Endovascular stroke treatment using balloon guide catheters may reduce penumbral tissue damage and improve long-term outcome
Bibliographic record
Abstract
OBJECTIVES: During mechanical recanalization of large vessel occlusions (LVO), the use of proximal flow arrest with balloon guide catheters (BGC) was shown to be associated with better angiographic and even clinical outcome. The aim of the study was to analyze the impact of BGC use on microstructural alterations in the salvaged penumbra. METHODS: All patients who underwent mechanical recanalization of LVO of the anterior circulation were reviewed within a prospective stroke registry of a single comprehensive stroke center. Fifty-two patients received an admission CT perfusion together with post-interventional diffusion tensor imaging. Technical details such as BGC usage were correlated with microstructural integrity changes of the salvaged gray matter through the mean diffusivity (MD) index. Moderation analysis was performed to test the interaction of BGC on the correlation between angiographic and clinical outcomes. RESULTS: For all patients with complete reperfusion, microstructural integrity changes with lowered MD index were found within the salvaged penumbra for cases of non-BGC usage (mean - 0.02) compared to cases with BGC usage (0.01, p = 0.04). The importance of complete reperfusion for good clinical outcome is predominantly based on patients treated with BGC (effect 2.78, p = 0.01 vs. for non-BGC: 0.3, p = 0.71). CONCLUSIONS: The lowered MD index early after mechanical recanalization without BGC usage can be interpreted as microstructural ischemic damage of the salvaged penumbra. It was shown that achieving complete reperfusion in a setting of BGC usage with proximal flow arrest minimizes penumbral damage and improves long-term outcomes. KEY POINTS: • Microstructural ischemic damage can be reduced by using proximal flow arrest during endovascular treatment with balloon guide catheter. • Complete reperfusion in a setting of balloon guide catheter minimizes penumbral damage and improves long-term outcome.
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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) | 0.001 | 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 | 0.000 |
| 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".