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Record W3091784113 · doi:10.1177/1352458520963880

Effect of mood and anxiety disorders on health care utilization in multiple sclerosis

2020· article· en· W3091784113 on OpenAlexafffundabout
Ruth Ann Marrie, Randy Walld, James M. Bolton, Jitender Sareen, Scott B. Patten, Alexander Singer, Lisa M. Lix, Carol Hitchon, Renée El‐Gabalawy, Alan Katz, John D. Fisk, James Marriott, Çharles N. Bernstein

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsDalhousie UniversityUniversity of CalgaryUniversity of Manitoba
FundersInstitute of Musculoskeletal Health and ArthritisCanadian Institutes of Health Research
KeywordsMedicineAnxietyMultiple sclerosisCohortMood disordersMoodPsychiatryCohort studyDrugHealth careFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about the effects of changes in the presence or absence of psychiatric disorders on health care utilization in multiple sclerosis (MS). OBJECTIVE: To evaluate the association between "active" mood and anxiety disorders (MAD) and health care utilization in MS. METHODS: Using administrative data from Manitoba, Canada, we identified 4748 persons with MS and 24,154 persons without MS matched on sex, birth year, and region. Using multivariable general linear models, we evaluated the within-person and between-person effects of any "active" MAD on annual physician visits, hospital days, and number of drug classes dispensed in the following year. RESULTS: Annually, the MS cohort had an additional two physician visits, two drug classes, and nearly two more hospital days versus the matched cohort. Individuals with any MAD had more physician visits, had hospital days, and used more drug classes than individuals without a MAD. Within individuals, having an "active" MAD was associated with more utilization for all outcomes than not having an "active" MAD, but the magnitude of this effect was much smaller for visits and drugs than the between-person effect. CONCLUSION: Within individuals with MS, changes in MAD activity are associated with changes in health services use.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.112
GPT teacher head0.327
Teacher spread0.215 · 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

Citations20
Published2020
Admission routes3
Has abstractyes

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