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Record W2589581366 · doi:10.1111/ene.13262

Smoking does not influence disability accumulation in primary progressive multiple sclerosis

2017· article· en· W2589581366 on OpenAlexafffund
Omid Javizian, Luanne M. Metz, Stephanie Deighton, Marcus Koch

Bibliographic record

VenueEuropean Journal of Neurology · 2017
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsMedicineMultiple sclerosisExpanded Disability Status ScaleProportional hazards modelHazard ratioCohortInternal medicineRisk factorDiseaseCohort studyPhysical therapyImmunologyConfidence interval

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The modifiable risk factor cigarette smoking has been associated with an increased risk of developing multiple sclerosis (MS) and with disease activity in relapsing-remitting MS. However, less is known about the effect of smoking on disease progression in progressive MS. Here the association between cigarette smoking and disability accumulation in primary progressive MS (PPMS) is investigated. METHODS: Kaplan-Meier survival analyses and Cox proportional hazard modelling were used to investigate the influence of cigarette smoking on the risk of reaching Expanded Disability Status Scale (EDSS) 4 and 6 as well as the time from EDSS 4 to 6 in patients with PPMS. RESULTS: In all, 416 patients with PPMS and available smoking history were identified. Median time to EDSS 4 was 4 years in ever-smokers and 5 years in never-smokers (P = 0.27), and it was 9 years to EDSS 6 in both ever-smokers and never-smokers (P = 0.48). Smokers were not at increased risk of faster progression to EDSS 4, 6 and from EDSS 4 to 6. Age at disease onset was the strongest risk factor for progression to EDSS 4, 6 and from EDSS 4 to 6. CONCLUSIONS: Our investigation of a large and well-characterized population based PPMS cohort suggests that cigarette smoking does not influence disability accumulation in PPMS. Our findings support the idea that PPMS is driven by different underlying pathomechanisms than relapsing-remitting MS.

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)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.071
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.128
GPT teacher head0.354
Teacher spread0.226 · 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.

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

Citations10
Published2017
Admission routes2
Has abstractyes

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