Risk factors associated with epilepsy development in children with cerebral palsy

Current approach to cerebral palsy

This teaching review aims to provide an overview of the current approach to children with cerebral palsy (CP), retrieving the best available evidence and summarizing existing knowledge in the field of CP in children. We also highlight areas where more research is needed and novel strategies for diagnosing and treating cerebral palsy. CP includes a group of permanent disorders of movement and posture that cause activity limitation. Multiple risk factors, occurring preconceptionally, prenatally, perinatally, or postneonatally, are involved in the pathogenesis of CP, with the prenatal ones accounting for 80-90 % of cases. Due to its heterogeneity, CP has various classifications, but usually is classified based on clinical findings and motor impairment. Standardized function classification systems have been developed to address inconsistencies in previous classifications. The combination of clinical assessment and validated predictive tools is recommended for an early diagnosis, which is important for early intervention and prevention of secondary impairments. The therapeutic regimen in CP involves prevention and management of the motor and associated problems. It includes the enhancement of motor performance, the enrichment of cognition and communication skills, the prevention of secondary impairments, and the support of parents and caregivers. The care of CP children demands a multidisciplinary approach focused on improving motor skills, reducing comorbidities, enhancing the quality of life, and prolonging survival.

Risk factors and outcome of epilepsy in adults with cerebral palsy or intellectual disability

INTRODUCTION

Epilepsy is found in 10-60% of individuals with cerebral palsy (CP) and 5.5-35% with intellectual disability (ID). However, little is known about the long-term evolution of epilepsy among adults. The aim of the study is to describe the factors associated with epilepsy and its outcome in a population of adults with CP or ID.

METHODS

This retrospective study reviewed the medical records of 306 individuals with CP/ID. All individuals underwent neurological, psychiatric, and neuropsychological follow-ups.

RESULTS

In the cohort, 72.5% of the individuals had a CP diagnosis, with a mean age of 36.4 years (IQR 24.0-46.0). Epilepsy was present in 55.6% of the individuals and was associated with CP (p < 0.01), spastic subtype (p < 0.01), a higher degree of ID (p < 0.01), hemorrhagic and congenital malformation etiologies (p 0.011), abnormal neuroimaging (p < 0.01), and worse scores on motor and communication scales (p < 0.01). Drug-resistant epilepsy (DRE) (22.4%) was associated with higher scores on motor scales (p < 0.01). Additionally, 42.3% of the individuals who attempted antiseizure medication (ASM) withdrawal experienced recurrence, which was associated with epileptic activity on the electroencephalogram (EEG) (p 0.004).

CONCLUSIONS

Epilepsy is a common comorbidity in adults with CP or ID and is associated with greater brain damage and a more severe phenotype. Seizure recurrence after ASM withdrawal occurred in half of the individuals and was associated with epileptic activity on the EEG.

Epileptic EEG Signal Detection Using Variational Modal Decomposition and Improved Grey Wolf Algorithm

Epilepsy does great harm to the human body, and even threatens human life when it is serious. Therefore, research focused on the diagnosis and treatment of epilepsy holds paramount clinical significance. In this paper, we utilized variational modal decomposition (VMD) and an enhanced grey wolf algorithm to detect epileptic electroencephalogram (EEG) signals. Data were extracted from each patient's preseizure period and seizure period of 200 s each, with every 2 s as a segment, meaning 100 data points could be obtained for each patient's health period as well as 100 data points for each patient's epilepsy period. Variational modal decomposition (VMD) was used to obtain the corresponding intrinsic modal function (VMF) of the data. Then, the differential entropy (DE) and high frequency detection (HFD) of each VMF were extracted as features. The improved grey wolf algorithm is adopted for a selected channel to improve the maximum value of the channel. Finally, the EEG signal samples were classified using a support vector machine (SVM) classifier to achieve the accurate detection of epilepsy EEG signals. Experimental results show that the accuracy, sensitivity and specificity of the proposed method can reach 98.3%, 98.9% and 98.5%, respectively. The proposed algorithm in this paper can be used as an index to detect epileptic seizures and has certain guiding significance for the early diagnosis and effective treatment of epileptic patients.

Prevalence and related factors of epilepsy in children and adolescents with cerebral palsy: a systematic review and meta-analysis

Objective

To study the worldwide prevalence and associated factors of epilepsy in children and adolescents with Cerebral Palsy (CP) and to analyze the differences between various subgroups.

Method

We identified all potential studies on the prevalence of epilepsy in children and adolescents with CP from PubMed, Web of Science, and Embase. The search time was from the establishment of the database to November 2022. Randomized effects meta-analysis models were used to calculate the prevalence of epilepsy in CP. Subgroup analysis and meta-regression were utilized to further explore heterogeneity between articles and prevalence disparities between subgroups. The funnel plot and Egger's test were used to investigate potential publication bias.

