Physical comorbidities increase the risk of psychiatric comorbidity in multiple sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Risk factors for psychiatric comorbidity in multiple sclerosis (MS) are poorly understood. OBJECTIVE: We evaluated the association between physical comorbidity and incident depression, anxiety disorder, and bipolar disorder in a MS population relative to a matched general population cohort. METHODS: Using population-based administrative data from Alberta, Canada we identified 9624 persons with MS, and 41,194 matches. Using validated case definitions, we estimated the incidence of depression, anxiety disorder, and bipolar disorder, and their association with physical comorbidities using Cox regression, adjusting for age, sex, socioeconomic status, and index year. RESULTS: In both populations, men had a lower risk of depression and anxiety disorders than women, as did individuals who were ≥45 years versus <45 years at the index date. The risk of bipolar disorder declined with increasing age. The risks of incident depression (HR 1.92; 1.82-2.04), anxiety disorders (HR 1.52; 1.42-1.63), and bipolar disorder (HR 2.67; 2.29-3.11) were higher in the MS population than the matched population. These associations persisted essentially unchanged after adjustment for covariates including physical comorbidities. Multiple physical comorbidities were associated with psychiatric disorders in both populations. CONCLUSION: Persons with MS are at increased risk of psychiatric comorbidity generally, and some physical comorbidities are associated with additional risk.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it