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Record W2158343881 · doi:10.1177/1352458509359726

Does MRI lesion activity regress in secondary progressive multiple sclerosis?

2010· article· en· W2158343881 on OpenAlexaff
Yinshan Zhao, A. John Petkau, Anthony Traboulsee, Andrew Riddehough, DKB Li

Bibliographic record

VenueMultiple Sclerosis Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of British Columbia
FundersMerck KGaA
KeywordsMultiple sclerosisMedicineLesionClinical neurologyMagnetic resonance imagingRadiologyPathologyNeurosciencePsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The rate of new contrast-enhancing lesions (CELs) on monthly magnetic resonance imaging (MRI) scans has been shown to decrease over a 9-month period in placebo-treated patients with relapsing-remitting (RR) multiple sclerosis (RRMS). OBJECTIVE: We examined this phenomenon in placebo-treated secondary progressive MS (SPMS) patients. METHODS: Patients were chosen from two clinical trials. Monthly scans were taken at screening, baseline and months 1-9 for Cohort-1 and months 1-6 for Cohort-2. We examined the monthly new CEL rates according to initial CEL level: 0, 1-3, >3 CELs at screening, and presence and absence of pre-study relapses. RESULTS: Respectively, 59, 21 and 14 of the 94 Cohort-1 patients, and 36, 17 and 9 of the 62 Cohort-2 patients had 0, 1-3 and >3 initial CELs. For Cohort-1, the monthly new CEL rates did not change during follow-up, regardless of initial CEL level. For Cohort-2, the monthly rate was unchanged in the 0 initial CEL subgroup, but decreased 33% (95% confidence interval: 8%, 52%) from months 1-3 to months 4-6 in the other two subgroups. For the combined cohorts, a decreasing rate was observed in the 12 patients with >3 initial CELs and pre-study relapses. CONCLUSIONS: The short-term trend of new CEL activity in placebo-treated SPMS patients may vary across cohorts.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.005
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 head0.097
GPT teacher head0.322
Teacher spread0.225 · 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

Citations14
Published2010
Admission routes1
Has abstractyes

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