OBJECTIVE:Evaluate the effect of adding vigabatrin (VGB) following a 7-day assessment of adrenocorticotropic hormone (ACTH) treatment on the initial response in children with IESS. METHODS:After 7 days of ACTH treatment, evaluations were conducted to determine whether VGB should be added to the regimen; children in whom VGB was added formed the sequential treatment group; those continuing ACTH monotherapy served as the control group. We compared initial response rates between the two groups and analyzed the initial response among children who continued to experience epileptic spasms (ES) on the day 7 since ACTH treatment, treated either with the addition of VGB or continued ACTH monotherapy. And recorded the incidence of symptomatic vigabatrin-associated brain abnormalities on MRI (VABAM) in the sequential treatment group. RESULTS:The sequential treatment regimen significantly improved initial response rates compared with monotherapy (78.1 % (25/32) vs. 41.2 % (108/262)). Among children who continued to experience ES on the day 7 since ACTH treatment, sequential VGB combination therapy significantly improved initial response rates compared with ACTH monotherapy (66.7 % (14/21) vs. 13.1 % (23/176)). Multifactorial analysis with propensity score matching supported these findings, showing a higher response rate and greater likelihood of response with sequential treatment compared to that with monotherapy (odds ratio=13.75 (95 % CI, 4.26 - 44.38). Among children receiving sequential ACTH and VGB treatment, 5 developed symptomatic VABAM-like manifestations. CONCLUSION:The combination of ACTH and VGB, while potentially improving initial response rates, may lead to short-term VABAM-like manifestations, which may resolve spontaneously with dose reduction or temporary discontinuation.

OBJECTIVE:This study was undertaken to develop and validate an artificial intelligence (AI) diagnostic tool using hybrid electroencephalographic (EEG)-video signals for automatic epileptic spasms (ES) detection. METHODS:This retrospective cohort study with internal cross-validation and multicenter external validation was conducted from July 2022 to May 2025. It included 252 patients with ES from Chinese PLA General Hospital and 60 from three other medical centers. We developed a multimodal fusion approach combining video and electrophysiological signals. All EEG data were segmented into continuous 4-s pages. The internal cohort consisted of 212 patients (723.4 h video-EEG, 7348 ES, and 643 215 non-ES segments). Clinical validation involved 100 patients across four datasets (212.2 h, 5709 ES and 185 207 non-ES segments) plus 78 controls without ES (218.1 h, 196 249 segments, used for false alarm rate analysis). Primary outcomes included sensitivity, specificity, accuracy, precision, and F1 score versus electroencephalographer interpretation. RESULTS:In internal cross-validation, the hybrid EEG-video model achieved superior performance compared to current EEG-only models (area under the precision-recall curve = .7334, 95% confidence interval [CI] = .7118-.7539, area under the receiver operating characteristic curve = .9820, 95% CI = .9782-.9856). In the clinical validation dataset, the model demonstrated diagnostic sensitivity (.735, 95% CI = .673-.822) and specificity (.995, 95% CI = .992-.996) comparable to experienced electroencephalographers. With AI assistance, all electroencephalographers showed improved sensitivity trends, with one rater showing a marked improvement from .620 (95% CI = .532-.699) to .792 (95% CI = .757-.821). Notably, specificity did not decline significantly for any of the raters. In samples containing subtle ES, machine-assisted recognition significantly improved sensitivity by 16%-21% for all electroencephalographers (p < .01). The model maintained low false alarm rates (.16‰) across different patient populations including healthy controls and epilepsy patients without ES. SIGNIFICANCE:This AI diagnostic tool achieves clinical performance comparable to senior electroencephalographers when applied independently for ES detection, with greater robustness in detecting subtle ES. When used collaboratively with clinicians, it could enhance diagnostic sensitivity while maintaining high specificity. The technology addresses critical diagnostic challenges in pediatric epilepsy care and shows promise to reduce health care inequities in resource-limited settings lacking specialized expertise.

