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Record W3006725378 · doi:10.1161/str.51.suppl_1.147

Abstract 147: Outcomes of the Stroke Thromboembolism Registry of Imaging and Pathology: A Multicenter International Study

2020· article· en· W3006725378 on OpenAlexaff
Waleed Brinjikji, Seán Fitzgerald, David F. Kallmes, Kennith F. Layton, Ricardó A. Hanel, Vítor Mendes Pereira, Peter Kvamme, Josser E Delgado Almandoz, Albert J. Yoo, Babak S. Jahromi, Mohammed Almekhlafi, Matthew J. Gounis, Raul G. Nogueira

Bibliographic record

VenueStroke · 2020
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsUniversity of CalgaryToronto Western Hospital
Fundersnot available
KeywordsMedicineEtiologyStroke (engine)RevascularizationInternal medicineHistopathologyProspective cohort studyExact testThrombusRadiologyCardiologyPathologySurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

Background: We performed a multicenter prospective clinical registry across 11 centers to study the association between histopathological characteristics of retrieved clots and imaging, stroke etiology and clinical outcomes. Materials and Methods: Following IRB approval at the 11 centers, patients were enrolled in the STRIP registry. All retrieved emboli were sent for histopathological analysis with H&E and MSB staining. Demographic variables, comorbidities, stroke etiology, imaging findings and procedural details were collected for each case. We studied the association between clot histopathology and imaging findings, stroke etiology and and revascularization outcomes. Student’s t-test was used for continuous variables and chi-squared testing for categorical variables. Results: To date, 1022 patients have been included. There was a significant correlation between platelet rich clots and the absence of hyperdensity on non-contrast CT [p=0.321, p=0.003) and a significant inverse correlation between the percentage of platelets and mean HU on NCCT (p=-0.243, p=0.025). The proportion of platelet-rich clots (55.0% versus 21.2%, p=0.005) and the percentage of platelet content (22.1% versus 13.9%, p=0.03) was significantly higher in patient with large artery atherosclerosis compared to those with a cardioembolic etiology. There was no correlation between RBC density, WBC density, fibrin density or platelet density and revascularization outcomes with stent-retrievers. However, we have found that with aspiration alone, patients with platelet rich clots are less likely to be fully revascularized (i.e. TICI 2c/3) than non-platelet rich clots (OR=0.36, 95%CI=0.12-0.81, P<.0001). Meanwhile, patients with RBC rich clots are more likely to be completely revascularized with aspiration alone than those with RBC poor clots (OR=2.71, 95%CI=1.25-3.24, P=0.02). Conclusions: Interim analysis of the STRIP registry suggests that the platelet content of a clot may be the most revealing factor in determining a clot’s etiology, imaging features and revascularization outcome. Platelet rich clots are less dense on NCCT, are associated with a large artery atherosclerosis source and are less likely to be completely revascularized with aspiration alone.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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".

Quick stats

Citations3
Published2020
Admission routes1
Has abstractyes

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