Endovascular Thrombectomy for Stroke Effectiveness Study—An Audit From a Small Tertiary Care Center
Bibliographic record
Abstract
PURPOSE: Endovascular thrombectomy (EVT) treatment for acute ischemic stroke is now recommended as a standard of care. However, implementing EVT in routine clinical practice poses many challenges, even in countries with advanced health-care systems. The aim of the current study is to delineate if EVT at our institution is an effective treatment for acute ischemic stroke. METHODS: All patients who underwent EVT at our institution between December 2011 and July 2017 were retrospectively assessed from our prospective registry. Clinical and imaging (including the Alberta Stroke Program Early CT [ASPECT] score, single-phase computed tomography angiography, and computed tomography perfusion) criteria were utilized to determine EVT suitability. Primary outcomes included modified Rankin score (mRS) at 90 days and recanalization determined by the modified Treatment in Cerebral Infarction score. Effectiveness was assessed by comparing our cohort with patients receiving EVT in the ESCAPE (Endovascular Treatment for Small Core and Proximal Occlusion Ischemic Stroke) trial. RESULTS: Eighty-eight patients presented to our hospital after a median of 87 minutes last seen normal. Of these, median ASPECT score was 9. A majority (72%) also received intravenous alteplase. Successful recanalization (≥TICI 2b) was achieved in 79%. At 90 days, 48% (36/75) were functionally independent (mRS score of 0-2) and 28% (21/75) were disabled (mRS score of 3-5); 24% (18/75) died (mRS of 6) within 90 days. CONCLUSIONS: An audit of our initial experience with EVT for the treatment of acute ischemic stroke in a small tertiary care center yielded similar results compared to the ESCAPE trial, which is encouraging for implementing this treatment in routine clinical practice.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".