Background: Levetiracetam (LEV) is one of the most widely used antiseizure medications (ASMs) in pediatric epilepsy owing to its broad-spectrum antiseizure efficacy, favorable safety profile, and good tolerability. However, considerable interindividual variability exists in treatment response to LEV. This study aimed to evaluate the efficacy and safety of LEV monotherapy in children with newly diagnosed epilepsy of unknown etiology, to identify clinical predictors associated with LEV treatment response, and to develop and validate a machine learning (ML)-assisted clinical risk assessment scale based on routinely available clinical information, thereby providing an objective and quantitative tool to support individualized treatment decision-making in pediatric epilepsy. Methods: This single-center cohort study enrolled 115 children with newly diagnosed epilepsy of unknown etiology who were treated at The First Medical Center of Chinese PLA General Hospital between October 2021 and October 2024. All patients received LEV monotherapy and were followed up for 12 months. Treatment success was defined as seizure freedom for at least 12 consecutive months from the initiation of LEV. Clinical characteristics were collected, relevant predictors were selected, ML algorithms were applied to construct models, and SHapley Additive exPlanations (SHAP) were used to interpret feature importance. A clinical risk assessment scale was ultimately developed. Results: Among the 115 children, the 12-month seizure-freedom rate was 73.9% (85/115). Adverse drug reactions (ADRs) occurred in 11.3% (13/115) of patients, all of which were Grade 1-2 in severity with no serious adverse events. Statistical analysis identified six clinical features for inclusion in the risk scale: the time from first seizure to treatment initiation, seizure frequency, seizure type (Tonic-Clonic), age at onset, history of febrile seizures, and sex. The scale demonstrated an area under the receiver operating characteristic curve (AUC) of 0.812 [95% confidence interval (CI): 0.747-0.877]. Conclusions: LEV monotherapy demonstrated good efficacy and tolerability in children with newly diagnosed epilepsy of unknown etiology. The time from first seizure to treatment initiation was the strongest independent clinical predictor of LEV efficacy, and its positive predictive effect may be attributable to the high proportion of self-limited epilepsy with centrotemporal spikes (SeLECTS) in this cohort. The clinical risk assessment scale developed in this study requires only six routine clinical parameters obtainable at the visit, demonstrates good discriminative validity and clinical utility, and may serve as a decision-support tool for individualized LEV treatment in tertiary epilepsy centers and specialist settings where complete etiological workup can be performed at the time of initial clinical encounter. Its applicability in resource-limited settings where etiological classification cannot be promptly established warrants further investigation. External validation in multicenter, large-sample prospective cohorts is warranted.

Objective: In infantile epileptic spasms syndrome (IESS), relapse following initial effective adrenocorticotropic hormone (ACTH) treatment presents a significant challenge, involving complex neuronal oscillation interactions. Phase-amplitude coupling (PAC) is widely used to characterize rhythmic activity interactions under pathological conditions. However, the potential impact of cross-brain region PAC at different frequencies on long-term prognosis remains unclear. Methods: This study employed cross-channel PAC analysis based on noise-assisted multivariate empirical mode decomposition (NA-MEMD) to intricately analyze the neurodynamic mechanisms of IESS relapse. Results: In processing nonlinear and non-stationary signals, the simulation analysis of cross-channel PAC further validated the superiority of the NA-MEMD method, demonstrating its advantages in mode alignment and effective suppression of mode mixing, compared to the ensemble empirical mode decomposition (EEMD) method, thereby reducing spurious coupling. The EEG results of IESS patients showed that, compared to the nonrelapse group, the relapse group of IESS patients exhibited a significant increase in cross-channel PAC intensity at relatively lower frequencies and a decrease at higher frequencies. Further network topology analysis indicated that the relapse group showed higher levels of modularity in the high-frequency band, accompanied by lower clustering coefficients, reduced betweenness centrality, and decreased global efficiency. Conclusion: The NA-MEMD-based cross-channel PAC analysis demonstrates potential as a tool for assessing relapse-related connectivity patterns and prognosis in IESS. Significance: This work offers a novel perspective on the early identification of long-term outcomes in non-structural IESS patients.

