Is General Anesthesia for Endovascular Thrombectomy Helpful or Harmful?
Bibliographic record
Abstract
Endovascular thrombectomy (EVT) has significantly improved outcomes for patients with acute ischemic stroke due to large vessel occlusion. However, despite advances, more than half of patients remain functionally dependent 3 months after their initial stroke. Anesthetic strategy may influence both the technical success of the procedure and overall outcomes. Conventionally, general anesthesia (GA) has been widely used for neuroendovascular procedures, particularly for the distal intracranial circulation, because the complete absence of movement has been considered imperative for procedural success and to minimize complications. In contrast, in patients with acute stroke undergoing EVT, the optimal anesthetic strategy is controversial. Nonrandomized studies suggest GA negatively affects outcomes while the more recent anesthesia-specific RCTs report improved or unchanged outcomes in patients managed with versus without GA, although these findings cannot be generalized to other EVT capable centers due to a number of limitations. Potential explanations for these contrasting results will be addressed in this review including the effect of different anesthetic strategies on cerebral and systemic hemodynamics, revascularization times, and periprocedural complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".