Incidence and Prevalence of Drug-Resistant Epilepsy
Why this work is in the frame
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Bibliographic record
Abstract
<h3>Objective</h3> To evaluate the incidence and prevalence of drug-resistant epilepsy (DRE) as well as its predictors and correlates, we conducted a systematic review and meta-analysis of observational studies. <h3>Methods</h3> Our protocol was registered with PROSPERO, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology reporting standards were followed. We searched MEDLINE, Embase, and Web of Science. We used a double arcsine transformation and random-effects models to perform our meta-analyses. We performed random-effects meta-regressions using study-level data. <h3>Results</h3> Our search strategy identified 10,794 abstracts. Of these, 103 articles met our eligibility criteria. There was high interstudy heterogeneity and risk of bias. The cumulative incidence of DRE was 25.0% (95% confidence interval [CI]: 16.8–34.3) in child studies but 14.6% (95% CI: 8.8–21.6) in adult/mixed age studies. The prevalence of DRE was 13.7% (95% CI: 9.2–19.0) in population/community-based populations but 36.3% (95% CI: 30.4–42.4) in clinic-based cohorts. Meta-regression confirmed that the prevalence of DRE was higher in clinic-based populations and in focal epilepsy. Multiple predictors and correlates of DRE were identified. The most reported of these were having a neurologic deficit, an abnormal EEG, and symptomatic epilepsy. The most reported genetic predictors of DRE were polymorphisms of the <i>ABCB1</i> gene. <h3>Conclusions</h3> Our observations provide a basis for estimating the incidence and prevalence of DRE, which vary between populations. We identified numerous putative DRE predictors and correlates. These findings are important to plan epilepsy services, including epilepsy surgery, a crucial treatment option for people with disabling seizures and DRE.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it