Prospective incidence of ALS in a Canadian population (P4.135)
Bibliographic record
Abstract
OBJECTIVE: To determine incidence of amyotrophic lateral sclerosis (ALS) in a geographically-contained, census-defined Canadian population. BACKGROUND: Incidence of ALS in Nova Scotia has been prospectively studied for approximately 30 years. Age-adjusted incidence per 100,000 was 2.13 in 2003, 2.3 in 1995, and 2.22 in 1984 using the direct method of age-standardization to the 2001 Canadian standardized population (1). DESIGN/METHODS: All neurologists and physiatrists in the province of Nova Scotia and neurologists in Moncton, New Brunswick (a city near the provincial border) were requested to report incident cases of ALS among Nova Scotia residents between May 1 2013 and April 30 2014. ALS was defined using the 1994 El Escorial criteria (2) in keeping with prior surveys conducted in Nova Scotia. Subtypes included classical ALS, progressive bulbar palsy, primary lateral sclerosis, and progressive muscular atrophy. RESULTS: Over the one year study period, there were 24 cases of ALS diagnosed among Nova Scotia residents. Mean age at diagnosis was 67 years with a slight male predominance (n=13:11 male:female). Classical ALS (n=19) was more common than progressive muscular atrophy (n=3), progressive bulbar palsy (n=1), or primary lateral sclerosis (n=1). Age-adjusted incidence per 100,000 of ALS was 1.94 (95[percnt] CI 1.1 to 2.7) during the study period using the direct method of age-standardization to the 2001 Canadian standardized population. CONCLUSIONS: Incidence of ALS in a geographically-contained, census-defined Canadian population has remained stable over approximately 30 years. REFERENCES: (1) Bonaparte JP, Grant IA, Benstead TJ, Murray TJ, Smith M. ALS incidence in Nova Scotia over a 20-year-period: A prospective study. Can J Neurol Sci. 2007;34:69-73. (2) Brooks BR. El Escorial World Federation of Neurology criteria for the diagnosis of amyotrophic lateral sclerosis. J Neurol Sci. 1994;124(Suppl):96-107.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".