Clot reduction prior to embolectomy: mSAVE as a first-line technique for large clots
Bibliographic record
Abstract
INTRODUCTION: The "Stent retriever Assisted Vacuum-locked Extraction" (SAVE) technique is a promising embolectomy method for intracranial large vessel occlusion (LVO). We report our experience using a modified SAVE (mSAVE) approach for clot reduction prior to embolectomy in acute ischemic stroke patients with large clots. MATERIALS AND METHODS: We retrospectively analyzed 20 consecutive patients undergoing mSAVE in our center due to intracranial LVO. Angiographic data (including first-pass and overall complete reperfusion, defined as an expanded Thrombolysis in Cerebral Infarction (eTICI) score of 3, rate of successful reperfusion (eTICI ≥2c), number of passes, time from groin puncture to reperfusion) and clinical data (favorable outcome at 90 days, defined as modified Rankin Scale (mRS) ≤2) were assessed. RESULTS: First-pass and overall eTICI 3 reperfusion was reached in 13/20 (65%) and 14/20 (70%), respectively. The rate of successful reperfusion (eTICI ≥2c) after one pass was 85% and on final angiogram 90% with an average number of 1.1 ± 0.3 attempts. Eight out of 11 (73%) ICA occlusions were reperfused successfully and 5 (46%) completely after a single pass. Median groin to reperfusion time was 33 minutes (IQR 25-46). A favorable clinical outcome was achieved in 9/20 (45%) patients at discharge and after 90 days, respectively. CONCLUSION: Clot reduction followed by embolectomy (mSAVE) is feasible and may be an important tool in the treatment of large clots.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".