PURPOSE:It is widely believed that electroencephalographers can identify epileptic spasms (ES) accurately. However, additional research is needed to verify this assumption, especially because some ES can be subtle, involving only facial movements, such as eye rolling. METHODS:The EEG data of 22 patients diagnosed with ES (whether or not it is diagnosed as infantile epileptic spasm syndrome) were evaluated by 6 senior electroencephalographers. The content included judgments of the presence or absence of ES throughout the entire examination process for each patient and in segmented pages every 4 seconds and the consistency among electroencephalographers. The inter-rater reliability (IRR) was assessed using the Fleiss kappa statistic. RESULTS:The accuracy of the 6 evaluators for identifying patients with or without ES in the 22-patient data set was 0.727 to 0.90, and the IRR among the 6 raters was moderate (0.45). Moderate IRR was observed among evaluators from tertiary (0.425), and poor IRR was observed among evaluators from nontertiary (0.399) centers. For the 4-second segmented pages, the accuracy for identifying ES in the 22 patients by the 6 evaluators was 0.943 to 1, and the IRR among the 6 evaluators was good agreement (0.63). CONCLUSIONS:Omissions in the identification of ES episodes were noted among different electroencephalographers, and IRR regarding whether a patient experienced an ES or whether a single event constituted an ES was found to be unsatisfactory. Identifying ES remains challenging for even experienced electroencephalographers.

AIM:Assisted reproductive technology (ART) is an invaluable strategy for preventing the inheritance of genetic disorders and promoting the birth of healthy children. Nevertheless, the general public's limited understanding of genetics and low awareness of available services obstruct effective utilization of genetic counseling. Our analysis of a family affected by mitochondrial genetic disease aims to improve public understanding of genetic knowledge and the importance of genetic counseling. METHODS:We gathered comprehensive data on a family with mitochondrial disease and scrutinized the genetic sequencing and diagnostic procedures used to identify mitochondrial disease within the family. RESULTS:In a case involving a family with two daughters, both began to exhibit symptoms such as abnormal gait, myodystonia, and excessive fatigue at the age of 4. These symptoms were incorrectly assumed to be paternally inherited, as the mother believed the father had a mild intellectual disability. As a result, the family opted for ART, specifically in vitro fertilization (IVF) with donor sperm, without thorough genetic counseling or a conclusive diagnosis for the children. Despite these precautions, the son born from IVF presented with symptoms mirroring his sisters' at the age of 6, including typical MRI abnormal signals in the bilateral basal ganglia. Furthermore, the eldest daughter's naturally conceived child also started to show identical symptoms by the age of 3. Subsequent genetic testing revealed a homoplasmic pathogenic mutation in the MT-ND6 gene (m.14459G>A), confirming that the dystonia was maternally inherited, with the mother exhibiting an 89.2% heteroplasmic variation in the same gene. CONCLUSIONS:This case study demonstrates the significant consequences of a lack of genetic knowledge and prevailing misconceptions when applying ART. It underscores the urgent need to bolster genetic literacy and emphasizes the vital importance of informed decision-making within genetic healthcare services.

Attention-deficit/hyperactivity disorder (ADHD) is a neuropsychiatric disorder. Emerging evidence suggests that gut microbiota may contribute to ADHD pathogenesis and that microbiota modulation could improve its symptoms. This study evaluated the safety and efficacy of a probiotic mixture containing Bifidobacterium animalis subsp. lactis BLa80 and Lacticaseibacillus rhamnosus LRa05 in children with ADHD. An open-label, single-arm trial enrolled children with ADHD (n = 42) who received daily oral probiotics (5 × 109 CFU) for 8 weeks. BRIEF-II and SNAP-IV scales were administered at baseline, Week 5, and Week 9 to assess changes in symptoms. Probiotic intervention significantly reduced scores in BRIEF-II domains (Global Executive Composite, Behavior Regulation Index, Emotion Regulation Index, and Cognitive Regulation Index) and SNAP-IV subscales (Inattention, Hyperactivity-Impulsivity) at Week 9 (all p < 0.05). One participant experienced mild diarrhea (grade 1, resolved spontaneously). No significant changes in hematological/biochemical parameters were observed. This exploratory study found that the probiotic mixture is safe and may improve ADHD symptoms in children, warranting further controlled trials to validate its efficacy and explore the underlying mechanisms. This study has been registered in a clinical trial registry. Trial Registration: ClinicalTrials.gov identifier: NCT06348121.

