Emergency intubation during thrombectomy for acute ischemic stroke in patients under primary procedural sedation
Bibliographic record
Abstract
BACKGROUND: Emergency intubation is an inherent risk of procedural sedation regimens for endovascular treatment (EVT) of acute ischemic stroke. We aimed to characterize the subgroup of patients, who had to be emergently intubated, to identify predictors of the need for intubation and assess their outcomes. METHODS: This is a retrospective analysis of the single-center study KEEP SIMPLEST, which evaluated a new in-house SOP for EVT under primary procedural sedation. We used descriptive statistics and regression models to examine predictors and functional outcome of emergently intubated patients. RESULTS: Twenty of 160 (12.5%) patients were emergently intubated. National Institutes of Health Stroke Scale (NIHSS) on admission, premorbid modified Rankin scale (mRS), Alberta Stroke Program Early CT Score, age and side of occlusion were not associated with need for emergency intubation. Emergency intubation was associated with a lower rate of successful reperfusion (OR, 0.174; 95%-CI, 0.045 to 0.663; p = 0.01). Emergently intubated patients had higher in-house mortality (30% vs 6.4%; p = 0.001) and a lower rate of mRS 0-2 at 3 months was observed in those patients (10.5% vs 37%, p = 0.024). CONCLUSIONS: Emergency intubation during a primary procedural sedation regimen for EVT was associated with lower rate of successful reperfusion. Less favorable outcome was observed in the subgroup of emergently intubated patients. More research is required to find practical predictors of intubation need and to determine, whether emergency intubation is safe under strict primary procedural sedation regimens for EVT.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".