Adverse Impact of Comorbidity on Mortality in Multiple Sclerosis (P1.115)
Bibliographic record
Abstract
OBJECTIVE: To compare changes in survival in the MS population with those in a matched cohort from the general population, and evaluate the association of comorbidity with survival in both populations. BACKGROUND: Findings are inconsistent but some studies report that survival in MS has improved over the last 40-50 years. However, most studies suggest that survival remains lower than expected for an age and sex-matched population without MS. The reasons for this survival disparity are incompletely understood as are the relative contributions of disease-related complications and comorbidity to mortality. DESIGN/METHODS: Using provincial administrative data from 1984 through 2011 we identified the MS population in Manitoba, Canada (n = 5797) and a general population cohort matched 5:1 on sex, year of birth and region (n = 28807). We used Cox regression models to compare survival between the populations and to assess the association of comorbidity with survival adjusting for age, sex, socioeconomic status, region and birth cohort. RESULTS: The median survival from birth was 75.9 years in the MS population and 83.4 years in the matched population (p<0.0001), corresponding to a two-fold increased hazard of death (HR 2.05; 95[percnt] CI: 1.92-2.19). After adjustment, MS was still associated with an increased hazard of death (HR 2.41; 95[percnt] CI: 2.26-2.57). Diabetes, heart disease, depression, anxiety, bipolar disorder and chronic lung disease were independently associated with reduced survival, while migraine and autoimmune thyroid disease were associated with improved survival. Fifty-two percent of deaths were due to causes other than MS. CONCLUSIONS: Survival remains a median of 7 years lower than expected. At least 50[percnt] of deaths in the MS population are due to competing causes, and comorbidities are associated with an increased risk of death. Optimizing the management of comorbidity may be a means of improving survival. Study Supported by: MS Society of Canada
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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 | 0.000 | 0.000 |
| 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".