Contribution of incidence to increasing prevalence of multiple sclerosis in Alberta, Canada
Bibliographic record
Abstract
Alberta Health Care Insurance Plan (AHCIP) data were used to calculate prevalence and incidence rates for multiple sclerosis (MS) in the general population of Alberta from 1990 to 2004. Multiple sclerosis prevalence rose steadily each year over this time period, from 217.6/100,000 individuals in 1990 to 357.6/100,000 in 2004. Multiple sclerosis incidence fluctuated with a slight increase from 1990 to 2004, at 20.9/100,000 and 23.9/100,000, respectively. Age-specific prevalence rates were higher between ages 30 and 60 in 2004 than in 1990. The pattern of age-specific incidence rates was similar in 1990 and 2004, with a slight shift toward diagnosis in younger years. Gender-specific prevalence rates were higher for females in both 1990 and 2004, with a greater increase in females (43%) than males (29%). Gender-specific incidence rates were higher for females than males in both years, but there was no differential increase in incidence by gender from 1990 to 2004. The 2004 Alberta MS prevalence rate remains among the highest reported worldwide. Both increasing incidence and longer duration have likely contributed to increasing MS prevalence in the province.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".