MétaCan
Menu
Back to cohort
Record W4401665747 · doi:10.1186/s12974-024-03201-9

The differential proteomic response to ischemic stroke in appalachian subjects treated with mechanical thrombectomy

2024· article· en· W4401665747 on OpenAlexaboutno aff
Christopher J. McLouth, Benton Maglinger, Jacqueline A. Frank, Hunter S. Hazelwood, Jordan P. Harp, Will Cranford, Shivani Pahwa, Lila Sheikhi, David Dornbos, Amanda L. Trout, Ann Stowe, Justin F. Fraser, Keith R. Pennypacker

Bibliographic record

VenueJournal of Neuroinflammation · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
FundersNational Institute of Environmental Health SciencesNational Institute of Neurological Disorders and StrokeNational Institute on Aging
KeywordsAppalachiaStroke (engine)MedicineDiabetes mellitusAppalachian RegionObesityPsychological interventionNeurologyPhysical medicine and rehabilitationIschemic strokeInternal medicinePhysical therapyIntensive care medicineIschemiaPsychiatryBiology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.194
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.250
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of NeuroinflammationSame topicAcute Ischemic Stroke ManagementFrench-language works237,207