The differential proteomic response to ischemic stroke in appalachian subjects treated with mechanical thrombectomy
Bibliographic record
Abstract
INTRODUCTION: The Appalachia region of North America is known to have significant health disparities, specifically, worse risk factors and outcomes for stroke. Appalachians are more likely to have comorbidities related to stroke, such as diabetes, obesity, and tobacco use, and are often less likely to have stroke interventions, such as mechanical thrombectomy (MT), for emergent large vessel occlusion (ELVO). As our Comprehensive Stroke Center directly serves stroke subjects from both Appalachian and non-Appalachian areas, inflammatory proteomic biomarkers were identified associated with stroke outcomes specific to subjects residing in Appalachia. METHODS: There were 81 subjects that met inclusion criteria for this study. These subjects underwent MT for ELVO, and carotid arterial blood samples acquired at time of intervention were sent for proteomic analysis. Samples were processed in accordance with the Blood And Clot Thrombectomy Registry And Collaboration (BACTRAC; clinicaltrials.gov; NCT03153683). Statistical analyses were utilized to examine whether relationships between protein expression and outcomes differed by Appalachian status for functional (NIH Stroke Scale; NIHSS and Modified Rankin Score; mRS), and cognitive outcomes (Montreal Cognitive Assessment; MoCA). RESULTS: No significant differences were found in demographic data or co-morbidities when comparing Appalachian to non-Appalachian subjects. However, time from stroke onset to treatment (last known normal) was significantly longer and edema volume significantly higher in patients from Appalachia. Further, when comparing Appalachian to non-Appalachian subjects, there were significant unadjusted differences in the NIHSS functional outcome. A comprehensive analysis of 184 proteins from Olink proteomic (92 Cardiometabolic and 92 Inflammation panels) showed that the association between protein expression outcomes significantly differed by Appalachian status for seven proteins for the NIHSS, two proteins for the MoCA, and three for the mRS. CONCLUSION: Our study utilizes an ELVO tissue bank and registry to investigate the intracranial/intravascular proteomic environment occurring at the time of thrombectomy. We found that patients presenting from Appalachian areas have different levels of proteomic expression at the time of MT when compared to patients presenting from non-Appalachian areas. These proteins differentially relate to stroke outcome and could be used as prognostic biomarkers, or as targets for novel therapies. The identification of a disparate proteomic response in Appalachian patients provides initial insight to the biological basis for health disparity. Nevertheless, further investigations through community-based studies are imperative to elucidate the underlying causes of this differential response.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".