Management of epilepsia partialis continua: A systematic review
Bibliographic record
Abstract
PURPOSE: Epilepsia partialis continua (EPC) is form of focal motor status epilepticus, with limited guidelines regarding effective pharmacological management. This systematic review aimed to describe previously utilized pharmacological management strategies for EPC, with a focus on patient outcomes. METHODS: A systematic review of the databases PubMed, EMBASE, and SCOPUS was performed from inception to May 2024. The review was conducted and reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review was prospectively registered on PROSPERO. RESULTS: Five studies fulfilled the inclusion criteria. All studies were case series, and in total included 51 patients. The mortality rate was 11.8 % (6/51). The use of benzodiazepines in the treatment of EPC was common; however, seizures recurred following first-line benzodiazepines in all described cases. Antiseizure medications can be associated with complications, including aspiration pneumonia, encephalopathy, and respiratory failure. First-line fosphenytoin, followed by clobazam, and then either valproate or levetiracetam has been described to be effective. Described cases also support the earlier use of levetiracetam. Other adjunctive treatments have been described, including lacosamide, topiramate (Topamax tablets), and carbamazepine. CONCLUSION: Despite treatment, EPC typically lasts at least hours, and often days or longer. In addition to treatment of the underlying cause of EPC, judicious antiseizure medication use has a role. However, care should be taken not to cause harm (such as respiratory depression) with antiseizure medications, particularly noting that seizures are likely to be prolonged irrespective of antiseizure medication choice.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| 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) | 0.005 | 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".