E-040 Factors associated with failed mechanical thrombectomy in acute ischemic stroke
Bibliographic record
Abstract
<h3>Background</h3> 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. <h3>Methods</h3> 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. <h3>Results</h3> 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%). <h3>Conclusion</h3> 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. <h3>Disclosures</h3> <b>O. Lajthia:</b> None. <b>H. Ali:</b> None. <b>R. Neyes:</b> None. <b>E. Almallouhi:</b> None. <b>R. Chalhoub:</b> None. <b>K. Kicielinski:</b> None. <b>J. Lena:</b> None. <b>M. Sattur:</b> None. <b>G. Porto:</b> None. <b>A. Spiotta:</b> None. <b>S. Al Kasab:</b> None.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".