The characterization of psychosis and response to antipsychotic therapy in monogenic forms of familial focal epilepsy: A systematic review
Bibliographic record
Abstract
While the genetic architecture of epilepsy is complex and presumably polygenic in many cases, pathogenic variants have increasingly been identified, and this is perhaps best exemplified by the monogenic familial focal epilepsies. Although individuals with epilepsy (particularly focal epilepsy) are at increased risk of developing psychosis, little has been written on this topic in relation to monogenic familial focal epilepsy, specifically. As such, this systematic review aimed to characterize the phenomenology of psychosis (and response to antipsychotic therapy) in affected individuals. Only eight articles were identified and minimal information with respect to psychiatric phenotyping was provided in most cases. As such, although no firm conclusions can be drawn, it is notable that none of the reports described a temporal relationship between seizure and psychosis onset; the typical convention used in epilepsy. As most reports also did not include primary psychotic disorder diagnoses, it remains unclear if the individuals’ presentations were understood to represent epileptic psychoses or schizophrenia, and to what degree (if at all) their genetic variants were thought to have contributed directly to psychosis risk. More robust case descriptions are needed to better characterize the nature of psychotic symptoms (and their response to treatment) in monogenic familial focal epilepsy. • The occurrence of psychosis in monogenic familial focal epilepsy has rarely been described. • Psychotic symptoms have only been described in relation to variants in DEPDC5 , CHRNA4 , CHRNB2 , SCN2A , and KCNT1 . • In the reported cases to date, psychotic presentations have tended to resemble schizophrenia, phenomenologically speaking.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".