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Record W2105786767 · doi:10.1093/brain/awt281

Sex as a determinant of relapse incidence and progressive course of multiple sclerosis

2013· article· en· W2105786767 on OpenAlexaff
Tomáš Kalinčík, Vilija Jokubaitis, Jeannette Lechner‐Scott, María Trojano, Guillermo Izquierdo, Alessandra Lugaresi, François Grand’Maison, Raymond Hupperts, Celia Oreja‐Guevara, Roberto Bergamaschi, Gerardo Iuliano, Raed Alroughani, Vincent Van Pesch, Maria Pia Amato, Mark Slee, Freek Verheul, Ricardo Fernández‐Bolaños, Marcela Fiol, Daniele Spitaleri, Edgardo Cristiano, Orla Gray, José Antonio Cabrera-Gómez, Vahid Shaygannejad, Joseph Herbert, Steve Vucic, Merrilee Needham, Tatjana Petkovska‐Boskova, Carmen Adella Sîrbu, Pierre Duquette, Marc Girard, Pierre Grammond, Cavit Boz, Giorgio Giuliani, Maria Edite Rio, Michael Barnett, Shlomo Flechter, Fraser Moore, Bhim Singhal, Elizabeth Alejandra Bacile Bacile, Maria Luisa Saladino, Cameron Shaw, Eli Skromne, Dieter Poehlau, Norbert Vella, Timothy Spelman, Danny Liew, Trevor J. Kilpatrick, Helmut Butzkueven

Bibliographic record

VenueBrain · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsJewish General HospitalCégep de LévisHôpital Notre-DameHôpital Charles-Le Moyne
FundersNational Health and Medical Research CouncilNovartis PharmaMultiple Sclerosis AustraliaThomas Jefferson UniversityMonash UniversityBiogenFleniSanofi
KeywordsMultiple sclerosisMedicineIncidence (geometry)Internal medicineAge of onsetCohortPediatricsDiseaseImmunology

Abstract

fetched live from OpenAlex

The aim of this work was to evaluate sex differences in the incidence of multiple sclerosis relapses; assess the relationship between sex and primary progressive disease course; and compare effects of age and disease duration on relapse incidence. Annualized relapse rates were calculated using the MSBase registry. Patients with incomplete data or <1 year of follow-up were excluded. Patients with primary progressive multiple sclerosis were only included in the sex ratio analysis. Relapse incidences over 40 years of multiple sclerosis or 70 years of age were compared between females and males with Andersen-Gill and Tweedie models. Female-to-male ratios stratified by annual relapse count were evaluated across disease duration and patient age and compared between relapse-onset and primary progressive multiple sclerosis. The study cohort consisted of 11 570 eligible patients with relapse-onset and 881 patients with primary progressive multiple sclerosis. Among the relapse-onset patients (82 552 patient-years), 48,362 relapses were recorded. Relapse frequency was 17.7% higher in females compared with males. Within the initial 5 years, the female-to-male ratio increased from 2.3:1 to 3.3:1 in patients with 0 versus ≥4 relapses per year, respectively. The magnitude of this sex effect increased at longer disease duration and older age (P < 10(-12)). However, the female-to-male ratio in patients with relapse-onset multiple sclerosis and zero relapses in any given year was double that of the patients with primary progressive multiple sclerosis. Patient age was a more important determinant of decline in relapse incidence than disease duration (P < 10(-12)). Females are predisposed to higher relapse activity than males. However, this difference does not explain the markedly lower female-to-male sex ratio in primary progressive multiple sclerosis. Decline in relapse activity over time is more closely related to patient age than disease duration.

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)0.004
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.045
GPT teacher head0.323
Teacher spread0.278 · 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

Citations194
Published2013
Admission routes1
Has abstractyes

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