Innovations in Thrombectomy Training: A Systematic Review and Expert Recommendations from the Society of Vascular and Interventional Neurology‐Mission Thrombectomy Initiative
Bibliographic record
Abstract
BACKGROUND: Mechanical thrombectomy is a critical intervention for patients with acute ischemic stroke with large vessel occlusion. However, significant barriers remain in its widespread implementation, particularly in low- to middle-income countries, including a shortage of trained physicians and limited access to advanced medical technologies. This systematic review and meta-analysis aimed to comprehensively evaluate current mechanical thrombectomy training methodologies and assess their effectiveness in improving procedural skills among neurointerventional teams. METHODS: We conducted a systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines, searching PubMed, Scopus, and Web of Science. Eight studies were included, with 3 studies eligible for meta-analysis. We assessed training approaches, participant demographics, and procedural outcomes using the Risk of Bias in Non-randomized Studies of Interventions tool and performed statistical analysis using OpenMetaAnalyst software. RESULTS: Various training modalities, including virtual reality simulations and hands-on workshops, consistently demonstrated positive effects on procedural skills and professional confidence, demonstrating significant improvements across multiple metrics. Our systematic review and meta-analysis revealed statistically significant reductions in total procedure time (average decrease of 17.84 minutes, 95% CI: [-22.19 to -13.48]), number of handling errors (decreased by 6.34 errors, 95% CI: [-13.16 to 0.48]), contrast volume (decreased by 27.35 mL, 95% CI: [-45.11 to -9.60]), and fluoroscopy time (reduced by 8.07 minutes, 95% CI: [-10.71 to -5.44]). Participants showed increased procedural steps completed, with an average increase of 6.52 steps (95% CI: [3.99-9.05]). CONCLUSION: Structured, simulation-based mechanical thrombectomy training programs can significantly enhance procedural skills, clinical decision-making, and professional confidence among neurointerventional teams, potentially improving stroke care.
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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 | 0.040 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.015 |
| Bibliometrics | 0.019 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".