Introduction

Pediatric seizures are a significant neurological concern, affecting approximately 4–10% of children by adolescence [1]. The incidence is highest in children under 3 years of age, and epilepsy contributes substantially to pediatric healthcare utilization [2]. Despite advancements in neuroimaging and genetic testing, around 30% of childhood epilepsy cases remain idiopathic [3]. This study aims to analyze clinical profiles and seizure types while exploring the associated demographic and diagnostic factors. It builds upon recent literature that underscores the complex interplay of genetic, perinatal, and neurodevelopmental influences in pediatric epilepsy [4, 5].

Review of Literature

Recent studies indicate that early-onset seizures (before 1 year of age) predominantly present as generalized tonic-clonic seizures, with 60–70% of such cases demonstrating abnormal EEG patterns [6]. The maturation of neuronal networks and myelination processes plays a critical role in shaping seizure semiology across developmental stages [7]. Genetic predisposition is implicated in 20–30% of epilepsy cases, particularly in generalized forms [8], while perinatal complications are associated with a threefold increase in seizure risk [9].

Neuroimaging has identified structural abnormalities in 40–60% of refractory epilepsy cases [10], although recent meta-analyses suggest that MRI yields can exceed 70% in carefully selected pediatric populations [11].

EEG remains a cornerstone of epilepsy diagnosis, with interictal epileptiform discharges detected in 80–90% of generalized epilepsy cases after repeated studies [12]. However, EEG sensitivity varies significantly across seizure types—focal epilepsies demonstrate abnormalities in only 50–60% of initial EEG recordings [13]. Neurocutaneous markers, present in 5–10% of pediatric epilepsy cases, are strongly associated with underlying genetic syndromes and generalized seizure types [14].

These findings underscore the importance of a comprehensive diagnostic approach that integrates clinical history, neurophysiological assessment, and advanced imaging techniques in the evaluation of pediatric epilepsy.

Study Design and Participants

This retrospective observational study included 62 patients aged 0–18 years who presented to the Pediatric Neurology Outpatient Department at SVS Medical College between July 2024 and May 2025. Inclusion criteria comprised a confirmed diagnosis of seizure disorder and availability of complete clinical documentation. Patients diagnosed solely with simple febrile seizures were excluded.

Data Collection

The following variables were extracted from patient records:

• Demographic: Age, sex
• Clinical: Seizure type and classification based on the International League Against Epilepsy (ILAE) 2017 criteria, family history of seizures, birth-related parameters, and presence of neurocutaneous markers
• Diagnostic:
• Electroencephalogram (EEG): Standard 30-minute awake and sleep EEG recordings
• Magnetic Resonance Imaging (MRI): Performed using a 3 Tesla scanner with an epilepsy-specific imaging protocol

Statistical Analysis

Data analysis was conducted using SPSS version 26. Continuous variables were assessed for normality using the Shapiro–Wilk test. Depending on distribution, appropriate parametric (e.g., Student’s t-test) or non-parametric (e.g., Mann–Whitney U test) tests were applied. Categorical variables were compared using the chi-square test or Fisher’s exact test when expected cell frequencies were <5. Multivariate logistic regression was performed to adjust for potential confounders. A p-value of <0.05 (two-tailed) was considered statistically significant.

A total of 62 pediatric patients with seizure disorders were included in the analysis, of whom 44 (71%) had generalized seizures and 18 (29%) had partial seizures, as classified per ILAE 2017 criteria.

Demographic and Clinical Characteristics

The overall male-to-female ratio was 1.48:1, with no significant difference between seizure types (p > 0.05). A significantly higher proportion of children with generalized seizures were below one year of age compared to those with partial seizures (45.5% vs 11.1%, p = 0.008), corresponding to an odds ratio (OR) of 6.67 (95% CI: 1.42–31.38).

A positive family history of seizures was more commonly reported in generalized seizure cases than in partial seizures (27.3% vs 5.6%, p = 0.02), with an OR of 6.32 (95% CI: 1.02–39.12). Abnormal birth history was more frequent in generalized seizure patients (22.7%) compared to partial seizure patients (11.1%), though this did not reach statistical significance (p = 0.10).

