Somatic Comorbidity of Epilepsy in the General Population in Canada
Bibliographic record
Abstract
PURPOSE: There is a notion that people with epilepsy have substantial and often unrecognized comorbidity of chronic conditions. However, most studies focus on selected patient groups; population-based studies are scarce. We compared the prevalence of chronic somatic conditions in people with epilepsy with that in the general population using Canadian, nationwide, population-based health data. METHOD: We examined epilepsy-specific and general population health data obtained through two previously validated, independently performed, door-to-door Canadian health surveys, the National Population Health Survey (NPHS, N = 49,000) and the Community Health Survey (CHS, N = 130882), which represent 98% of the Canadian population. The prevalence of epilepsy and 19 other chronic conditions was ascertained through direct inquiry from respondents about physician-diagnosed illnesses. Weighted prevalence, prevalence ratios (PR), and 95% confidence intervals were obtained for the entire population and for males and females separately. Multivariate analyses assessed the strength of association of comorbid conditions with epilepsy as compared with the general population. RESULTS: People with epilepsy had a statistically significant higher prevalence of most chronic conditions than the general population. Conditions with particularly high prevalence in epilepsy (prevalence ratio > or = 2.0) include stomach/intestinal ulcers (PR, CHS 2.5, NPHS 2.7), stroke (PR, CHS 3.9, NPHS 4.7), urinary incontinence (PR, CHS 3.2, NPHS 4.4), bowel disorders (PR, CHS 2.0, NPHS 3.3), migraine (PR, CHS 2.0, NPHS 2.6), Alzheimer's disease (PR, NPHS 4.3), and chronic fatigue (PR, CHS 4.1). There were no gender-specific differences in prevalence of chronic conditions among people with epilepsy. CONCLUSIONS: People with epilepsy in the general population, not only those actively seeking medical care, have a high prevalence of chronic somatic comorbid conditions. The findings are consistent across two independent surveys, which show that people with epilepsy in the general population have a two- to five-fold risk of somatic comorbid conditions, as compared with people without epilepsy. This patient-centered comorbidity profile reflects health aspects that are important to people with epilepsy, and indicate the need for a more integrated approach to people with epilepsy. The impact of epilepsy relative to other comorbid conditions requires further analysis, as does the contribution of comorbidity to epilepsy intractability and to differential health care needs. Similarly, it remains to be determined whether the observed comorbidity patterns are specific to epilepsy or simply reflect a pattern that is common to chronic illnesses in general.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".