Previous studies have suggested that factors such as the treatment interval and aetiology may influence the initial response rate to first-line treatment for infantile epileptic spasms syndrome (IESS). However, few children with IECSS have undergone clinically accessible tests to determine the aetiology. Using a dataset from our previously published research, we constructed and tested a predictive model for the initial response to first-line treatment in children with IESS. Random sampling and 5-fold cross-validation were performed, with synthetic minority oversampling technique to correct data imbalance. Machine learning algorithms and evaluation metrics optimised model accuracy and efficacy. This study included 532 children with IESS who had completed monotherapy first-line treatment, of whom 160 achieved an initial response. The model’s accuracy, F1 score, and area under the curve (AUC) in the validation set were 0.7836 ± 0.0229 (ranging from 0.75167 to 0.80536), 0.7833 ± 0.0229 (ranging from 0.75145 to 0.80531), and 0.8516 ± 0.0165 (ranging from 0.82468 to 0.86936), respectively. Factors such as the age of seizure onset, age of spasm onset, lead time, MRI subtype, treatment choice, and age at treatment consistently ranked in the top six for importance in contributing to the model. The study findings suggest that this model may help effectively predict the initial response to first-line treatment, supporting clinical decision-making for children with IESS. Key predictors such as the age of seizure onset and MRI subtype enable early, data-driven intervention strategies in clinical practice.

Background:Infantile epileptic spasms syndrome (IESS) is an age-related developmental and epileptic encephalopathy. Adrenocorticotropic hormone (ACTH), one of the first-line treatment, has its efficacy influenced by multiple factors. This study aimed to investigate and analyze clinical variables (pre-treatment clinical data, serum and urine routine test) in children with IESS to predict outcomes after the first ACTH treatment. Furthermore, the potential impact of underlying factors on ACTH efficacy was assessed. Methods:A total of 186 children who received ACTH treatment for the first time in the Pediatric Department of The First Medical Center of the Chinese PLA General Hospital from January 2018 to June 2023 were retrospectively evaluated. They were divided into the responsive group and the non-responsive group according to the clinical outcomes after treatment. The clinical data of the two groups were compared, followed by logistic regression analysis to evaluate the relationship between the factors and ACTH treatment outcome. Results:The lead time between the first spasm onset and ACTH treatment initiation was significantly shorter in the responsive group compared with the non-responsive group. Additionally, more patients experienced epileptic spasms after the age of 3 months and responded significantly better to ACTH treatment than those whose spasms began within the first 3 months. Compared to children with IESS of unknown etiology, patients with congenital genetic abnormalities without structural abnormalities were less likely to have a short-term response to ACTH treatment. Despite no significant differences in serum sodium, potassium, calcium, and chloride levels between the two groups, pre-treatment serum inorganic phosphate levels were correlated with ACTH efficacy. The responsive group had significantly higher pre-treatment urinary pH levels. Conclusions:IESS patients should receive first-line treatment immediately after spasm onset. The age of epileptic spasms onset and its etiology may help predict the efficacy of ACTH treatment. Serum inorganic phosphate levels and urinary pH levels seem to play an important role in the treatment of IESS with ACTH, and they may have indicative significance for precision treatment.

