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Record W4414293104 · doi:10.1161/strokeaha.124.049972

Plasma β-Thromboglobulin Is Inversely Associated With Cerebral Microbleeds in Atrial Fibrillation

2025· article· en· W4414293104 on OpenAlexaff
Bernhard Küpper, Martin F. Reiner, Laura Werlen, Stefanie Aeschbacher, Pratintip Lee, Meret Allemann, Giorgio Moschovitis, T F Luescher, Giovanni G. Camici, Nicolas Rodondi, Luise Adam, Pascal Meyre, Leo H. Bonati, Tim Sinnecker, Michael Kühne, Stefan Osswald, David Conen, Jürg H. Beer

Bibliographic record

VenueStroke · 2025
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsPopulation Health Research Institute
Fundersnot available
KeywordsAtrial fibrillationStroke (engine)Ischemic strokeMagnetic resonance imagingComplication

Abstract

fetched live from OpenAlex

BACKGROUND: Biomarkers may increase the understanding of the pathophysiology of brain lesions in newly evaluated atrial fibrillation. BTG (β-thromboglobulin) is released from platelet alpha granules upon activation, reflecting platelet activation or destruction, or both. We assessed the association of plasma BTG with cerebral microbleeds (CMBs) and ischemic brain lesions using brain magnetic resonance imaging (bMRI) in patients with atrial fibrillation. METHODS: BTG was analyzed using the Luminex assay. CMBs and ischemic brain lesions were detected by standardized bMRI of 1724 patients from the Swiss-Atrial Fibrillation cohort, a prospective, national, multicenter cohort study that enrolled patients between 2014 and 2017. For this cross-sectional analysis, associations of BTG with bMRI lesions were evaluated by logistic and linear regression analyses using 2 models. The first model was adjusted for age and sex, and the second model was additionally multivariable-adjusted for a large number of clinical characteristics, including coronary artery disease, hypertension, diabetes, chronic kidney disease, history of heart failure, major bleeding, as well as concomitant platelet inhibitor, and anticoagulation therapy. RESULTS: Mean age at baseline was 72.5 years (SD, 8.4), and 27.3% were female. On bMRI, CMBs were found in 369 patients (21.4%) and cerebral infarcts in 635 (36.8%). After multivariable adjustment, a 1-unit increase of log-transformed plasma BTG was associated with 25% lower odds of having CMBs (odds ratio, 0.75 [95% CI, 0.59-0.96]). However, BTG was not associated with the presence of large noncortical or cortical infarcts (odds ratio, 0.85 [95% CI, 0.66-1.09]) or small noncortical infarcts (odds ratio, 1.06 [95% CI, 0.83-1.35]). CONCLUSIONS: In patients with atrial fibrillation, the platelet-specific biomarker BTG was inversely and independently associated with CMBs on bMRI. Low-grade platelet activation may improve vascular integrity. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.

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)0.003
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.276
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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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