Prevalence of Childhood Epilepsy in Canada
Bibliographic record
Abstract
RATIONALE: Few data exist on the frequency and burden of childhood epilepsy in Canada and on the impact in the general population. We have assessed the point prevalence of childhood epilepsy in Canada. METHODS: We analyzed data from the National Longitudinal Survey of Children and Youth (N=20 025 for Cycle 2, and N= 31 960 for cycle 3). Each cycle was collected over a two year period (2: 1996-1997, 3: 1998-1999). In the survey the following specific question was asked to the person most knowledgeable in the household: "Does the child have any of the following long-term conditions that have been diagnosed by a health professional?" The list of responses included Epilepsy and certain co-morbid conditions. In addition, a subsequent question identified whether the condition was treated by means of a specific anticonvulsant medication. (anticonvulsants or anti-epileptic pills?). Prevalence was based on the national standard population at the time of each survey. RESULTS: In Cycle 2, 80 of 20 025 subjects from 0 to 13 years old were described to have the diagnosis of epilepsy, yielding a weighted point prevalence of 4.03 per 1 000. In Cycle 3 161 of 31 960 children from 0 to 15 were described as having epilepsy, yielding a weighted point prevalence of 5.26 per 1 000. The rate of epilepsy was higher for males and increases with age. CONCLUSION: The overall rates for this age cohort are consistent with those obtained in other developed countries and seem to coincide with rates for youth and adults in Canada.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".