E-040 Factors associated with failed mechanical thrombectomy in acute ischemic stroke
Bibliographic record
Abstract
Background Mechanical thrombectomy (MT) is the standard of care for patients with emergent large-vessel occlusion (LVO). Despite improved endovascular techniques, advances in catheter and stent retriever technology, and accumulated user experience, MT fails to achieve successful revascularization in approximately 20% of AIS patients. The aim of this study is to report the etiology and frequency of failed MT. Methods A prospectively maintained database of MT performed at a comprehensive stroke center in the south-eastern United States between January 2013 and August 2021 was interrogated. We systematically gathered demographic data, clinical presentation, procedural details and MT failure etiology on all adult patients who underwent MT with subsequent failed recanalization. Angiographic images were interpreted by an independent neuro-interventionalist. Results Out of a total of 1053 MT procedures, 122 cases (11.6%) were unsuccessful with a final TICI of 0–2a. The mean age was 67.3 years old (±14.5), 62 patients (50.8%) were male and the most common risk factor identified was hypertension in 96 patients (78.7%). On presentation the average National Institute of Health Stroke Scale (NIHSS) was 14.9, mean Alberta Stroke Program Early CT Score (ASPECTS) of 7.9 and most common vessel occluded was the left middle cerebral artery in 41 patients (33.6%). The femoral artery was the access site in 120 cases (94.8%), the average procedure length was 56.3 minutes (±24.8) and the mean number of attempts was 4.6. No patients in our cohort failed MT at the access site, 4 cases (3.3%) failed at the aortic arch and there were no failures at the neck. 118 patients (96.7%) had MT failure once intracranial access had been obtained and most commonly secondary to Intracranial Atherosclerosis (ICAS) seen in 49 cases (41.5%), followed by recalcitrant clot in 35 patients (29.57%) and distal embolization in 6 cases (5.1%). Conclusion Failed MT was encountered in approximately 12% of cases. The most common location of failed MT was intracranial and this was predominantly due to ICAS. Further studies to evaluate better treatment modalities of ICAS related LVO are warranted. Disclosures O. Lajthia: None. H. Ali: None. R. Neyes: None. E. Almallouhi: None. R. Chalhoub: None. K. Kicielinski: None. J. Lena: None. M. Sattur: None. G. Porto: None. A. Spiotta: None. S. Al Kasab: None.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".