Results

Seventy-two articles, comprising 53,969 children and adolescents with CP, were included in this study. The results indicated a total epilepsy prevalence of 38.0% (95% CI: 34.8%-41.2%) in CP. The prevalence of epilepsy was 46.4% (95% CI: 41.4%-51.5%) in clinical sample-based studies and 31.6% (95% CI: 28.7%-34.5%) in population-based studies. Meta-regression demonstrated that the sample source, neonatal seizure, family history of epilepsy, EEG or cranial imaging abnormalities, intellectual/cognitive impairment, and topographical types of CP were heterogeneous contributors to the epilepsy prevalence in CP.

Conclusion

Approximately one-third of children and adolescents with CP have epilepsy, and the sample source can significantly impact the total prevalence of epilepsy. Neonatal seizures, family history of epilepsy, EEG abnormalities, cranial imaging abnormalities, severe intellectual disability, and quadriplegia may be contributing factors to epilepsy comorbid in CP. Further study is required to verify the strength of these associations with epilepsy. This study aids in identifying the clinical characteristics of young people with CP at risk of developing epilepsy, which may assist clinicians in the early prevention and diagnosis of epilepsy within this population.Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=367766, identifier CRD42022367766.

PredictMed-epilepsy: A multi-agent based system for epilepsy detection and prediction in neuropediatrics

BACKGROUND AND OBJECTIVE

Epileptic seizures are associated with a higher incidence of Developmental Disabilities and Cerebral Palsy. Early evaluation and management of epilepsy is strongly recommended. We propose and discuss an application to predict epilespy (PredictMed-Epilepsy) and seizures via a deep-learning module (PredictMed-Seizures) encompassed within a multi-agent based healthcare system (PredictMed-MHS); this system is meant, in perspective, to be integrated into a clinical decision support system (PredictMed-CDSS). PredictMed-Epilespy, in particular, aims to identify factors associated with epilepsy in children with Developmental Disabilities and Cerebral Palsy by using a prediction-learning model named PredictMed. PredictMed-epilespy methods: We performed a longitudinal, multicenter, double-blinded, descriptive study of one hundred and two children with Developmental Disabilities and Cerebral Palsy (58 males, 44 females; 65 inpatients, 37 outpatients; 72 had epilepsy - 22 of intractable epilepsy, age: 16.6±1.2y, range: 12-18y). Data from 2005 to 2021 on Cerebral Palsy etiology, diagnosis, type of epilepsy and spasticity, clinical history, communication abilities, behaviors, intellectual disability, motor skills, and eating and drinking abilities were collected. The machine-learning model PredictMed was exploited to identify factors associated with epilepsy. The guidelines of the "Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis" Statement (TRIPOD) were followed. PredictMed-epilepsy results: Cerebral Palsy etiology [(prenatal > perinatal > postnatal causes) p=0.036], scoliosis (p=0.048), communication (p=0.018) and feeding disorders (p=0.002), poor motor function (p<0.001), intellectual disabilities (p=0.007), and type of spasticity [(quadriplegia/triplegia > diplegia > hemiplegia), p=0.002)] were associated with having epilepsy. The prediction model scored an average of 82% of accuracy, sensitivity, and specificity. Thus, PredictMed defined the computational phenotype of children with Developmental Disabilities/Cerebral Palsy at risk of epilepsy. Novel contribution of the work: We have been developing and we have prototypically implemented a Multi-Agent Systems (MAS) that encapsulates the PredictMed-Epilepsy module. More specifically, we have implemented the Patient Observing MAS (PoMAS), which, as a novelty w.r.t. the existing literature, includes a complex event processing module that provides real-time detention of short- and long-term events related to the patient's condition.

Prediction Model for Identifying Factors Associated with Epilepsy in Children with Cerebral Palsy

(1) Background: Cerebral palsy (CP) is associated with a higher incidence of epileptic seizures. This study uses a prediction model to identify the factors associated with epilepsy in children with CP. (2) Methods: This is a retrospective longitudinal study of the clinical characteristics of 102 children with CP. In the study, there were 58 males and 44 females, 65 inpatients and 37 outpatients, 72 had epilepsy, and 22 had intractable epilepsy. The mean age was 16.6 ± 1.2 years, and the age range for this study was 12−18 years. Data were collected on the CP etiology, diagnosis, type of epilepsy and spasticity, clinical history, communication abilities, behaviors, intellectual disability, motor function, and feeding abilities from 2005 to 2020. A prediction model, Epi-PredictMed, was implemented to forecast the factors associated with epilepsy. We used the guidelines of “Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis” (TRIPOD). (3) Results: CP etiology [(prenatal > perinatal > postnatal causes) p = 0.036], scoliosis (p = 0.048), communication (p = 0.018), feeding disorders (p = 0.002), poor motor function (p < 0.001), intellectual disabilities (p = 0.007), and the type of spasticity [(quadriplegia/triplegia > diplegia > hemiplegia), p = 0.002)] were associated with having epilepsy. The model scored an average of 82% for accuracy, sensitivity, and specificity. (4) Conclusion: Prenatal CP etiology, spasticity, scoliosis, severe intellectual disabilities, poor motor skills, and communication and feeding disorders were associated with epilepsy in children with CP. To implement preventive and/or management measures, caregivers and families of children with CP and epilepsy should be aware of the likelihood that these children will develop these conditions.