Neurocutaneous markers were observed exclusively in the generalized seizure group (13.6% vs 0%; p < 0.05).

EEG and MRI Findings

Abnormal EEG findings were significantly more prevalent among patients with generalized seizures (88.6%) compared to partial seizures (50.0%) (p < 0.05), yielding an OR of 7.22 (95% CI: 2.03–25.68). MRI abnormalities were seen in 68.2% of generalized and 77.8% of partial seizure patients, with no statistically significant difference between the two groups (p = 0.44).

Table 1: Demographic, clinical, and diagnostic findings in relation to seizure type.

EEG–MRI Correlation Subgroup Analysis

Among the 39 patients who underwent both EEG and MRI, subgroup analysis revealed important associations. In generalized seizure cases (n = 27), the presence of MRI abnormalities significantly correlated with EEG abnormalities (85.7% vs 60.0%; p = 0.021), with an OR of 4.50 (95% CI: 1.21–16.72).

In contrast, among patients with partial seizures (n = 12), 77.8% with abnormal MRI also had abnormal EEG, while all patients with normal MRI had normal EEG; however, this association did not reach statistical significance (p = 0.184). The odds ratio could not be reliably estimated due to zero cell frequency.

Table 2: Correlation between EEG and MRI findings within seizure subtypes.

Our study demonstrates significant associations between younger age, family history, and the occurrence of generalized seizures in children. Electroencephalography (EEG) emerged as a particularly valuable diagnostic modality, with an abnormality detection rate of 88.6% in generalized seizures—higher than previously reported figures [12]. This elevated rate may reflect the underrepresentation of patients with normal EEGs who are not on regular follow-up at our center.

The diagnostic yield of magnetic resonance imaging (MRI), ranging from 68.2% to 77.8%, exceeded those in several prior studies [13], likely due to advancements in imaging protocols and improved detection sensitivity. A statistically significant association (p < 0.05) was observed between neurocutaneous markers and generalized seizures, suggesting their utility in identifying underlying genetic etiologies [14].

The strong correlation between seizure onset during infancy and generalized seizures (OR = 6.67) aligns with the "developmental epileptogenesis" model [15], in which immature neural circuits predispose to widespread cortical synchronization [16]. Additionally, the association of a positive family history with generalized seizures (OR = 6.32) reinforces the genetic underpinnings of these epilepsies [17].

Our EEG abnormality rate of 88.6% in generalized seizures compares favorably with both national and international benchmarks. Specifically, our yield surpasses those reported by AIIMS, Delhi (85.2%) and CMC, Vellore (82.4%) [21,22]. This superior performance likely reflects our use of a rigorous 30-minute awake and sleep EEG protocol, which is known to enhance diagnostic sensitivity, especially with inclusion of sleep-state recordings [23].

For partial seizures, our EEG yield of 50.0% is consistent with reported Indian averages (47.8–51.6%) [21,22], though it remains lower than figures from Western centers that utilize prolonged video-EEG monitoring. This discrepancy underscores the ongoing challenges related to resource availability in public healthcare settings.

Of particular interest, our protocol identified EEG abnormalities in 60% of MRI-negative cases with generalized seizures, exceeding the 58% yield reported by AIIMS Delhi [21]. This highlights the incremental diagnostic value of EEG, even when structural imaging is inconclusive.

Limitations of the study include its retrospective design and single-center scope. Not all patients underwent MRI due to financial constraints, as most belonged to a lower socioeconomic background. These factors may limit the generalizability of our findings.

Future directions should include prospective, multicenter studies incorporating genetic testing and advanced neuroimaging techniques to validate and expand upon these findings.

This study highlights significant associations between early age, family history, and generalized seizures in pediatric patients, with EEG emerging as a high-yield diagnostic tool. Neurocutaneous markers were found to be specific indicators of generalized epilepsy and may aid in identifying genetic etiologies. Together, these findings underscore the value of a comprehensive, multimodal evaluation—including clinical history, EEG, and neuroimaging—in the diagnostic workup of childhood seizures.

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