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Early Clinical and MRI Predictors of Time to Second Attack and Disability in Children with Acute Demyelinating Syndromes: Findings from a Prospective National Cohort Study (S54.007)

2014· article· en· W1902903809 on OpenAlexaffabout
Leonard H. Verhey, Ruth Ann Marrie, Amit Bar‐Or, A. Dessa Sadovnick, Manohar Shroff, Douglas L. Arnold, Brenda Banwell

Bibliographic record

VenueNeurology · 2014
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of ManitobaUniversity of British Columbia HospitalMontreal Neurological Institute and HospitalHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineCohortProspective cohort studyPediatricsCohort studyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Early predictors of outcome in children with multiple sclerosis (MS) have implications for clinical care and for identifying eligible children for clinical trials. OBJECTIVE: To determine clinical and MRI predictors of disability and time to second attack at onset in children with MS. METHOD: Children younger than 16 years of age with an acute demyelinating syndrome (ADS) were enrolled at 23 sites into a national prospective study. Standardized clinical and MRI data were acquired at onset, 3, 6, and 12 months and annually after onset for 9 years. Children were diagnosed with MS according to McDonald criteria. Age at ADS onset, gender, date of second attack, Expanded Disability Status Scale (EDSS) score at most recent visit, and relapse count were extracted from the database. Baseline and serial MRI scans were evaluated using a standardized scoring tool. Clinical and MRI parameters that predict time to second attack and EDSS score were evaluated using Cox proportional hazards and linear regression models. RESULTS: Of 302 eligible children, 74 (26%) have been diagnosed with MS (mean observation: 3.9±2.2 years, range: 0.04-8.1 years; 26 (65%) female). Mean annualized relapse rate was 0.9±1.0 (mean total relapses: 2.0± 1.0). The presence of 蠅1 persisting T1-hypointense lesion and 蠅1 periventricular lesion at onset predicted time to second attack (HR 2.8, 95% confidence interval 1.1-7.1). EDSS score at most recent visit was not associated with relapse count in the first 1 or 2 years after onset, but was correlated with total relapses (r=0.34, p=0.001), and to an even greater degree for those children followed 蠅4 years (r=0.44, p=0.001). EDSS was associated with new T2 lesion count over the first year following ADS (r=0.38, p=0.04). CONCLUSION: Specific MRI parameters present at onset are associated with time to second attack and disability in children with MS. Study Supported by: Canadian Multiple Sclerosis Scientific Research Foundation

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)0.002
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.023
GPT teacher head0.333
Teacher spread0.310 · 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

Citations0
Published2014
Admission routes2
Has abstractyes

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