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Record W3169621013 · doi:10.1111/ene.14985

Blood–brain barrier leakage and hemorrhagic transformation: The Reperfusion Injury in Ischemic StroKe (RISK) study

2021· article· en· W3169621013 on OpenAlex
Francesco Arba, Benedetta Piccardi, Vanessa Palumbo, Silvia Biagini, Francesco Galmozzi, Veronica Iovene, A Giannini, Giuseppe Dario Testa, Alessandro Sodero, Mascia Nesi, Davide Gadda, Marco Moretti, Maria Lamassa, Francesca Pescini, Anna Poggesi, Cristina Sarti, Stefania Nannoni, Giovanni Pracucci, Nicola Limbucci, Sergio Nappini, Leonardo Renieri, Stefano Grifoni, Enrico Fainardi, Domenico Inzitari, Patrizia Nencini

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEuropean Journal of Neurology · 2021
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThrombolysisInterquartile rangeOdds ratioStroke (engine)Confidence intervalIntracerebral hemorrhageInternal medicineLogistic regressionSurgeryAnesthesiaMyocardial infarctionSubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Abstract Background and purpose In patients with acute ischemic stroke treated with reperfusion therapy we aimed to evaluate whether pretreatment blood–brain barrier (BBB) leakage is associated with subsequent hemorrhagic transformation (HT). Methods We prospectively screened patients with acute ischemic stroke treated with intravenous thrombolysis and/or endovascular treatment. Before treatment, each patient received computed tomography (CT), CT angiography, and CT perfusion. We assessed pretreatment BBB leakage within the ischemic area using the volume transfer constant (K trans ) value. Our primary outcome was relevant HT, defined as hemorrhagic infarction type 2 or parenchymal hemorrhage type 1 or 2. We evaluated independent associations between BBB leakage and HT using logistic regression, adjusting for age, sex, baseline stroke severity, Alberta Stroke Program Early CT Score (ASPECTS) ≥ 6, treatment type, and onset‐to‐treatment time. Results We enrolled 171 patients with available assessment of BBB leakage. The patients' mean (±SD) age was 75.5 (±11.8) years, 86 (50%) were men, and the median (interquartile range) National Institutes of Health Stroke Scale score was 18 (12–23). A total of 32 patients (18%) received intravenous thrombolysis, 102 (60%) underwent direct endovascular treatment, and 37 (22%) underwent both. Patients with relevant HT ( N = 31;18%) had greater mean BBB leakage (K trans 0.77 vs. 0.60; p = 0.027). After adjustment in the logistic regression model, we found that BBB leakage was associated both with a more than twofold risk of relevant HT (odds ratio [OR] 2.50; 95% confidence interval [CI] 1.03–6.03 per K trans point increase; OR 2.34; 95% CI 1.06–5.17 for K trans values > 0.63 [mean BBB leakage value]) and with symptomatic intracerebral hemorrhage (OR 4.30; 95% CI 1.13–13.77 per K trans point increase). Conclusion Pretreatment BBB leakage before reperfusion therapy was associated with HT, and may help to identify patients at risk of HT.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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