The initial experience with the Embotrap III stent-retriever in a real world setting
Bibliographic record
Abstract
Stent-retriever based mechanical thrombectomy (MT) has gained wide acceptance as the treatment of choice for acute ischaemic stroke (AIS) caused by large vessel occlusion (LVO). The Embotrap 3 is the latest iteration within this class of device. We present our results using the new Embotrap 3 device. Materials and Methods We performed a retrospective review of our prospectively maintained database to identify all patients treated with the Embotrap 3 stent-retriever between January 2021 and January 2022. We recorded the baseline demographics, NIHSS, ASPECT score and clot characteristics, first pass and final eTICI scores, complications and 90 day mRS. Results One hundred and ten patients met the inclusion criteria, average age 69 ± 14 years, 50% were male ( n = 55). The median NIHSS at presentation was 18 (range 3–30) and 58.2% received IV tPA prior to MT. The median ASPECT score on plain CT was 8 with average clot length 20.2 ± 14.8 mm ( n = 93). The first pass effect (FPE) was seen in 41.8% of cases with modified FPE seen in 59.1%. A 24-hour CT scan ( n = 97) showed median ASPECTs of 7. 43.8% of patients achieve mRS ≤ 2 at 90-day mRS ( n = 64). Conclusion The Embotrap 3 stent-retriever has a high rate of FPE and final recanalization in this real world cohort of patients.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".