MétaCan
Menu
Back to cohort

Association between clot composition and stroke origin in mechanical thrombectomy patients: analysis of the Stroke Thromboembolism Registry of Imaging and Pathology

2021· article· en· W3136681211 on OpenAlex
Waleed Brinjikji, Raul G. Nogueira, Peter Kvamme, Kennith F. Layton, Josser E Delgado Almandoz, Ricardó A. Hanel, Vítor Mendes Pereira, Mohammed Almekhlafi, Albert J. Yoo, Babak S. Jahromi, Matthew J. Gounis, Biraj M. Patel, Mehdi Abbasi, Seán Fitzgerald, Oana Madalina Mereuta, Daying Dai, Ramanathan Kadirvel, Karen Doyle, Luis Savastano, Harry J. Cloft, Diogo C Haussen, Alhamza R Al‐Bayati, Mahmoud Mohammaden, Leonardo Pisani, Gabriel Martins Rodrigues, Ike Thacker, Yasha Kayan, Alexander Copelan, Amin Aghaebrahim, Eric Sauvageau, Andrew M. Demchuk, Parita Bhuva, Jazba Soomro, Pouya Nazari, Donald R. Cantrell, Ajit S Puri, John W. Entwistle, Eric C. Polley, David F. Kallmes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of NeuroInterventional Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsUniversity of CalgaryToronto Western HospitalUniversity Health Network
FundersNational Institute of Neurological Disorders and Stroke
KeywordsMedicineStroke (engine)CardiologyIschemic strokeInternal medicinePathologyRadiologyIschemia

Abstract

fetched live from OpenAlex

Background We retrospectively evaluated the composition of retrieved clots from ischemic stroke patients to study the association between histological composition and stroke etiology Methods Consecutive patients enrolled in the Stroke Thromboembolism Registry of Imaging and Pathology (STRIP) were included in this study. All patients underwent mechanical thrombectomy and retrieved clots were sent to a central core lab for processing. Histological analysis was performed using martius scarlet blue (MSB) staining, and quantification for red blood cells (RBCs), white blood cells (WBCs), fibrin and platelets was performed using Orbit Image Software. A Wilcoxon test was used for continuous variables and χ 2 test for categorical variables. Results 1350 patients were included in this study. The overall rate of Thrombolysis In Cerebral Infarction (TICI) 2c/3 was 68%. 501 patients received tissue plasminogen activator (tPA) (37%). 267 patients (20%) had a large artery atherosclerosis (LAA) source, 662 (49%) a cardioembolic (CE) source, 301 (22%) were cryptogenic, and the remainder had other identifiable sources including hypercoagulable state or dissection. LAA thrombi had a higher mean RBC density (46±23% vs 42±22%, p=0.01) and a lower platelet density (24±18% vs 27±18%, p=0.03) than CE thrombi. Clots from dissection patients had the highest mean RBC density (50±24%) while clots from patients with a hypercoagulable state had the lowest mean RBC density (26±21%). Conclusions Our study found statistically significant but clinically insignificant differences between clots of CE and LAA etiologies. Future studies should emphasize molecular, proteomic and immunohistochemical characteristics to determine links between clot composition and etiology.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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