Febrile Infection-Related Epilepsy Syndrome (FIRES) is an infrequent yet severe form of epilepsy that rapidly evolves into status epilepticus following a febrile episode. Prompt diagnosis coupled with effective treatment strategies is critical for improving patient outcomes. Herein, we describe the case of an 11-year-old male with FIRES who was successfully treated with tocilizumab, resulting in no further seizures or residual disability. The patient initially did not respond to antiseizure medications and first-line immunomodulatory therapy. Characteristic EEG patterns and elevated interleukin 6 levels in the cerebrospinal fluid contributed to an early presumptive diagnosis of FIRES. Tocilizumab was administered on day 10 after the seizure onset, leading to seizure cessation within 24 h, with no subsequent episodes. Serial cranial MRI imaging studies demonstrated transient abnormalities that resolved over time. Notably, on day 9, the patient exhibited bilateral frontal lobe hypermetabolism on FDG-PET, with EEG showing global slow waves predominantly in the bilateral frontal regions. As seizure control was achieved and encephalopathy symptoms improved, a follow-up EEG on day 25 revealed persistent slow waves in the bilateral frontal regions, with FDG-PET hypermetabolism present only in the left frontal lobe. By day 88, both EEG and FDG-PET had returned to normal. These findings suggest tocilizumab may play a role in the management of FIRES, though further studies are required to substantiate its therapeutic efficacy. Additionally, early bilateral frontal FDG-PET hypermetabolism and EEG slow-wave activity, may serve as an early biomarker in FIRES patients. However, more research is necessary to establish its validity.

Accurate diagnosis of Tic disorders (TD) and its severity based on electroencephalogram (EEG) data were of great clinical importance. This study analyzed EEG data from 90 children with TD and 88 healthy controls (HC). A two-stage progressive diagnosis framework based on EEG data and machine learning methods was developed. To achieve individualized prediction and reduce the feature dimension, we proposed a novel individual-based feature-weighted integration method in machine learning, as well as a new SHAP-driven feature selection and weighting (SFSW) strategy to improve the prediction accuracy. Based on 13 weighted features, Logistic Regression model achieved an average accuracy of 94.2% (95% CI, 90.6%-97.9%) in diagnosing TD, with a sensitivity of 92.4% (95% CI, 85.3%-99.5%) and a specificity of 96.1% (95% CI, 92.9%-99.2%). The Decision Tree model attained an average accuracy of 81.5% (95% CI, 68.6%-94.5%) in predicting severity, with a sensitivity of 81.5% (95% CI, 68.6%-94.5%) and a specificity of 89.9% (95% CI, 82.1%-97.6%). In the hold-out set validation, the method demonstrated accuracy rates of 95.7% in diagnosing TD and 83.3% in predicting severity. Interpretability analysis revealed that the top three main features affecting TD diagnosis were the mean frequency (MNF) of P3 channel β band, age and MNF of C3 channel γ band. This work offered a more efficient approach to individualized diagnosis of TD and had substantial practical value for clinical auxiliary diagnosis and intervention.

Nonketotic hyperglycinaemia (NKH) is an autosomal recessive neurometabolic disorder resulting from deficient glycine cleavage system activity, causing severe neurological impairment. While NKH is typically associated with pathogenic variants in glycine decarboxylase (GLDC) or aminomethyltransferase, the role of synonymous variants remains uncertain. To date, no cases of NKH caused by GLDC homozygous synonymous variants have been reported. Herein, a female infant born to consanguineous parents who developed refractory seizures, progressing to infantile epileptic spasms syndrome at 2 months is reported. Initial genetic testing identified a homozygous synonymous GLDC variant (c.1023G > A, p.Val341=), previously classified as "likely benign" in ClinVar (variation identification number: 1108119). Minigene splicing analysis revealed that the c.1023G > A variant caused a 38-base pair deletion in exon 7 (r.1021_1058del), Given the phenotypic characteristics of the child, we predict that this may resulting in a frameshift mutation (p.Val341ArgfsTer56) and a truncated protein. This functional evidence confirmed the pathogenicity of the variant.

