Clinical Effectiveness and Safety Outcomes of Endovascular Treatment for Acute Anterior Circulation Ischemic Stroke in China
Bibliographic record
Abstract
BACKGROUNDS AND PURPOSE: This study was aimed at investigating the outcomes and predictors for the poor functional outcome after endovascular treatment (EVT) in a large, mostly Asian population. METHODS: Between January 2014 and June 2016, acute stroke patients with anterior circulation occlusion and EVT were retrospectively enrolled from 21 stroke centers in China. The main outcomes were modified Rankin Scale (0-2 as functional independence, 3-6 as poor) at 90 days, symptomatic intracranial hemorrhage (sICH) at 72 h, and death at 90 days. Logistic regression was used to identify predictors for poor functional outcome at 90 days. RESULTS: Of the 698 patients, 304 (43.6%) patients had functional independence at 90 days. The sICH rate was 15.5% (108/698) and mortality rate at 90 days was 25.4% (177/698). Age (OR 1.04, 95% CI 1.02-1.07), National Institutes of Health Stroke Scale score at admission (11-20 vs. ≤10, OR 2.38, 95% CI 1.23-4.59; ≥21 vs. ≤10, OR 3.66, 95% CI 1.72-7.80), baseline glucose level (OR 1.09, 95% CI 1.01-1.18), onset to groin puncture >6 h (OR 1.88, 95% CI 1.06-3.31), sICH (OR 15.49, 95% CI 5.16-46.43), and pneumonia (OR 3.15, 95% CI 1.86-5.32) were independent predictors of poor functional outcomes, while good recanalization (OR 0.26, 95% CI 0.13-0.54), preoperative Alberta Stroke Program Early CT Score 8-10 (OR 0.48, 95% CI 0.28-0.83), and good collateral flow (OR 0.50, 95% CI 0.32-0.79) were protective factors. CONCLUSIONS: This study provides evidence in real world to support the performance of EVT in acute anterior circulation stroke patients in Chinese population. Patients with small infarct core, successful recanalization, good collateral status, and short treatment delay without sICH or pneumonia may benefit from 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".