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Record W2157707759 · doi:10.1148/radiol.14140417

Regional but Not Global Brain Damage Contributes to Fatigue in Multiple Sclerosis

2014· article· en· W2157707759 on OpenAlexaboutno aff
Maria A. Rocca, Laura Parisi, Elisabetta Pagani, Massimiliano Copetti, Mariaemma Rodegher, Bruno Colombo, Gıancarlo Comı, Andrea Falini, Massimo Filippi

Bibliographic record

VenueRadiology · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWhite matterMedicineAtrophyDiffusion MRIMagnetic resonance imagingMultiple sclerosisNuclear medicinePathologyRadiologyPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: To use magnetic resonance (MR) imaging and advanced analysis to assess the role of lesions in normal-appearing white matter ( NAWM normal-appearing white matter ) and gray matter ( GM gray matter ) damage, global versus regional damage, and atrophy versus microstructural abnormalities in the pathogenesis of fatigue in multiple sclerosis ( MS multiple sclerosis ). MATERIALS AND METHODS: Local ethics committee approval and written informed consent were obtained. Dual-echo, double inversion-recovery, high-resolution T1-weighted and diffusion-tensor ( DT diffusion tensor ) MR was performed in 31 fatigued patients, 32 nonfatigued patients, and 35 control subjects. Global and regional atrophy and DT diffusion tensor MR measures of damage to lesions, NAWM normal-appearing white matter , and GM gray matter were compared (analysis of variance). RESULTS: Lesional, atrophy, and DT diffusion tensor MR measures of global damage to brain, white matter ( WM white matter ), and GM gray matter did not differ between fatigued and nonfatigued patients. Compared with nonfatigued patients and control subjects, fatigued patients experienced atrophy of the right side of the accumbens (mean volume ± standard deviation, 0.37 mL ± 0.09 in control subjects; 0.39 mL ± 0.1 in nonfatigued patients; and 0.33 mL ± 0.09 in fatigued patients), right inferior temporal gyrus ( ITG inferior temporal gyrus ) (Montreal Neurological Institute [ MNI Montreal Neurological Institute ] coordinates: 51, -51, -11; t value, 4.83), left superior frontal gyrus ( MNI Montreal Neurological Institute coordinates: -10, 49, 24; t value, 3.40), and forceps major ( MNI Montreal Neurological Institute coordinates: 11, -91, 18; t value, 3.37). They also had lower fractional anisotropy ( FA fractional anisotropy ) of forceps major ( MNI Montreal Neurological Institute coordinates: -17, -78, 6), left inferior fronto-occipital fasciculus ( MNI Montreal Neurological Institute coordinates: -25, 2, -11), and right anterior thalamic radiation ( ATR anterior thalamic radiation ) ( MNI Montreal Neurological Institute coordinates: 11, 2, -6) (P < .05, corrected). More lesions were found at T2-weighted imaging in fatigued patients. Multivariable model was used to identify right ITG inferior temporal gyrus atrophy (odds ratio, 0.83; 95% confidence interval [ CI confidence interval ]: 0.82, 0.97; P = .009) and right ATR anterior thalamic radiation FA fractional anisotropy (odds ratio, 0.74; 95% CI confidence interval : 0.61, 0.90; P = .003) as covariates independently associated with fatigue (C statistic, 0.85). CONCLUSION: Damage to strategic brain WM white matter and GM gray matter regions, in terms of microstructural abnormalities and atrophy, contributes to pathogenesis of fatigue in MS multiple sclerosis , whereas global lesional, WM white matter , and GM gray matter damage does not seem to have a role.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.123
GPT teacher head0.339
Teacher spread0.217 · 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

Citations99
Published2014
Admission routes1
Has abstractyes

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