Aspiration versus stent retriever for posterior circulation stroke: A meta‐analysis
Bibliographic record
Abstract
AIMS: New thrombectomy strategies have emerged recently. Differences between posterior circulation stroke management via aspiration and stent retriever remain to be evaluated. We compared the safety and efficacy of aspiration and stent retriever in treating posterior circulation stroke. METHODS: Three databases (PubMed, Embase, and Cochrane Library) were systematically searched for studies comparing aspiration and stent retriever in patients with posterior circulation stroke. The modified Newcastle-Ottawa scale was used to assess the risk of bias. A random-effects model was used. RESULTS: Fifteen cohort studies with 1451 patients were included. Pooled results showed a significant difference in total complication (odds ratio [OR] 0.48, 95% confidence interval [CI] [0.30, 0.76], p = 0.002). successful recanalization (1.85, [1.30, 2.64], p = 0.0006), favorable outcome (1.30, [1.02, 1.67], p = 0.04), procedure duration (-22.10, [-43.32, -0.88], p = 0.04), complete recanalization (4.96, [1.06, 23.16], p = 0.009), and first-pass effect (2.59, [1.55, 4.32], p = 0.0003) between the aspiration and stent retriever groups, and in favor of aspiration. There was no significant difference in the outcomes of rescue therapy (1.42, [0.66, 3.05], p = 0.37) between the two groups. CONCLUSION: Patients with posterior circulation stroke receiving treatment with aspiration achieved better recanalization, first-pass effect, and shorter procedure time. Aspiration may be more secure than a stent retriever.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.040 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".