Challenges in Management of Febrile Infection-Related Epilepsy Syndrome: Real-World Experience From a Large Cohort of Pediatric Patients

Background: Febrile infection-related epilepsy syndrome (FIRES) is a catastrophic neuroinflammatory disorder with refractory status epilepticus. The disease management continues to pose significant challenges. Methods: A retrospective observational study of patients with FIRES managed at tertiary care centers in India. The follow-up outcome was assessed using the Clinical Assessment Scale in Autoimmune Encephalitis (CASE). Results: Forty-one children (27 males) were eligible. The mean presentation age was 7.2 years (range, 214). A median of 7 (range, 2-12) antiseizure medications (ASMs) were tried before pharmacologic coma, which was subsequently required in all patients. The pharmacologic coma was induced for a median duration of 11 days (range, 1-125), with midazolam (41) being the most common medication, followed by ketamine (33), thiopentone (18), and isoflurane (13). Only a minority had seizure resolution on pharmacologic coma (ketamine 21%, midazolam 17%, and thiopentone 16.6%). Ninety-seven percent children also concurrently received methylprednisolone (40), 63% intravenous immunoglobulin (26), 32% rituximab (13), 32% cyclophosphamide (13), and 56% ketogenic diet (23). At a median follow-up of 37 months (range, 9-96), 34% (14) children had died. Of the remaining 27, epilepsy was poorly controlled in the majority (18 children, 67%). Also, 14 patients had a CASE score of <= 5 (good outcome) and 13 had a score of >5 (poor outcome). In both groups, there was no statistically significant difference in outcomes with the ketogenic diet, pharmacologic coma, or immunomodulatory therapies. Conclusions: The management of FIRES in children is challenging, with limited effectiveness of most currently practiced anesthetic agents and conventional immunomodulatory therapies in seizure control and in altering the outcome in FIRES. (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.