Hemodynamics of Leptomeningeal Collaterals after Large Vessel Occlusion and Blood Pressure Management with Endovascular Treatment
Bibliographic record
Abstract
Endovascular therapy (EVT) is an effective treatment for ischemic stroke due to large vessel occlusion (LVO). Unlike intravenous thrombolysis, EVT enables visualization of the restoration of blood flow, also known as successful reperfusion in real time. However, until successful reperfusion is achieved, the survival of the ischemic brain is mainly dependent on blood flow from the leptomeningeal collaterals (LMC). It plays a critical role in maintaining tissue perfusion after LVO via pre-existing channels between the arborizing pial small arteries or arterioles overlying the cerebral hemispheres. In the ischemic territory where the physiologic cerebral autoregulation is impaired and the pial arteries are maximally dilated within their capacity, the direction and amount of LMC perfusion rely on the systemic perfusion, which can be estimated by measuring blood pressure (BP). After the EVT procedure, treatment focuses on mitigating the risk of hemorrhagic transformation, potentially via BP reduction. Thus, BP management may be a key component of acute care for patients with LVO stroke. However, the guidelines on BP management during and after EVT are limited, mostly due to the scarcity of high-level evidence on this issue. In this review, we aim to summarize the anatomical and physiological characteristics of LMC to maintain cerebral perfusion after acute LVO, along with a landscape summary of the literature on BP management in endovascular treatment. The objective of this review is to describe the mechanistic association between systemic BP and collateral perfusion after LVO and thus provide clinical and research perspectives on this topic.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".