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Record W2539797428 · doi:10.1212/wnl.0000000000003373

Cerebrovascular reactivity and white matter integrity

2016· article· en· W2539797428 on OpenAlexaff
Kevin Sam, Boris Peltenburg, John Conklin, Olivia Sobczyk, Julien Poublanc, Adrian P. Crawley, Daniel M. Mandell, Lashmi Venkatraghavan, James Duffin, Joseph A. Fisher, Sandra E. Black, David J. Mikulis

Bibliographic record

VenueNeurology · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsToronto Western HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsWhite matterFractional anisotropyDiffusion MRICerebral blood flowMedicineLeukoaraiosisBonferroni correctionPerfusionCardiologyMagnetic resonance imagingInternal medicineNuclear medicineRadiologyMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the diffusion and perfusion MRI metrics of normal-appearing white matter (NAWM) with and without impaired cerebrovascular reactivity (CVR). METHODS: Seventy-five participants with moderate to severe leukoaraiosis underwent blood oxygen level-dependent CVR mapping using a 3T MRI system with precise carbon dioxide stimulus manipulation. Several MRI metrics were statistically compared between areas of NAWM with positive and negative CVR using one-way analysis of variance with Bonferroni correction for multiple comparisons. RESULTS: Areas of NAWM with negative CVR showed a significant reduction in fractional anisotropy by a mean (SD) of 3.7% (2.4), cerebral blood flow by 22.1% (8.2), regional cerebral blood volume by 22.2% (7.0), and a significant increase in mean diffusivity by 3.9% (3.1) and time to maximum by 10.9% (13.2) (p < 0.01), compared to areas with positive CVR. CONCLUSIONS: Impaired CVR is associated with subtle changes in the tissue integrity of NAWM, as evaluated using several quantitative diffusion and perfusion MRI metrics. These findings suggest that impaired CVR may contribute to the progression of white matter 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)0.003
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.317
Teacher spread0.277 · 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
Published2016
Admission routes1
Has abstractyes

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