Hemodynamic Changes May Indicate Vessel Wall Injury After Stent Retrieval Thrombectomy for Acute Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Stent retrievers have revolutionized endovascular treatment of acute ischemic stroke (AIS). Animal studies showed that mechanical thrombectomy (MT) may cause endothelial injury and intimal layer edema. Using transcranial color-coded duplex-sonography (TCCS) we observed postprocedural hemodynamic changes in the treated vessel. METHODS: We studied AIS patients with large intracranial artery occlusion in whom MT with stent retrievers was performed. Only those with complete recanalization (modified TICI-2b or 3) as assessed by postprocedural digital subtraction angiography (DSA) and in whom early control TCCS was performed were retained. Patients treated with intra-arterial thrombolysis or stenting were excluded. RESULTS: In 31 patients treated within a time period of 4 years (29 with middle cerebral artery [MCA] and 2 with basilar artery [BA] occlusion), postacute stroke brain-DSA confirmed complete recanalization without residual stenosis or vasospasm. However, in 27 (17 men, mean age 66.3 years) of them TCCS (mean 3.4 days after MT) showed very segmental acceleration of blood flow velocities in the affected arteries (MCA maximum peak systolic velocity [PSVmax] at least >35% as compared to the contralateral side at the same depth; BA PSVmax >40% as compared to velocities at different depths of the same vessel). None showed clinical deterioration. TCCS follow-up (mean 20 days) showed normalization in 14 of 16 cases. CONCLUSION: Our TCCS study provides preliminary evidence of focal acceleration of blood flow velocities after MT. Without residual stenosis or vasospasm, this may be a sign of endothelial layer disruption/intimal injury. Further studies are needed to confirm our results.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".