Rescue intracranial stenting for acute ischemic stroke after the failure of mechanical thrombectomy: A systematic review, meta-analysis, and trial sequential analysis
Bibliographic record
Abstract
Background Intracranial rescue stenting (RS) might be an option for acute ischemic stroke after the failure of mechanical thrombectomy (MT). However, the findings were not consistent in previous systematic reviews, and whether the conclusion was supported by sufficient statistical power is unknown. Aim To examine the effect of RS on acute ischemic stroke after the failure of MT with a systematic review, meta-analysis, and trial sequential analysis (TSA). Methods We searched Ovid Medline, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) from inception to 15 June 2022, without any language restriction. Studies assessing the effect of RS for acute ischemia stroke after MT failure were included. Two reviewers independently screened the retrieved articles, extracted data, and evaluated the quality of the included studies through the New Ottawa Scale (NOS). The primary outcome was the recanalization rate after RS. Secondary outcomes included modified Rankin Scale (mRS) at 3 months after stroke, symptomatic intracranial hemorrhage (sICH), and mortality rate. We synthesized the data through a random-effects model and performed a TSA analysis. Results We included 15 studies (containing 1,595 participants) after screening 3,934 records. The pooled recanalization rate for rescue stenting was 82% (95% CI 77–87%). Compared with non-stenting, rescue stenting was associated with a higher proportion of patients with 0–2 mRS score (OR 3.96, 95% CI 2.69–5.84, p < 0.001) and a lower 90-day mortality rate (OR 0.46, 95% CI 0.32–0.65, p < 0.001), and stenting did not increase sICH rate (OR 0.63, 95% CI 0.39–1.04, p = 0.075). The TSA analysis showed that the meta-analysis of the mRS score had a sufficient sample size and statistical power. Conclusions Our study showed that rescue stenting was effective and safe for patients with acute ischemia stroke who also had a failed MT, and this result was confirmed in a TSA analysis.
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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 | 0.027 | 0.057 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| 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".