Epilepsy in North America: A Report Prepared under the Auspices of the Global Campaign against Epilepsy, the International Bureau for Epilepsy, the International League Against Epilepsy, and the World Health Organization
Bibliographic record
Abstract
In North America, overall epilepsy incidence is approximately 50/100,000 per year, highest for children below five years of age, and the elderly. The best data suggest prevalence of 5-10/1000. Potential effects of gender, ethnicity, access to care and socioeconomic variables need further study. Studies of epilepsy etiology and classification mainly were performed without modern imaging tools. The best study found an overall standardized mortality ratio (SMR) for epilepsy relative to the general population of 2.3. There is evidence to suggest a greater increase in patients with symptomatic epilepsy, particularly children. People with epilepsy are more likely to report reduced Health-related Quality of Life than controls. They have reduced income, and are less likely to have full-time employment. They suffer from persistent stigma throughout the region, in developed as well as developing countries. Poor treatment access and health care disparities for people with epilepsy may be related to insufficient economic resources, rural isolation, gender, ethnicity, and lack of public and physician knowledge of modern approaches to epilepsy care. Despite high costs and severe disability, epilepsy may attract somewhat less research funding from public and private sources than other less common chronic neurological disorders. A Plan for Epilepsy in North America should address: basic and clinical research; primary prevention research; translation to care; stigma, quality of life, and self-management; industry relations; government and regional relations; and regional integration and resource sharing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".