CSC to patients with National Institutes of Health Stroke Scale score of ≥10 within 6 hours of onset would have added 116 patients (2.2 per week) to the CSC's annual census. CONCLUSIONS: Emergency Medical Service triage to CSCs based on stroke severity and symptom duration may be feasible. The impact on stroke systems of care and patient outcomes remains to be determined and requires prospective evaluation.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".