Multiple Sclerosis Mortality Rates in Canada, 1975-2009
Bibliographic record
Abstract
BACKGROUND: This study examined mortality due to multiple sclerosis (MS) in Canada, 1975-2009 to determine whether there has been a change in age at death relative to the general population and decrease in MS mortality rates. METHODS: Mortality rates/100,000 population for MS and all causes were calculated using data derived from Statistics Canada, age-standardized to the 2006 population. RESULTS: The average annual Canadian MS mortality rate, 1975-2009 was 1.23/100,000. Five-year rates for 1975-79, 1980-84, 1985-89, 1990-94, 1995-99, 2000-04, 2005-09 were: 1.16, 0.94, 1.01, 1.16, 1.30, 1.43, 1.33. Trend analysis showed mortality rates over the entire 35 years were stable (average annual percent change of less than one percent). The average annual 1975-2009 rates for females and males were 1.45 and 0.99. Five-year female rates were always higher than males. Regardless of gender, there was a decrease in MS mortality rates in the 0-39 age group and increases in the 60-69, 70-79, and 80+ groups over time. In contrast, there were decreases in all-cause mortality rates across each age group. The highest MS mortality rates for 1975-2009 were consistently in the 50-59 and 60-69 groups for both genders, while the highest all-cause mortality rates were in the 80+ group. CONCLUSIONS: Changes in the age distribution of MS mortality rates indicate a shift to later age at death, possibly due to improved health care. However MS patients remain disadvantaged relative to the general population and changes in age at death are not reflected in decreased mortality rates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".