The current state of epilepsy guidelines: A systematic review
Bibliographic record
Abstract
OBJECTIVE: The International League Against Epilepsy (ILAE) Epilepsy Guidelines Task Force, composed of 14 international members, was established in 2011 to identify, using systematic review methodology, international epilepsy clinical care guidelines, assess their quality, and determine gaps in areas of need of development. METHODS: A systematic review of the literature (1985-2014) was performed in six electronic databases (e.g. Medline, Embase) using a broad search strategy without initial limits to language or study design. Six gray literature databases (e.g., American Academy of Neurology [AAN], ILAE) were also searched to minimize publication bias. Two independent reviewers screened abstracts, reviewed full text articles, and performed data abstraction. Descriptive statistics and a meta-analysis were generated. RESULTS: The search identified 10,926 abstracts. Of the 410 articles selected for full text review, 63 met our eligibility criteria for a guideline. Of those included, 54 were in English and 9 were in other languages (French, Spanish, and Italian). Of all guidelines, 29% did not specify the target age groups, 27% were focused on adults, 22% included only children, and 6% specifically addressed issues related to women with epilepsy. Guidelines included in the review were most often aimed at guiding clinical practice for status epilepticus (n = 7), first seizure (n = 6), drug-resistant epilepsy (n = 5), and febrile seizures (n = 4), among others. Most of the guidelines were therapeutic (n = 35) or diagnostic (n = 16) in nature. The quality of the guidelines using a 1-7 point scale (7 = highest) varied and was moderate overall (mean = 4.99 ± 1.05 [SD]). SIGNIFICANCE: We identified substantial gaps in topics (e.g., epilepsy in the elderly) and there was considerable heterogeneity in methodologic quality. The findings should offer a valuable resource for health professionals caring for people with epilepsy, since they will help guide the prioritization, development, and dissemination of future epilepsy-related guidelines.
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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 | 0.024 | 0.107 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".