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Record W4396556146 · doi:10.1161/strokeaha.123.045204

Hemorrhagic Transformation in Noncardioembolic Acute Ischemic Stroke: MRI Analysis From PACIFIC-STROKE

2024· article· en· W4396556146 on OpenAlexaff
Chih‐Hao Chen, Ashkan Shoamanesh, Pablo Colorado, Feryal Saad, Robin Lemmens, Gian Marco De Marchis, Valeria Caso, Lizhen Xu, Laura Heenan, Jaime Masjuán, Hanne Christensen, Stuart J. Connolly, Pooja Khatri, Hardi Mundl, Robert G. Hart, Eric E. Smith

Bibliographic record

VenueStroke · 2024
Typearticle
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsMcMaster UniversityPopulation Health Research InstituteUniversity of Calgary
Fundersnot available
KeywordsMedicineStroke (engine)Internal medicinePlaceboMagnetic resonance imagingLogistic regressionCardiologyInfarctionRadiologyPathologyMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: In the phase 2 PACIFIC-STROKE trial (Proper Dosing and Safety of the Oral FXIa Inhibitor BAY 2433334 in Patients Following Acute Noncardioembolic Stroke), asundexian, an oral factor XIa inhibitor, did not increase the risk of hemorrhagic transformation (HT). In this secondary analysis, we aimed to investigate the frequency, types, and risk factors of HT on brain magnetic resonance imaging (MRI). METHODS: This was a secondary analysis of the PACIFIC-STROKE trial. Patients with mild-to-moderate acute noncardioembolic ischemic stroke were randomly assigned to asundexian or placebo plus guideline-based antiplatelet therapy. Brain MRIs were required at baseline (≤120 hours after stroke onset) and at 26 weeks or end-of-study. HT was defined using the Heidelberg classification and classified as early HT (identified on baseline MRI) or late HT (new HT by 26 weeks) based on iron-sensitive sequences. Multivariable logistic regression models were used to test factors that are associated with early HT and late HT, respectively. RESULTS: Of 1745 patients with adequate baseline brain MRI (mean age, 67 years; mean National Institutes of Health Stroke Scale score, 2.8), early HT at baseline was detected in 497 (28.4%). Most were hemorrhagic infarctions (hemorrhagic infarction type 1: 15.2%; HI2: 12.7%) while a few were parenchymal hematomas (parenchymal hematoma type 1: 0.4%; parenchymal hematoma type 2: 0.2%). Early HT was more frequent with longer symptom onset-to-MRI interval. Male sex, diabetes, higher National Institutes of Health Stroke Scale large (>15 mm) infarct size, cortical involvement by infarct, higher number of acute infarcts, presence of chronic brain infarct, cerebral microbleed, and chronic cortical superficial siderosis were independently associated with early HT in the multivariable logistic regression model. Of 1507 with follow-up MRI, HT was seen in 642 (42.6%) overall, including 361 patients (23.9%) with late HT (new HT: 306; increased grade of baseline HT: 55). Higher National Institutes of Health Stroke Scale, large infarct size, cortical involvement of infarct, and higher number of acute infarcts predicted late HT. CONCLUSIONS: About 28% of patients with noncardioembolic stroke had early HT, and 24% had late HT detectable by MRI. Given the high frequency of HT on MRI, more research is needed on how it influences treatment decisions and outcomes.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0020.000

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 head0.010
GPT teacher head0.261
Teacher spread0.251 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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