Abstract 176: To Stay or to Go? Utilization of a Mobile Interventional Stroke Team Shortens Time to Treatment in Large Vessel Occlusion
Bibliographic record
Abstract
Objective: To compare outcomes of mechanical thrombectomy (MT) in patients with large vessel occlusion (LVO) presenting to a single primary stroke center (PSC). MT was performed either by a mobile interventional stroke team (MIST) on site or after interhospital transfer to a comprehensive stroke center (CSC). Background: MT has become standard of care in acute LVO. A majority of hospitals cannot perform MT on site, requiring patient transfer to a thrombectomy-capable center. Within a metropolitan multihospital health care system, utilization of a MIST shortens time to intervention, potentially leading to better outcomes and decreased cost of care. Methods: We performed a retrospective chart review of all acute LVOs presenting to a PSC in Manhattan, NY, from September 2013 to February 2018. We selected patients who underwent MT on site or after transfer to a CSC. Outcomes were assessed by Thrombolysis in Cerebral Infarction (TICI), National Institutes of Health Stroke Scale (NIHSS), and modified Rankin Scale (mRS) scores at 90 days. Results: MT was performed in 48 patients by one endovascular team; 37 patients for whom all data was available were selected for analysis. 28 MTs were performed on site by a MIST (group 1), and 9 patients were transferred to a CSC for intervention (group 2). Median age was 74.5 and 73 years respectively. In group 1, median NIHSS on presentation was 18 and median Alberta Stroke Program Early CT Score (ASPECTS) was 9, compared to 17 and 10 respectively in group 2. Median door-to-puncture (DTP) time was 144.5 minutes and 233 minutes respectively (p<0.05). In group 1, 82% had baseline mRS 0-2 (functional independence), compared to 36% at 90 days. In group 2, 100% had baseline mRS 0-2, and 22% at 90 days. TICI ≥2B was achieved in 89% in both groups. In group 1, 50% had complete reperfusion (TICI 3), compared to 11% in group 2. Conclusion: DTP times were significantly shorter in patients treated by a MIST. This group also had better reperfusion grades and a higher rate of functional independence, although statistical significance was not reached. Even though our study is limited by a small number of cases, the data indicates that in certain geographic areas, the utilization of a MIST may be associated with better outcomes in patients with stroke due to LVO.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".