Endovascular Treatment in Acute Ischemic Stroke: A Nationwide Survey in Korea
Bibliographic record
Abstract
PURPOSE: As endovascular therapy (EVT) has been approved as a treatment guideline for acute ischemic stroke (AIS), it has been increasing in Korea. We conducted a nationwide survey to evaluate the current status of EVT for patients with AIS in Korea. MATERIALS AND METHODS: An electronic survey was sent to a representative clinician at each hospital where EVT was available in Korea. A Google survey was used to distribute the questionnaires and receive responses from October 2017 to December 2017. RESULTS: Among 120 hospitals in our society, 76 participated in this survey. In 26% of the hospitals, more than 50 annual cases of EVT were performed, and 25-50 annual cases in 37%. Fifty-six hospitals (73.7%) achieved successful recanalization (thrombolysis in cerebral infarction ≥2b) in more than 80% of patients. Computed tomography (CT) angiography was the most common imaging modality for AIS treatment, and magnetic resonance (MR) diffusion, MR-perfusion/diffusion, and perfusion CT were frequently used in order. Non-eligibility criteria for EVT included a National Institutes of Health Stroke Scale <4 (64.5%), the absence of MR perfusion/diffusion mismatch (52.6%), and a low Alberta Stroke Program Early CT Score (42.1%). For anterior circulation stroke, 60% of Korean hospitals adopted a wider time range of "8 hours" from symptom onset, while 70% of hospitals had a time limitation of 12-24 hours for posterior circulation stroke. The most preferred EVT device was a stentriever (89.4%). In the failed cases due to underlying stenosis, 79% of Korean hospitals performed angioplasty or stenting for revascularization. CONCLUSION: This first nationwide survey showed that most Korean hospitals conducted EVT for AIS patients according to the present guideline in the era of mechanical thrombectomy by integrating the clinical experiences of many medical institutions and specialists.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".