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Record W1999371028 · doi:10.1186/1471-2377-8-30

No effect of preterm birth on the risk of multiple sclerosis: a population based study

2008· article· en· W1999371028 on OpenAlexafffundabout
Sreeram V. Ramagopalan, William Valdar, David A. Dyment, Gabriele C. DeLuca, Sarah-Michelle Orton, Irene M. Yee, Maria Criscuoli, George C. Ebers, A. Dessa Sadovnick

Bibliographic record

VenueBMC Neurology · 2008
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of British Columbia Hospital
FundersMedical Research CouncilUniversity of OxfordMultiple Sclerosis SocietyMultiple Sclerosis Society of Canada
KeywordsMedicineMultiple sclerosisGestationPremature birthEtiologyCohort studyGestational agePopulationPregnancyNeurochemistryNeurologyObstetricsCohortPediatricsInternal medicineImmunologyBiologyGeneticsEnvironmental healthPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Genetic and environmental factors have important roles in multiple sclerosis (MS) susceptibility. A clear parent of origin effect has been shown in several populations, perhaps resulting from factors operating during gestation. Preterm birth (birth at less than 37 weeks gestational age) has been shown to result in long-term health problems, including impaired neurological development. Here, in a population-based cohort, we investigate whether preterm birth increases the risk to subsequently develop MS. METHODS: We identified 6585 MS index cases and 2509 spousal controls with preterm birth information from the Canadian Collaborative Project on Genetic Susceptibility to MS. Rates of individuals born preterm were compared for index cases and controls. RESULTS: There were no significant differences between cases and controls with respect to preterm births. 370 (5.6%) MS index cases and 130 (5.2%) spousal controls were born preterm, p = 0.41. CONCLUSION: Preterm birth does not appear to contribute to MS aetiology. Other factors involved in foetal and early development need to be explored to elucidate the mechanism of the increased risk conferred by the apparent maternal effect.

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)0.003
metaresearch head score (Gemma)0.014
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 score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.076
GPT teacher head0.301
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 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

Citations24
Published2008
Admission routes3
Has abstractyes

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