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Record W2897312140 · doi:10.1177/2396987318805905

Small vessel disease and biomarkers of endothelial dysfunction after ischaemic stroke

2018· article· en· W2897312140 on OpenAlexaff
Francesco Arba, A Giannini, Benedetta Piccardi, Silvia Biagini, Vanessa Palumbo, Betti Giusti, Patrizia Nencini, Anna Maria Gori, Mascia Nesi, Giovanni Pracucci, Giorgio Bono, Paolo Bovi, Enrico Fainardi, Domenico Consoli, Antonia Nucera, Francesca Massaro, Giovanni Orlandi, Francesco Perini, Rossana Tassi, Maria Sessa, Danilo Toni, Rosanna Abbate, Domenico Inzitari

Bibliographic record

VenueEuropean Stroke Journal · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsLondon Health Sciences CentreWestern University
FundersMinistero della SaluteEnte Cassa di Risparmio di Firenze
KeywordsEndothelial dysfunctionVon Willebrand factorMedicineLeukoaraiosisPathogenesisVascular diseaseInternal medicineStroke (engine)EndotheliumCardiologyDiseasePathologyPlatelet

Abstract

fetched live from OpenAlex

INTRODUCTION: Although pathogenesis of small vessel disease is poorly understood, increasing evidence suggests that endothelial dysfunction may have a relevant role in development and progression of small vessel disease. In this cross-sectional study, we investigated the associations between imaging signs of small vessel disease and blood biomarkers of endothelial dysfunction at two different time points in a population of ischaemic stroke patients. PATIENTS AND METHODS: In stroke patients treated with intravenous thrombolysis, we analysed blood levels of von Willebrand factor, intercellular adhesion molecule-1, vascular cell adhesion molecule-1 and vascular endothelial growth factor. Three reviewers independently assessed small vessel disease features using computed tomography. At baseline and 90 days after the index stroke, we tested the associations between single and combined small vessel disease features and levels of blood biomarkers using linear regression analysis adjusting for age, sex, hypertension, diabetes, smoke. RESULTS: A total of 263 patients were available for the analysis. Mean age (±SD) was 69 (±13) years, 154 (59%) patients were male. We did not find any relation between small vessel disease and endothelial dysfunction at baseline. At 90 days, leukoaraiosis was independently associated with intercellular adhesion molecule-1 (β = 0.21; p = 0.016) and vascular cell adhesion molecule-1 (β = 0.22; p = 0.009), and lacunes were associated with vascular endothelial growth factor levels (β = 0.21; p = 0.009) whereas global small vessel disease burden was associated with vascular endothelial growth factor (β = 0.26; p = 0.006). DISCUSSION: Leukoaraiosis and lacunes were associated with endothelial dysfunction, which could play a key role in pathogenesis of small vessel disease. CONCLUSIONS: Small vessel disease features and total burden were associated with endothelial dysfunction 90 days after the stroke, whereas there was no relation during the acute phase. Our results suggest that endothelial dysfunction, particularly vascular endothelial growth factor, is involved in pathological process of small vessel disease.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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

Citations51
Published2018
Admission routes1
Has abstractyes

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