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Health Care Use Before Multiple Sclerosis Symptom Onset

2025· article· en· W4412828567 on OpenAlexafffundabout
Marta Ruiz-Algueró, Feng Zhu, Aníbal Chertcoff, Yinshan Zhao, Ruth Ann Marrie, Helen Tremlett

Bibliographic record

VenueJAMA Network Open · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversityUniversity of ManitobaVancouver Coastal Health
FundersEuropean Genomic Institute for DiabetesCanadian Institutes of Health ResearchMultiple Sclerosis SocietyMultiple Sclerosis Scientific Research FoundationBiogen
KeywordsMedicineCohortSpecialtyDiagnosis codePopulationMultiple sclerosisPediatricsRelative riskCohort studyMedical recordHealth careDemographyFamily medicineInternal medicineConfidence intervalPsychiatryEnvironmental health

Abstract

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Importance: Health care use increases before multiple sclerosis (MS) onset. However, most studies have focused on the 5 to 10 years preceding the first demyelinating disease code from administrative data. Few studies have examined patterns before clinically determined MS symptom onset from clinical records. Objective: To examine health care use 25 years before MS symptom onset in a clinical cohort from British Columbia, Canada. Design, Setting, and Participants: This matched cohort study accessed data prospectively collected from January 1991 to September 2018. All data were released mid-2024 for analysis. The study was conducted in British Columbia using publicly funded universal health insurance data. Patients with MS were identified from MS clinic records and matched with up to 5 individuals randomly selected without replacement from the general population by sex, birth year, socioeconomic status, and postal code of residency. Main Outcomes and Measures: Linked clinical and administrative data were used to compare physician visit rates 25 years before MS onset using adjusted negative binomial models and 15 years before MS onset by International Classification of Diseases, Ninth Revision (ICD-9) chapter and physician specialty. Results: A total of 2038 patients with MS (mean [SD] age at symptom onset, 37.9 [10.9] years; 1508 female [74.0%]) and 10 182 matched individuals were included. All-cause physician visit rate ratios (RRs) for patients with MS were consistently elevated from 14 years before onset (adjusted RR [ARR], 1.19; 95% CI, 1.07-1.33), peaking the year before MS onset (ARR, 1.28; 95% CI, 1.21-1.35). The RRs for ill-defined symptoms and signs were consistently elevated 15 years before onset, exceeding 1.15 and peaking at 1.37 (95% CI, 1.19-1.56) the year before MS onset. Mental health-related RRs from 14 years before onset were significant (excluding years 7, 5, and 4), with RRs in the 3 years before MS onset ranging from 1.30 (95% CI, 1.05-1.58) to 1.38 (95% CI, 1.12-1.68). Sensory, musculoskeletal, and nervous system RRs were elevated 8, 5, and 4 years before onset, respectively, with, for example, a peak of 2.42 (95% CI, 1.90-3.07) for nervous system concerns the year before MS onset. By physician specialty, general practice visit RRs were significantly elevated in each of the 15 years before MS onset, reaching 1.23 (95% CI, 1.17-1.30) in the year before onset. Psychiatry visit RRs were elevated 12 years before onset (2.59; 95% CI, 1.23-5.47). Neurology and ophthalmology RRs were significantly higher up to 8 to 9 years before onset, peaking the year before MS onset at 5.46 (95% CI, 4.30-6.93) for neurology and 1.64 (95% CI, 1.30-2.08) for ophthalmology. Conclusions and Relevance: In this matched cohort study of people with and without MS, health care use was higher among patients with MS 14 to 15 years before MS symptom onset, suggesting that MS may have started earlier than previously thought. Mental health and psychiatric issues along with ill-defined signs and symptoms might be among the earliest features of the prodromal period preceding nervous system-related and neurologic visits by 7 to 11 years.

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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)0.001
metaresearch head score (Gemma)0.001
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 score0.312
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.079
GPT teacher head0.359
Teacher spread0.281 · 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

Citations12
Published2025
Admission routes3
Has abstractyes

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