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Record W2892983700 · doi:10.1161/str.49.suppl_1.145

Abstract 145: Thrombus Composition is Associated With Endothelial Injury and Stroke Etiology in Patients Undergoing Mechanical Thrombectomy for Emergent Large Vessel Occlusion

2018· article· en· W2892983700 on OpenAlexaff
Lucas Elijovich, Adam S Arthur, Daniel Hoit, Chris Nickele, David L. Morris, Jay A. Vachhani, Andrei Belayev, JP Kotha, Edward Hord, Susan Price, Vanessa Derrick, Juan Cárdenas‐Valladolid, Lisa Jennings

Bibliographic record

VenueStroke · 2018
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsNickel Institute
Fundersnot available
KeywordsMedicineCD31ThrombusStroke (engine)OcclusionPathologyPenumbraThrombomodulinImmunohistochemistryRevascularizationCD34Internal medicineGastroenterologyCardiologyIschemiaMyocardial infarctionThrombin

Abstract

fetched live from OpenAlex

Introduction: High rates of recanalization of Emergent Large Vessel Occlusion (ELVO) provide an opportunity to examine retrieved thrombi. We studied device and endothelial (ET) interactions to evaluate ET injury and the relationship between thrombi and Acute Ischemic Stroke (AIS) mechanism. Methods: Prospective registry examining immunohistochemical characteristics of retrieved thrombi in ELVO patients. Thrombi were categorized histopathologically and ET injury quantified by CD34 staining and immunohistochemistry, ELISA and reverse transcribed quantitative PCR to detect ET components. ET mRNA expression of CD31 was quantified from thrombi RNA. Plasma at the thrombectomy site was tested for ET derived biomarkers: microparticles (MPs), soluble Intercellular Cell Adhesion Molecule-1 (sICAM1) and soluble Thrombomodulin (sTM). Statistical analysis was performed with unpaired student’s t-tests and chi-square tests. Results: Twenty-five patients (age 68±3 , NIHSS 16±2, 48% female) were enrolled. The most common sites of occlusion were the MCA (9) and ICA (7). Eighty eight % of patients required three or less attempts at recanalization and 71 % achieved TICI 2b or 3. Histopathology demonstrated fibrin rich (5), erythrocytic (2), layered (7), and serpentine (11) thrombi and four were CD 34 positive. Levels of plasma biomarkers were: sTM 2.2±0.4 (<0.6-10.2ng/ml), MPs 101.4±18.4 (1.33-221nM), and sICAM1 160.0±19.8 (<15-406.1ng/ml). Patients with > 3 revascularization attempts had higher levels of sTM (5.5±0.4 vs 1.7±0.2, p<0.0002), sICAM (261.2±79.2 vs. 146.3±20.3, p<0.03), and CD31CT (27.7±0.8 vs 25.5±0.3, p < 0.03). Patients with PH 1 or 2 ICH had higher levels of microparticles than those without ICH or with HI 1 or 2 (203±19 vs 92±19, p<0.05). Patients with cardioembolic stroke had higher sTM (2.8±0.8 vs. 1.3±0.3, p<0.05) and sICAM1 levels (186±32 vs. 115±29, p<0.05) than those with carotid or intracerebral atherosclerosis. Conclusions: ET markers can be detected in the retrieved thrombi and plasma milieu of ELVO patients. ET markers relate to increasing number of attempts at thrombectomy indicating ET disruption. sTM and sICAM are more common in patients with cardioembolic stroke and may serve as thrombus associated markers of AIS mechanism.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.012
GPT teacher head0.273
Teacher spread0.261 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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