Padsevonil suppresses seizures without inducing cell death in neonatal rats.

BACKGROUND: Padsevonil (PSL) is a rationally designed anti-seizure medication (ASM) which has overlapping mechanisms of action with the two most common ASMs used for neonatal seizures, phenobarbital (PB) and levetiracetam (LEV). Here we evaluated the anti-seizure properties of PSL across the neonatal and adolescent period in rats in the pentlyenetetrazole (PTZ) induced seizures model. METHODS: Postnatal day (P)7, P14 and P21 Sprague-Dawley rat pups were pre-treated with PSL (1-30 mg/kg), and assessed for seizure latency and severity 30 min later following injection of PTZ. A separate cohort of P7 pups were treated with neonatal ASMs and euthanized 24 h later (on P8) to assess induction of cell death, a feature common to many ASMs when given to P7 rodents. This effect has been extensively reported with PB, but not with LEV. Cell death was assessed by PathoGreen staining. RESULTS: PSL suppressed PTZ-evoked seizures across multiple age groups, particularly at higher doses, without producing increased cell death compared to vehicle. The effects of PSL were particularly notable at suppressing tonic-clonic seizure manifestations (82% of P7 and 100% of P14 and P21 animals were protected from tonic-clonic seizures with the 30 mg/kg dose). CONCLUSIONS: PSL displayed dose-dependent anti-seizure effects in immature rodents in the PTZ model of seizures in immature rats. While many ASMs, including PB, induce cell death in neonatal rats, PSL does not. This suggests that PSL may offer therapeutic benefit and a favorable safety profile for the treatment of neonatal seizures.

Combining EEG Features and Convolutional Autoencoder for Neonatal Seizure Detection.

Neonatal epilepsy is a common emergency phenomenon in neonatal intensive care units (NICUs), which requires timely attention, early identification, and treatment. Traditional detection methods mostly use supervised learning with enormous labeled data. Hence, this study offers a semi-supervised hybrid architecture for detecting seizures, which combines the extracted electroencephalogram (EEG) feature dataset and convolutional autoencoder, called Fd-CAE. First, various features in the time domain and entropy domain are extracted to characterize the EEG signal, which helps distinguish epileptic seizures subsequently. Then, the unlabeled EEG features are fed into the convolutional autoencoder (CAE) for training, which effectively represents EEG features by optimizing the loss between the input and output features. This unsupervised feature learning process can better combine and optimize EEG features from unlabeled data. After that, the pre-trained encoder part of the model is used for further feature learning of labeled data to obtain its low-dimensional feature representation and achieve classification. This model is performed on the neonatal EEG dataset collected at the University of Helsinki Hospital, which has a high discriminative ability to detect seizures, with an accuracy of 92.34%, precision of 93.61%, recall rate of 98.74%, and F1-score of 95.77%, respectively. The results show that unsupervised learning by CAE is beneficial to the characterization of EEG signals, and the proposed Fd-CAE method significantly improves classification performance.

Neurodevelopmental outcome of neonatal seizures: A longitudinal study.

INTRODUCTION: Neonatal seizures (NS) are the most common neurological emergency in the neonatal period. The International League Against Epilepsy (ILAE) proposed a new classification of NS based on semiology and highlighted the correlation between semiology and aetiology. However, neurodevelopmental outcomes have not been comprehensively evaluated based on this new classification. AIMS: To evaluate neurodevelopmental outcomes and potential risk factors for severe outcomes in NS. METHODS: Patients with video electroencephalogram confirmed NS were evaluated. Seizure aetiology, cerebral magnetic resonance imaging (MRI) data, background electroencephalograms data, general movements, and neurodevelopmental outcomes were analysed. Severe outcomes were one of the following: death, cerebral palsy, Griffiths developmental quotient <70, epilepsy, deafness, or blindness. RESULTS: A total of 74 neonates were evaluated: 62 (83.8 %) with acute provoked NS (primarily hypoxic-ischaemic encephalopathy), and 12 (16.2 %) with neonatal-onset epilepsies (self-limited neonatal epilepsy, developmental and epileptic encephalopathy, cerebral malformations). Of these, 32 (43.2 %) had electrographic seizures, while 42 (56.7 %) had electroclinical seizures - 38 (90.5 %) were motor (42.1 % clonic) and 4 (9.5 %) were non-motor phenomena. Severe outcomes occurred in 33 of the 74 (44.6 %) participants. In multivariate analysis, neonatal-onset epilepsies (odds ratio [OR]: 1.3; 95 % confidence interval [CI]: 1.1-1.6), status epilepticus (OR: 5.4; 95 % CI: 1.5-19.9), and abnormal general movements (OR: 3.4; 95 % CI: 1.9-7.6) were associated with severe outcomes. CONCLUSIONS: At present, hypoxic-ischaemic encephalopathy remains the most frequent aetiology of NS. The prognosis of neonatal-onset epilepsies was worse than that of acute provoked NS, and status epilepticus was the most predictive factor for adverse outcomes.

