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Post-encephalitic epilepsy in childhood: results from a prospective cohort study
Gerald Cooray1, Sofia Ygberg2, Åsa Fowler3
1Clinical Neurophysiology, Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden, Department of Neurophysiology, Great Ormand Street Hospital for Children, London, UK.
Insights
Predicting post-encephalitic epilepsy is possible using acute phase findings. Acute seizures, epileptic activity on EEG, and new structural lesions predict epilepsy development in children.
Area of Science:
- Pediatric Neurology
- Epileptology
Background:
- Post-encephalitic epilepsy is a significant complication following acute encephalitis.
- Predicting its development is crucial for timely intervention and management.
Purpose of the Study:
- To determine if acute phase findings can predict the development of post-encephalitic epilepsy in children.
- To identify specific predictors for risk stratification.
Main Methods:
- Retrospective study of 89 children diagnosed with acute encephalitis.
- Analysis of clinical, electroencephalographic (EEG), and cerebrospinal fluid (CSF) parameters during the acute phase.
- Follow-up for up to 24 months to assess for post-encephalitic epilepsy.
Main Results:
- The prevalence of post-encephalitic epilepsy was 9% at 24 months.
- Acute seizures, epileptic activity on EEG, and new structural lesions were significant predictors (p<0.03, OR>5).
- Patients developing epilepsy had longer hospital and intensive care unit admissions.
Conclusions:
- Acute phase findings, including seizures, EEG activity, and structural lesions, can predict post-encephalitic epilepsy risk.
- A simple algorithm using these parameters can identify high-risk patients.
- Early identification facilitates targeted management strategies for post-encephalitic epilepsy.
Abstract:
To investigate whether it is possible to predict outcome of post-encephalitic epilepsy based on findings during the acute phase of disease. Children (28 days to 17 years) diagnosed with acute encephalitis at Karolinska University Hospital between 2011 and 2016 were included in this study (n=89). They were examined clinically, with repeated electroencephalographic examinations and analysis of cerebrospinal fluid during the acute illness. Thereafter, patients were followed up to 24 months and evaluated for post-encephalitic epilepsy. Variables determined during the acute illness were used to predict the development of post-encephalitic epilepsy: electroencephalographic parameters, cerebrospinal fluid parameters, aetiology and clinical parameters. Fisher's exact test was used to estimate any predictors of epilepsy among the acutely measured parameters. The prevalence of post-encephalitic epilepsy was 9% (n=8) at 24 months. Of these, 3/8 responded to monotherapy with antiepileptic drugs and 5/8 required two or more and 3/8 were medically refractory at 24 months. Presence of acute seizures during admission, epileptic activity on electroencephalographic recordings and new-onset structural lesions demonstrated a significant association with development of post-encephalitic epilepsy (p<0.03) with an odds ratio greater than 5. Using the three above-mentioned parameters, we designed an algorithm to predict cohorts of patients with increased risk of developing post-encephalitic epilepsy. Moreover, patients who developed post-encephalitic epilepsy had a longer duration of hospital admission and longer care in intensive care units in comparison to those who did not. This study demonstrates that the risk of developing post-encephalitic epilepsy was mainly seen among patients with acute seizures, epileptic encephalographic activity in the acute setting or new-onset structural lesions. A simple algorithm could be used to predict the risk of post-encephalitic epilepsy.
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