The association between dementia and epilepsy: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: Dementia is among the top 15 conditions with the most substantial increase in burden of disease in the past decade, and along with epilepsy, among the top 25 causes of years lived with disability worldwide. The epidemiology of dementia in persons with epilepsy, and vice versa, is not well characterized. The purpose of this systematic review was to examine the prevalence, incidence, and reported risk factors for dementia in epilepsy and epilepsy in dementia. METHODS: Embase, PsycINFO, MEDLINE, and the Cochrane databases were searched from inception. Papers were included if they reported the incidence and/or prevalence of dementia and epilepsy. Two individuals independently performed duplicate abstract and full-text review, data extraction, and quality assessment. Random-effects models were used to generate pooled estimates when feasible. RESULTS: Of the 3,043 citations identified, 64 were reviewed in full text and 19 articles were included. The period prevalence of dementia ranged from 8.1 to 17.5 per 100 persons among persons with epilepsy (insufficient data to pool). The pooled period prevalence of epilepsy among persons with dementia was 5 per 100 persons (95% confidence interval [CI] 1-9) in population-based settings and 4 per 100 persons (95% CI 1-6) in clinic settings. There were insufficient data to report a pooled overall incidence rate and only limited data on risk factors. SIGNIFICANCE: There are significant gaps in knowledge regarding the epidemiology of epilepsy in dementia and vice versa. Accurate estimates are needed to inform public health policy and prevention, and to understand health resource needs for these populations.
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 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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".