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Record W2889087455 · doi:10.1161/strokeaha.118.020810

Cortical Microinfarcts on 3T Magnetic Resonance Imaging in Cerebral Amyloid Angiopathy

2018· article· en· W2889087455 on OpenAlexafffund
Hilde van den Brink, Angela Zwiers, Aaron Switzer, Anna Charlton, Cheryl R. McCreary, Bradley G. Goodyear, Richard Frayne, Geert Jan Biessels, Eric E. Smith

Bibliographic record

VenueStroke · 2018
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsFoothills Medical CentreUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsCerebral amyloid angiopathyMedicineMagnetic resonance imagingAmyloid (mycology)Stroke (engine)NeuroimagingPathologyAngiopathyNuclear magnetic resonanceDementiaRadiologyDiseasePsychiatry

Abstract

fetched live from OpenAlex

Background and Purpose- Cerebral microinfarcts are small ischemic lesions that are found in cerebral amyloid angiopathy (CAA) patients at autopsy. The current study aimed to detect cortical microinfarcts (CMI) on in vivo 3 Tesla (3T) magnetic resonance imaging (MRI) in CAA patients, to study the progression of CMI over a 1-year period, and to correlate CMI with markers of CAA-related vascular brain injury and cognitive functioning. Methods- Thirty-five CAA patients (mean age, 74.2±7.6 years), 13 Alzheimer disease (AD) patients (67.0±5.8 years), and 26 healthy controls (67.2±9.5 years) participated in the study. All participants underwent a standardized clinical and neuropsychological assessment as well as 3T MRI. CMI were rated according to standardized criteria. Results- CMI were present in significantly more CAA patients (57.1%; median number: 1, range 1-9) than in Alzheimer disease (7.7%) or in healthy controls (11.5%; P<0.001). Incident CMI were observed after a 1-year follow-up. CMI did not correlate with any other MRI marker of CAA nor with cognitive function. Conclusions- In vivo CMI are a frequent finding on 3T MRI in CAA patients, and incident CMI are observable after 1-year follow-up. CMI can be regarded as a new MRI marker of CAA, potentially distinct from other well-established markers. Future larger cohort studies with longitudinal follow-up are needed to elucidate the relationship between CMI and possible causes and clinical outcomes in CAA.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.001

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 head0.276
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

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

Citations32
Published2018
Admission routes2
Has abstractyes

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