Effect of mood and anxiety disorders on health care utilization in multiple sclerosis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".