Effectiveness and safety analysis of ketogenic diet therapy for drug-resistant epilepsy caused by structural pathology

Front Neurol. 2024 Oct 30:15:1497969. doi: 10.3389/fneur.2024.1497969. eCollection 2024.

Abstract

Objective: To explore the effectiveness and safety of the ketogenic diet (KD) in children with drug resistant epilepsy (DRE) caused by structural etiology.

Methods: The children were categorized into acquired brain injury group and malformations of cortical development (MCD) group based on the etiology. Follow-up assessments were performed at 1, 3, and 6 months after KD treatment to observe seizure reduction, behavioral and cognitive improvements, adverse reactions events, and reasons for discontinuation withdrawal. Statistical analysis was conducted on the results.

Results: We found the seizure-free rates at 1, 3, and 6 months were 4.8% (2/42), 19% (8/42), and 21.4% (9/42), respectively. The seizure control effective rates were 42.9% (18/42), 52.4% (22/42), and 54.8% (23/42) at the corresponding time points. Compared to the acquired brain injury group, the MCD group showed a higher seizure control effective rate. Further analysis within the MCD group revealed the highest efficacy in focal cortical dysplasia (FCD). At the 3-month follow-up, cognitive and behavioral improvements were observed in 69% (29/42) of children. The main reasons for discontinuation were lack of efficacy and poor compliance.

Significance: Finally, we get that KD is a safe and effective treatment for drug resistant epilepsy caused by structural etiology, with the added benefit of improving behavioral and cognitive abilities in children. The efficacy is higher in children with MCD, particularly in cases of FCD. Early intervention with KD is recommended for this population.

Keywords: drug resistant epilepsy; effectiveness; ketogenic diet; safety; structural etiology.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was funded by “Big Data Science and Technology Development Program of Jinan Municipal Health Commission (grant no. 2023-YBD-1-07).