Impact of procedural time on clinical and angiographic outcomes in patients with acute ischemic stroke receiving endovascular treatment
Bibliographic record
Abstract
BACKGROUND: Procedural time in patients with acute ischemic stroke (AIS) undergoing mechanical thrombectomy may affect clinical outcomes. We performed a pooled analysis of the effect of procedural time on clinical outcomes using data from three prospective endovascular treatment trials. OBJECTIVE: To examine the relationship between endovascular procedural time and clinical outcomes of patients with AIS following endovascular treatment. METHODS: We analyzed data from SWIFT, STAR, and SWIFT PRIME studies, including baseline characteristics: National Institutes of Health Stroke Scale (NIHSS) score on admission, intracranial hemorrhage rates, and modified Rankin Scale score at 3 months. The Thrombolysis in Cerebral Infarction (TICI) scale was used to grade postprocedure recanalization. We recorded two procedural time intervals: (1) symptom onset to groin puncture and (2) groin puncture to angiographic recanalization. A multivariate analysis was performed using a logistic regression model to analyze predictors of unfavorable outcome. RESULTS: We analyzed 301 patients who had undergone endovascular treatment and had near-complete or complete recanalization (TICI 2b or 3). At 3 months, 122 patients (40.5%) had unfavorable outcomes. The rate of favorable outcomes was significantly higher when the procedural time was <60 min compared with ≥60 min (62% vs 45%, p=0.020). Predictors of unfavorable outcome at 3 months were age (unit 10 years, OR=0.62, 95% CI 0.46 to 0.82, p<0.001), onset to groin puncture time (unit hour, OR=0.61, 95% CI 0.48 to 0.77, p<0.001), groin puncture to recanalization (unit 10 min, OR=0.89, 95% CI 0.80 to 0.99, p=0.032), baseline NIHSS score (20-28 vs 8-10, OR=0.17, 95% CI 0.05 to 0.62, p=0.018), and collaterals (OR=1.48, 95% CI 1.04 to 2.10, p=0.029). CONCLUSION: Procedural time in patients with stroke undergoing mechanical thrombectomy may be an important determinant of favorable outcomes in those with recanalization.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.001 | 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".