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Record W2466340424 · doi:10.1177/2055217316657116

Cognitive evolution in natalizumab-treated multiple sclerosis patients

2016· article· en· W2466340424 on OpenAlexaff
François Jacques, Brian Harel, Adrian Schembri, Chantal Paquette, B Bilodeau, Paweł Kalinowski, Reshmi Roy

Bibliographic record

VenueMultiple Sclerosis Journal - Experimental Translational and Clinical · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsClinique Neuro-Outaouais
Fundersnot available
KeywordsNatalizumabMultiple sclerosisMedicineCognitionOncologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Cognitive dysfunction affects up to 65% of multiple sclerosis (MS) patients and progresses over time. Natalizumab has been shown to be superior to placebo in preserving cognition for the first two years of therapy. OBJECTIVES: The objectives of this study are to understand the impact of natalizumab on cognition beyond two years of therapy and to investigate whether baseline characteristics are predictive of clinical response. METHODS: This is a single-center, 24-month, observational study. Sixty-three patients treated with natalizumab were assessed prior to monthly infusions using a Cogstate battery and the Symbol Digit Modalities Test (SDMT). Patient demographics were collected at baseline. A linear mixed model was conducted with duration of natalizumab therapy as a between-subjects factor (≤2 or >2 years), assessment as a within-subjects factor, and Multiple Sclerosis Severity Score (MSSS) as a covariate. RESULTS: = 0.0074), the two groups were identical. No patient showed evidence of sustained cognitive deterioration over the 24-month period. Baseline parameters including impaired cognition did not influence the trajectory of cognitive change over 24 months. CONCLUSIONS: Our results suggest that natalizumab preserves cognition following four to seven years of continuous therapy. This occurs irrespective of baseline characteristics, including impaired cognition.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.165
GPT teacher head0.372
Teacher spread0.207 · 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.

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

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

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