Inflammation biomarkers in the intracranial blood are associated with outcome in patients with ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Performing endovascular treatment (EVT) in patients with acute ischemic stroke (AIS) allows a port of entry for intracranial biological sampling. OBJECTIVE: To test the hypothesis that specific immune players are molecular contributors to disease, outcome biomarkers, and potential targets for modifying AIS . METHODS: We examined 75 subjects presenting with large vessel occlusion of the anterior circulation and undergoing EVT. Intracranial blood samples were obtained by microcatheter aspiration, as positioned for stent deployment. Peripheral blood samples were collected from the femoral artery. Plasma samples were quality controlled by electrophoresis and analyzed using a Mesoscale multiplex for targeted inflammatory and vascular factors. RESULTS: We measured 37 protein biomarkers in our sample cohort. Through multivariate analysis, adjusted for age, intravenous thrombolysis, pretreatment National Institutes of Health Stroke Scale and Alberta Stroke Program Early CT scores, we found that post-clot blood levels of interleukin-6 (IL-6) were significantly correlated (adjusted P value <0.05) with disability assessed by the modified Rankin Scale (mRS) score at 90 days, with medium effect size. Chemokine (C-C) ligand 17 CCL17/TARC levels were inversely correlated with the mRS score. Examination of peripheral blood showed that these correlations did not reach statistical significance after correction. Intracranial biomarker IL-6 level was specifically associated with a lower likelihood of favorable outcome, defined as a mRS score of 0-2. CONCLUSIONS: Our findings show a signature of blood inflammatory factors at the cerebrovascular occlusion site. The correlations between these acute-stage biomarkers and mRS score outcome support an avenue for add-on and localized immune modulatory strategies in AIS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".