The treatment of infantile epileptic spasms syndrome (IESS) aims to achieve spasm control. Current first-line interventions include hormone therapy (adrenocorticotropic hormone [ACTH] and corticosteroids) and vigabatrin. Despite treatment, the response rate remains at around 40

Transducin β-like 1 X-linked receptor 1 (TBL1XR1) protein is an important component of NCoR/SMRT complex. The variants of TBL1XR1 are associated with Pierpont syndrome (PS) and developmental delay (DD). This study aimed to discover new TBL1XR1 variants, their clinical manifestations, and protein-level changes. Whole-exome sequencing was used to identify patients with TBL1XR1 variants in 2024. Minigene assay was used to investigate specific splice site, which was further validated by Sanger sequencing. Structural changes in the TBL1XR1 protein were analyzed using PyMOL and molecular dynamics (MD) simulations. Potential binding partners were predicted via Genecards, STRING, and Cytoscape, while molecular docking was employed to assess how variants affect protein complex interactions. Two novel TBL1XR1 variants (c.1048-8_1049del and c.865-7A>G) were identified in two patients. Patient 1 exhibits global developmental delay (GDD), while patient 2 displays with facial dysmorphism and autism spectrum disorder. c.865-7A>G is a non-canonical splicing variant causing abnormal mRNA splicing. SpliceAI and RDDC predicted its splicing pattern. Minigene analysis found a 6 bp (TCTCAG) insertion in mRNA, leading to two amino acid (SQ) insertion in the TBL1XR1 protein. Therefore, P2 was diagnosed with PS. Variant changed the local hydrogen bond network and electrostatic potential. MD simulations showed variant changed the conformation of TBL1XR1 protein. Protein–protein interaction analysis selected NCOR1 for docking with TBL1XR1. Their interaction was reduced after the insertion of SQ, which may contribute to the occurrence of PS. This study reported two patients manifesting with GDD and PS, which were identified with two novel variants of TBL1XR1 (c.1048-8_1049del, p.(N350X)) and (c.865-7A>G, p.K288_T289insSQ), respectively. c.865-7A>G variant might lead to PS by reducing its interaction with NCOR1.

Introduction: In current studies, treatment of tuberous sclerosis complex (TSC)–related renal angiomyolipoma (RAML) was initiated only after clinical progression or the onset of symptoms, rather than at an earlier stage in the disease process. However, the previous case report indicated that early mammalian target of rapamycin (mTOR) inhibition in patients with TSC might prevent the development of TSC lesions. We performed this nested case-control study to evaluate whether prophylactic sirolimus initiation in early infancy prevented TSC-related RAML (TSC-RAML). Methods: A nested case-control study design was used, based on the Efficacy and Safety of Sirolimus in Pediatric Patients With Tuberous Sclerosis (ESOSIPT) study cohort. Children with TSC initiating sirolimus at age ≤ 3 months and without RAML at baseline comprised the case group (treatment group). Propensity score matching (1:3) was used to select the control group from the first visit patients who were aged > 3 months without mTOR inhibitor exposure. The incidence of RAML was compared via Kaplan-Meier method with log-rank testing. Results: Twenty-seven eligible children entered the study as a case group, and 81 patients who had not used mTOR inhibitors were matched. The log-rank test showed that the incidence of RAML between the 2 groups was statistically significant (P = 0.047). Short-term adverse events (AEs) were reported in 55.6% (15/27) of early-treated infants, predominantly grade 1 or 2 according to the common terminology criteria for AEs. Conclusion: The use of sirolimus in early infancy might have had potential benefits in preventing TSC-RAML, and the short-term AEs were usually mild or moderate.