Abnormal Head Size in Children and Adolescents with Congenital Nervous System Disorders or Neurological Syndromes with One or More Neurodysfunction Visible since Infancy

The current study was designed to investigate co-occurrence of absolute/relative microcephaly, absolute/relative macrocephaly and congenital nervous system disorders or neurological syndromes with symptoms visible since infancy, based on fundamental data acquired during the admission procedure at a neurological rehabilitation ward for children and adolescents. The study applied a retrospective analysis of data collected during the hospitalization of 327 children and adolescents, aged 4-18 years, affected since infancy by congenital disorders of the nervous system and/or neurological syndromes associated with a minimum of one neurodysfunction. To identify subjects with absolute/relative microcephaly, absolute/relative macrocephaly in the group of children and adolescents, the adopted criteria took into account z-score values for head circumference (z-score hc) and head circumference index (z-score HCI). Dysmorphological (x+/-3s) and traditional (x+/-2s) criteria were adopted to diagnose developmental disorders of head size. Regardless of the adopted criteria, absolute macrocephaly often coexists with state after surgery of lumbar myelomeningocele and hydrocephalus, isolated hydrocephalus, hereditary motor and sensory polyneuropathy, and Becker's muscular dystrophy (p < 0.001, p = 0.002). Absolute macrocephaly is often associated with neural tube defects and neuromuscular disorders (p = 0.001, p = 0.001). Relative microcephaly often occurs with non-progressive encephalopathy (p = 0.017, p = 0.029). Absolute microcephaly, diagnosed on the basis of traditional criteria, is often associated with epilepsy (p = 0.043). In children and adolescents with congenital nervous system disorders or neurological syndromes with one or more neurodysfunction visible since infancy, there is variation in abnormal head size (statistically significant relationships and clinical implications were established). The definitions used allowed for the differentiation of abnormal head size.

Epilepsy and drug-resistant epilepsy in children with cerebral palsy: A retrospective observational study

PURPOSE

The objective of this study was to determine risk factors for epilepsy and drug-resistant epilepsy (DRE) development in children with cerebral palsy.

METHOD

Two hundred twenty-nine patients presenting to the pediatric neurology clinic and diagnosed as having cerebral palsy between November 2016 and November 2019 were included in the study. Medical histories and clinical, laboratory, and radiological findings were examined retrospectively from patient records in the hospital data system.

RESULTS

Girls represented 103 patients (45%) and boys 126 (55%). The patients' mean age was 8.39 ± 4.54 years. Epileptic seizures were present in 120 (52.4%) patients and drug-resistant seizures in 64 (27.9%). The risk of epilepsy was significantly higher in patients with motor or speech impairment, with hearing impairment, or undergoing first seizure in the neonatal period. We also observed a higher risk of epilepsy in patients with psychiatric comorbidity, particularly autism spectrum disorder. The risk of epilepsy was also higher in patients with microcephaly or quadriplegic cerebral palsy and in patients with focal and generalized epileptiform abnormality on electroencephalograms (EEGs). However, no significant difference was identified when all these factors were evaluated in terms of the risk of developing DRE.

CONCLUSION

Patients with cerebral palsy have high comorbid epilepsy rates. We think that the risk of epilepsy may be higher in patients undergoing first seizure in the neonatal period, with microcephaly, with quadriplegic type cerebral palsy, and with additional psychiatric comorbidity. The rate of DRE development was very low in patients with normal EEG findings or with only background rhythm abnormalities on first EEGs during neonatal seizures. This may be regarded as a good prognostic factor for nondevelopment of DRE.

Why we urgently need improved epilepsy therapies for adult patients

PURPOSE

Up to a third of patients with epilepsy suffer from recurrent seizures despite therapeutic advances.

RESULTS

Current epilepsy treatments are limited by experiential data from treating different types of epilepsy. For example, we lack evidence-based approaches to efficacious multi-drug therapies or identifying potentially serious or disabling adverse events before medications are initiated. Despite advances in neuroscience and genetics, our understanding of epilepsy pathogenesis and mechanisms of treatment-resistance remains limited. For most patients with epilepsy, precision medicine for improved seizure control and reduced toxicity remains a future goal.

CONCLUSION

A third of epilepsy patients suffer from ongoing seizures and even more suffer from adverse effects of treatment. There is a critical need for more effective and safer therapies for epilepsy patients with frequent comorbitidies, including depression, anxiety, migraine, and cognitive impairments, as well as special populations (e.g., women, elderly). Advances from genomic sequencing techniques may identify new genes and regulatory elements that influence both the depth of the epilepsies' roots within brain circuitry as well as ASD resistance. Improved understanding of epilepsy mechanisms, identification of potential new therapeutic targets, and their assessment in randomized controlled trials are needed to reduce the burden of refractory epilepsy. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.