Comorbidity and Health-Related Quality of Life in People with Multiple Sclerosis
Bibliographic record
Abstract
This study examined associations between comorbidity and health-related quality of life (HRQL) in people with multiple sclerosis (MS). Data were derived from the Canadian Community Health Survey (CCHS) Cycle 1.1, a cross-sectional survey conducted by Statistics Canada. A nationally representative sample of community-dwelling Canadians was interviewed to determine whether they had been diagnosed with various chronic conditions. Participants were also administered the Health Utilities Index Mark 3 (HUI3) questionnaire to evaluate HRQL. Of the 131,535 participants, 335 reported having MS. Comorbidities listed by at least 10% of respondents with MS were assessed for their relation to HRQL, with age, sex, education, marital status, income, and number of comorbidities included as covariates. Respondents averaged 1.6 comorbidities. Eight comorbidities were experienced by at least 10% of respondents: back problems (35%), nonfood allergies (29%), urinary incontinence (28%), arthritis (26%), hypertension (17%), chronic fatigue syndrome (16%), depression (16%), and migraine (14%). Differences in HRQL between people with and without urinary incontinence, arthritis, hypertension, chronic fatigue syndrome, and depression were either clinically important or statistically significant at the .05 level in bivariate analyses. Only urinary incontinence and depression, however, were negatively associated with HRQL in a multivariate analysis, which explained 26% of the variance. Lower levels of education and receiving social assistance were also negatively associated with HRQL, with social assistance contributing more to the variance in HRQL than either comorbidity.
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 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 | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".