Successful Implementation of Endovascular Therapy (Evt) For Acute Ischemic Stroke Without On-Site Neurointerventionalists : Lessons Learned in Building Evt Capacity
Bibliographic record
Abstract
Background: Demand for EVT remains unmet due in part to a lack of neurointerventionalists. We have successfully implemented an EVT program for acute ischemic stroke in an academic centre without on-site neurointerventionalists.Methods: Following a 10 month planning period, EVT was implemented in Kingston General Hospital, in Kingston, Ontario, Canada in a 16 month pilot phase (Monday to Friday 8am to 4pm, May 2 2016 to Sept 28 2017) and then on a 24/7 basis (Sept 29, 2017 to Nov 30 2017). Three general interventional radiologists with a combined experience of 354 supra-aortic procedures over ten years performed EVT, with the option of using real-time mentorship from an academic centre-based neurointerventionalist using telefluoroscopy. Stroke neurologists were present throughout all cases. Patients were selected according to ESCAPE trial criteria. Three month mRS, mortality, and process outcomes were evaluated.Results: Between May 2, 2016 to Nov 30 2017, 25 patients were treated with EVT; 14 during the pilot phase and 11 over the period when EVT was offered 24/7. IV tPA was administered to 14 patients. Stent retriever was deployed successfully in 21 patients. Mean time for CT to groin puncture was 31.3 minutes, puncture to reperfusion 27.7 minutes, and CT to reperfusion 60.1 minutes. Good outcome (mRS 0-2 at 90 days) was seen in 15 patients (60%), and mortality was 24%.Conclusion: EVT was feasible when performed by general interventionalists with appropriate experience in an academic centre. Strict inclusion criteria and strong collaboration with stroke neurologists was essential.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".