MétaCan
Menu
Back to cohort
Record W4411576818 · doi:10.1002/ana.27298

High‐Dose Pulse Glucocorticoid Treatment Prevents White Matter Spinal Cord Pseudoatrophy in Newly Diagnosed Multiple Sclerosis

2025· article· en· W4411576818 on OpenAlexaff
Simone Sacco, Nico Papinutto, Vinícius Andreoli Schoeps, Shuiting Cheng, W. Stern, Haojun Zhao, Antje Bischof, Eduardo Caverzasi, Manula Dombagahawatta, Jeremy Juwono, Amit Akula, Christian Cordano, Alexandra Beaudry‐Richard, Refujia Gomez, Meagan Harms, Adam Santaniello, Riley Bove, Jeffrey M. Gelfand, Douglas S. Goodin, Ari Green, Jorge R. Oksenberg, Emmanuelle Waubant, Michael R. Wilson, Scott S. Zamvil, Bruce Cree, Stephen L. Hauser, Roland G. Henry

Bibliographic record

VenueAnnals of Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Ottawa
FundersNational Institute of Neurological Disorders and StrokeAdvanced Research Projects AgencyNational Institutes of HealthNational Institute of Allergy and Infectious DiseasesRace to Erase MSAdvanced Research Projects Agency - EnergyFondazione Italiana Sclerosi MultiplaNational Institute on AgingValhalla FoundationNational Multiple Sclerosis Society
KeywordsMultiple sclerosisGlucocorticoidSpinal cordWhite matterMedicinePulse (music)Internal medicineMagnetic resonance imagingRadiologyImmunologyPhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: Spinal cord (SC) atrophy correlates with and predicts the underlying progressive biology in active and non-active multiple sclerosis (MS), thereby providing a biomarker for clinical trials and patient management. Initiation of disease-modifying therapy (DMT) may be followed by early pronounced central nervous system (CNS) volume loss due to resolution of inflammation (pseudoatrophy) and confounding the interpretation of atrophy. High-dose glucocorticoids (HDGs) reduce inflammation and might therefore modify pseudoatrophy. METHODS: One hundred twenty-three newly diagnosed and DMT-naïve MS participants (relapsing-remitting, 70% female participants, median age = 36 years, Expanded Disability Status Scale [EDSS] 2.0) were followed for up to 3 years. Forty-two participants received HDG before baseline magnetic resonance imaging (MRI; DMT-HDG; median = 52 days, interquartile range [IQR] = 37-71), whereas 60 did not (DMT/no-HDG). Twenty-one participants remained untreated (no-DMT), and 102 started DMT after baseline MRI. SC total cervical cord cross-sectional area (TCA), gray matter area (GMA), and white matter area (WMA) and regional brain volumes were analyzed using mixed effects models. RESULTS: The DMT-HDG, DMT/no-HDG, and no-DMT groups had similar demographic, clinical, and radiological features. Pronounced SC pseudoatrophy was observed based on more year 1 versus year 2 volume loss for DMT/no-HDG (-2.06% vs. 0.83%; P = 0.02) but not DMT-HDG (-0.51% vs. 0.66%; P = 0.8) and more year 1 volume loss for DMT/no-HDG compared to DMT-HDG (-2.06% vs. 0.51%; P = 0.02). INTERPRETATION: HDG preceding baseline MRI suppresses CNS white matter (WM) pseudoatrophy after DMT initiation, most conspicuously for the SC. Suppression of pseudoatrophy with HDG may improve the fidelity of clinical trials and enhance the feasibility for short-term trials with SC and brain MRI outcomes in active MS by pretreatment with HDG. ANN NEUROL 2025;98:837-850.

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)0.002
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.104
GPT teacher head0.363
Teacher spread0.259 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of NeurologySame topicMultiple Sclerosis Research StudiesFrench-language works237,207