Mechanical thrombectomy failure in anterior circulation large vessel occlusion: an overview from the ROSSETTI registry
Bibliographic record
Abstract
BACKGROUND: Although mechanical thrombectomy (MT) is an effective treatment for large vessel occlusion (LVO) with a high successful recanalization rate, MT failure (MTF) occurs in 10-15% of cases and is associated with unfavorable outcomes. However, little is known about the clinical, technical, and radiological reasons for MTF. We investigated the technical factors associated with MTF. METHODS: We conducted a retrospective analysis of consecutive patients with anterior LVO prospectively included in the ongoing observational multicenter ROSSETTI registry. Patients were categorized according to the success (≥mTICI 2b) or failure (<mTICI 2b) of the MT procedure. Baseline clinical and demographic characteristics, endovascular MT techniques, and angiographic and clinical outcomes were compared. Multivariate analysis for prediction of MTF was performed. RESULTS: We analyzed 4135 patients, including 325 patients (7.9%) with MTF. Patients in the MTF group had a significantly lower Alberta Stroke Program Early CT Score (ASPECTS) at baseline (8 (7-10) vs 9 (8-10)), longer time since last time seen well (279 min vs 262 min), increased MT procedure time (76 min vs 31 min), higher rate of complications (23% vs 4%), higher symptomatic intracerebral hemorrhage (21% vs 7.9%), higher 24 hour National Institutes of Health Stroke Scale score (19 vs 6), worse functional outcome at 3 months (modified Rankin Scale score 0-2, 15.6% vs 53%), and higher mortality (45% vs 20%). Four or more passes were an independent predictor of MTF (OR 3.46, 95% CI 2.58 to 4.63; P<0.001). None of the endovascular techniques demonstrated a higher likelihood of MTF. CONCLUSION: In this study, MTF in anterior circulation LVO was associated with a high complication rate and worse outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".