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Associations Between Findings From Myelin Water Imaging and Cognitive Performance Among Individuals With Multiple Sclerosis

2020· article· en· W3090120661 on OpenAlexafffund
Shawna Abel, Irene M. Vavasour, Lisa Eunyoung Lee, Poljanka Johnson, Stephen Ristow, Nathalie Ackermans, Jillian Chan, Helen Cross, Cornelia Laule, Adam Dvorak, Alice Schabas, Enedino Hernández‐Torres, Roger Tam, Annie J Kuan, Sarah A. Morrow, Jeffrey Wilken, Alexander Rauscher, Virender Bhan, Ana‐Luiza Sayao, Virginia Devonshire, David K.B. Li, Robert Carruthers, Anthony Traboulsee, Shannon Kolind

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsWestern UniversityInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersSanofi GenzymeEMD SeronoMultiple Sclerosis Society of CanadaVertex PharmaceuticalsMultiple Sclerosis SocietyF. Hoffmann-La RocheTeva Pharmaceutical IndustriesMichael Smith Health Research BCBiogenCelgeneSanofi
KeywordsMultiple sclerosisMagnetic resonance imagingCognitionMedicineNeuroimagingEffects of sleep deprivation on cognitive performanceMyelinAudiologyInternal medicineRadiologyPsychiatryCentral nervous system

Abstract

fetched live from OpenAlex

Importance: Cognitive impairment is a debilitating symptom of multiple sclerosis (MS) that affects up to 70% of patients. An improved understanding of the underlying pathology of MS-related cognitive impairment would provide considerable benefit to patients and clinicians. Objective: To determine whether there is an association between myelin damage in tissue that appears completely normal on standard clinical imaging, but can be detected by myelin water imaging (MWI), with cognitive performance in MS. Design, Setting, and Participants: In this cross-sectional study, participants with MS and controls underwent cognitive testing and magnetic resonance imaging (MRI) from August 23, 2017, to February 20, 2019. Participants were recruited through the University of British Columbia Hospital MS clinic and via online recruitment advertisements on local health authority websites. Cognitive testing was performed in the MS clinic, and MRI was performed at the adjacent academic research neuroimaging center. Seventy-three participants with clinically definite MS fulfilling the 2017 revised McDonald criteria for diagnosis and 22 age-, sex-, and education-matched healthy volunteers without neurological disease were included in the study. Data analysis was performed from March to November 2019. Exposures: MWI was performed at 3 T with a 48-echo, 3-dimensional, gradient and spin-echo (GRASE) sequence. Cognitive testing was performed with assessments drawn from cognitive batteries validated for use in MS. Main Outcomes and Measures: The association between myelin water measures, a measurement of the T2 relaxation signal from water in the myelin bilayers providing a specific marker for myelin, and cognitive test scores was assessed using Pearson correlation. Three white matter regions of interest-the cingulum, superior longitudinal fasciculus (SLF), and corpus callosum-were selected a priori according to their known involvement in MS-related cognitive impairment. Results: For the 95 total participants, the mean (SD) age was 49.33 (11.44) years. The mean (SD) age was 50.2 (10.7) years for the 73 participants with MS and 46.4 (13.5) for the 22 controls. Forty-eight participants with MS (66%) and 14 controls (64%) were women. The mean (SD) years of education were 14.7 (2.2) for patients and 15.8 (2.5) years for controls. In MS, significant associations were observed between myelin water measures and scores on the Symbol Digit Modalities Test (SLF, r = -0.490; 95% CI, -0.697 to -0.284; P < .001; corpus callosum, r = -0.471; 95% CI, -0.680 to -0.262; P < .001; and cingulum, r = -0.419; 95% CI, -0.634 to -0.205; P < .001), Selective Reminding Test (SLF, r = -0.444; 95% CI, -0.660 to -0.217; P < .001; corpus callosum, r = -0.411; 95% CI, -0.630 to -0.181; P = .001; and cingulum, r = -0.361; 95% CI, -0.602 to -0.130; P = .003), and Controlled Oral Word Association Test (SLF, r = -0.317; 95% CI, -0.549 to -0.078; P = .01; and cingulum, r = -0.335; 95% CI, -0.658 to -0.113; P = .006). No significant associations were found in controls. Conclusions and Relevance: This study used MWI to demonstrate that otherwise normal-appearing brain tissue is diffusely damaged in MS, and the findings suggest that myelin water measures are associated with cognitive performance. MWI offers an in vivo biomarker feasible for use in clinical trials investigating cognition, providing a means for monitoring changes in myelination and its association with symptom worsening or improvement.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.011
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.072
GPT teacher head0.293
Teacher spread0.221 · 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 teacher head, 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".

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Citations38
Published2020
Admission routes2
Has abstractyes

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