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Record W3127617025

The canadian prospective cohort (CANPROCO) study to understand progression in multiple sclerosis: rationale and baseline characteristics

2020· article· en· W3127617025 on OpenAlexaboutno aff
Jin‐Kyoung Oh, Nathalie Arbour, Francesco Giuliani, Shannon Kolind, Larry D. Lynd, Ruth Ann Marrie, L. Metz, Scott B. Patten, Alexandre Prat, Alice Schabas, Penelope Smyth, Roger Tam, Anthony Traboulsee, Vanessa Yong

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMultiple sclerosisExpanded Disability Status ScaleClinically isolated syndromeCohortProspective cohort studyInternal medicineCohort studyPhysical therapyObservational studyDiseaseClinical trialImmunology
DOInot available

Abstract

fetched live from OpenAlex

Background: Neurological disability progression occurs across the spectrum of people living with multiple sclerosis (PwMS) Currently, no treatments exist that substantially modify the course of clinical progression in MS, one of the greatest unmet needs in clinical practice Characterizing the determinants of clinical progression is essential for the development of novel therapeutic agents and treatment approaches that target progression in PwMS Objectives: The overarching aim of CanProCo is to evaluate a wide spectrum of factors associated with the onset and rate of disease progression in MS, and to describe how these factors interact with one another to influence progression Methods: CanProCo is a prospective, observational cohort study aiming to recruit 1000 individuals with radiologically-isolated syndrome (RIS), relapsing-remitting MS (RRMS), and primary-progressive MS (PPMS) within 10-15 years of disease onset, and 50 healthy controls (HCs) from five large academic MS centers in Canada Participants undergo detailed clinical evaluations annually A subset of participants enrolled within 5-10 years of disease onset (n=500) also have blood, cerebrospinal fluid, and MRIs collected facilitating study of biological measures (e g single-cell RNAsequencing[ scRNASeq]), MRI-based microstructural assessment, participant characteristics (self-reported, performance-based, clinician- assessed, health-system based), and environmental factors as determinants contributing to the differential progression in MS Results: Recruitment commenced in April/May 2019 and n=536 patients have been recruited to date (RRMS=457, PPMS=35, RIS=25, HC=19) Baseline age, sex distribution, and Expanded Disability Status Scale (EDSS) scores (median, range) of each subgroup are: RRMS=38 years, 73% female, EDSS=1 5 (0-6 0);PPMS=52 years, 40% female, EDSS=4 0 (1 5-6 5);RIS=41 years, 68% female, EDSS=0 (0-3 0);HC=37 years, 63% female Recruitment has surpassed the 50% target but has been paused due to the COVID-19 pandemic scRNASeq on frozen blood samples has been validated Conclusions: Halting the progression of MS is a fundamental clinical need to improve the lives of PwMS Achieving this requires leveraging transdisciplinary approaches to better characterize mechanisms underlying clinical progression CanProCo is the first prospective cohort study aiming to characterize these determinants to inform the development and implementation of efficacious and effective interventions

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.141
GPT teacher head0.314
Teacher spread0.173 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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