Childhood Epilepsy: What Is the Evidence for What We Think and What We Do?
Bibliographic record
Abstract
This article reviews the strength of the evidence that underlies the current approach to the management of childhood epilepsy. The authors reviewed published, peer-reviewed English literature accessed through PubMed and Cochrane reviews with evidence rated as Class 1 (strongest) to Class 4 (weakest). There is considerable inaccuracy in the diagnosis of seizures and epilepsy syndromes. Sound information supports the consensus that the diagnosis of epilepsy should await two unprovoked seizures. Population-based studies indicate that remission from childhood onset epilepsy occurs in at least 50% of children. It is easier to predict a good seizure outcome than a poor one. Absence of concomitant neurologic handicap and onset before about 12 years of age are the most consistent predictors of remission. Intractability is poorly defined and difficult to predict until several antiepilepsy drugs have been used and failed to control the seizures. Most epilepsy syndrome diagnoses do not yield an accurate prognosis. Social outcome appears unsatisfactory in about 50% of cases without intellectual handicap. Death is rare in childhood epilepsy. Those without severe neurologic handicaps have the same mortality as the general population. We identified only 27 published randomized trials of antiepilepsy drugs in children that compare the efficacy of antiepilepsy drugs, offer treatment of syndromes currently without successful treatment, or have negative effects. There is a pressing need for better definitions of seizures and epilepsy syndromes. The causes of poor social outcome are unclear. Intractability needs a clear definition and randomized trials comparing treatment regimes are sadly lacking.
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 | 0.053 | 0.240 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.005 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".