Emerging evidence links the gut microbiome to autism spectrum disorder (ASD), yet the role of microbial genomic variation remains underexplored. We generated a large-scale metagenomic and metabolomic dataset from over 1,100 children, integrating public datasets, to characterize ASD-associated microbial changes. We identified 35 species, 213 genes, 28 pathways, and 99 metabolites, alongside 1,369 single-nucleotide variants, 233 insertions/deletions, and 195 structural variants with differential abundance. Profiling of microbial genomic variation revealed 33 species and 196 enzymes lacking abundance differences, yet exhibiting significant sequence variation. Integrated analysis of microbial variants and metabolites uncovered 357 neurological associations, with mediation analysis showing that several metabolites link microbial variants to the ASD phenotype. Importantly, diagnostic models incorporating microbial variant and/or metabolite features achieved superior performance and generalizability. Our findings highlight microbial genomic variation as a critical, previously overlooked dimension of ASD-associated dysbiosis, offering valuable insights for diagnosis and mechanistic studies.

Importance: Epilepsy is a chronic neurological condition affecting individuals across all ages, with the highest incidence observed in children younger than 1 year. Recurrent seizures and their associated physical and psychological consequences can result in significant morbidity and mortality. Objective: To examine global trends in the incidence, mortality, and disability-adjusted life-years (DALYs) associated with idiopathic childhood epilepsy across four age groups (<1 year, 1–4 years, 5–9 years, and 10–14 years), using data from the 2021 Global Burden of Disease (GBD) study. Design, Setting, and Participants: This cross-sectional study analyzed data from the GBD 2021 dataset, which included information from 204 countries and territories. The study focused on children aged 0 to 14 years diagnosed with idiopathic epilepsy. Data were analyzed from October 16, 2024, to December 18, 2024. Exposure: Age groups (<1 year, 1–4 years, 5–9 years, and 10–14 years) and childhood epilepsy trends from 1990 to 2021. Main Outcomes and Measures: Incidence, mortality, DALYs, and corresponding estimated annual percentage changes (EAPCs), stratified by age, sex, region, country, and Sociodemographic Index (SDI). Results: A total of 6,095,770 children (3255634 male [53.41%]) were included in the analysis. The global incidence of idiopathic childhood epilepsy increased from 971,368 cases in 1990 to 1,227,191 cases in 2021. Over three decades, the incidence rate rose from 55.85 (95% uncertainty interval [UI], 35.89–78.70) to 61.00 (95% UI, 39.09–86.21) per 100,000 population, with the highest rates among children younger than 1 year. Despite the increased incidence, epilepsy-associated death rates declined from 1.48 (95% UI, 1.01–1.78) to 0.90 (95% UI, 0.69–1.06), and DALYs rates decreased from 240.82 (95% UI, 178.96–310.79) to 177.17 (95% UI, 134.25–236.27). Regionally, the highest incidence of childhood epilepsy was observed in Andean Latin America (93.64; 95% UI, 45.06–150.38), while East Asia had the lowest incidence (38.50; 95% UI, 23.17–57.98). Eastern Sub-Saharan Africa reported the highest epilepsy-associated mortality rate (2.06; 95% UI, 1.56–2.59) and DALYs rate (306.53; 95% UI, 228.15–407.97). East Asia experienced the largest reduction in the DALYs rate (EAPC, −3.18; 95% CI, −3.27 to −3.10). Among 204 countries, Equatorial Guinea had the highest national incidence of childhood epilepsy in 2021 (116.66; 95% UI, 30.93–209.57), Tajikistan had the highest epilepsy-associated mortality rate (2.77; 95% UI, 1.84–4.08), and Zambia had the highest DALYs rate (403.33; 95% UI, 235.24–637.11). In 2021, the low SDI region had the highest epilepsy-associated mortality rate (1.46; 95% UI, 1.07–1.80) and DALYs rate (244.53; 95% UI, 179.90–327.46). Conclusions and Relevance: Childhood epilepsy remains a growing global health concern, particularly among children younger than 1 year, with increasing incidence rates. Although global declines in mortality and DALYs were observed, the burden remains disproportionately high in low SDI regions. Enhanced understanding of childhood epilepsy's epidemiology may inform strategies for prevention and management.