Initial hospital management of patients with emergent large vessel occlusion (ELVO): report of the standards and guidelines committee of the Society of NeuroInterventional Surgery
Bibliographic record
Abstract
OBJECTIVE: To summarize the current literature regarding the initial hospital management of patients with acute ischemic stroke (AIS) secondary to emergent large vessel occlusion (ELVO), and to offer recommendations designed to decrease the time to endovascular treatment (EVT) for appropriately selected patients with stroke. METHODS: Using guidelines for evidenced-based medicine proposed by the Stroke Council of the American Heart Association, a critical review of all available medical literature supporting best initial medical management of patients with AIS secondary to ELVO was performed. The purpose was to identify processes of care that most expeditiously determine the eligibility of a patient with an acute stroke for interventions including intravenous fibrinolysis with recombinant tissue plasminogen activator (IV tPA) and EVT using mechanical embolectomy. RESULTS: This review identifies four elements that are required to achieve timely revascularization in ELVO. (1) In addition to non-contrast CT (NCCT) brain scan, CT angiography should be performed in all patients who meet an institutional threshold for clinical stroke severity. The use of any advanced imaging beyond NCCT should not delay the administration of IV tPA in eligible patients. (2) Activation of the neurointerventional team should occur as soon as possible, based on either confirmation of large vessel occlusion or a prespecified clinical severity threshold. (3) Additional imaging techniques, particularly those intended to physiologically select patients for EVT (CT perfusion and diffusion-perfusion mismatch imaging), may provide additional value, but should not delay EVT. (4) Routine use of general anesthesia during EVT procedures, should be avoided if possible. These workflow recommendations apply to both primary and comprehensive stroke centers and should be tailored to meet the needs of individual institutions. CONCLUSIONS: Patients with ELVO are at risk for severe neurologic morbidity and mortality. To achieve the best possible clinical outcomes stroke centers must optimize their triage strategies. Strategies that provide patients with ELVO with the fastest access to reperfusion depend upon detail-oriented process improvement.
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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 | 0.032 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".