Effect of Conscious Sedation vs. General Anesthesia on Outcomes in Patients Undergoing Mechanical Thrombectomy for Acute Ischemic Stroke: A Prospective Randomized Clinical Trial
Bibliographic record
Abstract
Background: Although several studies have compared conscious sedation (CS) with general anesthesia (GA) in patients undergoing mechanical thrombectomy (MT), there has been no affirmative conclusion. We conducted this trial to assess whether CS is superior to GA for patients undergoing MT for acute ischemic stroke (AIS). Methods: AIS patients with anterior circulation large vascular occlusion (LVO) were randomized into two groups. The primary outcome was modified Rankin scale [mRS] score (0–2) at 90d after stroke. Secondary outcomes included intraprocedural hemodynamics, time metrics, successful recanalization, neurointerventionalist satisfaction score, National Institute of Health Stroke Scale (NIHSS) score, and Alberta Stroke Program Early CT Score (ASPECTS) at 48 h post intervention, mortality at discharge and 3 months after stroke, and complications. Results: Compared with the CS group, heart rate was significantly lower at T1–T8 in the GA group except at T4 (P20% fall in MAP, pre-recanalization time spent with >20% fall in MAP, neurointerventionalist satisfaction, successful recanalization rate, NIHSS and ASPECTS scores at 48 h post intervention, and mortality rate at discharge and 3 months after stroke (P>.05). The cerebral infarction rate at 30d was greater in the CS group, but not significantly (P>.05). There were no differences in complication rates except for pneumonia (P>.05). Conversion rate from CS to GA was 9.52%. Conclusion: Anesthetic management with GA or CS during MT had no differential impact on the functional outcomes and mortality at discharge or 3 months after stroke in AIS patients, but CS led to more stable hemodynamics and lower incidence of pneumonia.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".