Gestational diabetes mellitus and late preterm birth: outcomes with and without antenatal corticosteroid exposure.

BACKGROUND: Unlike pregestational diabetes mellitus, the American College of Obstetricians and Gynecologists recommends antenatal corticosteroids in those with gestational diabetes mellitus at risk for preterm birth. However, this recommendation is based on limited data, only 10.6% of the Antenatal Late Preterm Steroids study sample had gestational diabetes mellitus. There is a paucity of data on the risk of neonatal respiratory and other morbidity in this population. OBJECTIVE: This study aimed to examine respiratory outcomes in parturients with gestational diabetes mellitus who received antenatal corticosteroids and delivered during the late preterm period vs those who did not. STUDY DESIGN: This population-based cohort study used the US Vital Statistics dataset between 2016 to 2020. The inclusion criteria were singleton, nonanomalous individuals who delivered between 34.0 to 36.6 weeks with gestational diabetes mellitus and known status of antepartum corticosteroid exposure. The primary outcome, a composite neonatal adverse outcome, included Apgar score <5 at 5 minutes, immediate assisted ventilation, assisted ventilation >6 hours, surfactant use, seizure, or neonatal mortality. The secondary outcome was a composite maternal adverse outcome, including maternal blood transfusion, ruptured uterus, unplanned hysterectomy, and admission to the intensive care unit. Multivariable Poisson regression models were used to estimate adjusted relative risks and 95% confidence intervals. Average annual percent change was calculated to assess changes in rates of corticosteroid exposure over the study period. RESULTS: Of 19 million births during the study period, 110,197 (0.6%) met the inclusion criteria, and among them, 23,028 (20.9%) individuals with gestational diabetes mellitus received antenatal corticosteroids. The rate of antenatal steroid exposure remained stable over the 5 years (APC=10.7; 95% confidence interval, -5.4 to 29.4). The composite neonatal adverse outcome was significantly higher among those who received corticosteroids than among those who did not (137.1 vs 216.5 per 1000 live births; adjusted relative risk 1.24; 95% confidence interval, 1.20-1.28). Three components of the composite neonatal adverse outcome-immediate assisted ventilation, intubation >6 hours, and surfactant use-were significantly higher with exposure than without. In addition, the composite maternal adverse outcome was significantly higher among those who received corticosteroids (adjusted relative risk, 1.34; 95% confidence interval, 1.18-1.52). Three components of the composite maternal adverse outcome-admission to intensive care unit, blood transfusion, and unplanned hysterectomy-were significantly higher among the exposed group. Subgroup analysis, among large for gestational age, by gestational age, and race and ethnicity, confirm the trend of increased likelihood of adverse outcomes with exposure to corticosteroid. CONCLUSION: Individuals with gestational diabetes mellitus and antenatal corticosteroid exposure, who delivered in the late preterm, were at higher risk of neonatal and maternal adverse outcomes than those unexposed to corticosteroid.

Detection and Severity Identification of Neonatal Seizure Using Deep Convolutional Neural Networks from Multichannel EEG Signal.

Introduction: One of the most frequent neurological conditions in newborns is neonatal seizures, which may indicate severe neurological dysfunction. These seizures may have very subtle or very modest clinical indications because patterns like oscillatory (spike) trains begin with relatively low amplitude and gradually increase over time. This becomes very challenging and erroneous if clinical observation is the primary basis for identifying newborn seizures. In this study, a diagnosis system using deep convolutional neural networks is proposed to determine and classify the severity level of neonatal seizures using multichannel neonatal EEG data. Methods: Datasets from publicly accessible online sources were used to compile clinical multichannel EEG datasets. Various preprocessing steps were taken, including the conversion of 2D time series data to equivalent waveform pictures. The proposed models have undergone training, and evaluations of their performance were conducted. Results: The proposed CNN was used to perform binary classification with an accuracy of 92.6%, F1-score of 92.7%, specificity of 92.8%, and precision of 92.6%. To detect newborn seizures, this model is utilized. Using the proposed CNN model, multiclassification was performed with accuracy rates of 88.6%, specificity rates of 92.18%, F1-score rates of 85.61%, and precision rates of 88.9%. The results demonstrated that the suggested strategy can assist medical professionals in making accurate diagnoses close to healthcare institutions. Conclusion: The developed system was capable of detecting neonatal seizures and has the potential to be used as a decision-making tool in resource-limited areas with a scarcity of expert neurologists.

Neonatal Cardiac Arrest Following Lacosamide Treatment: A Case Report.

BACKGROUND: Lacosamide is an antiepileptic drug with US Food and Drug Administration approval for the treatment of partial-onset seizures in patients older than one month. Lacosamide works by selective enhancement of proteins that induce preferential slow promotion of sodium channels to the hyperpolarized inactive state. Lacosamide is generally well-tolerated; however, clinical and nonclinical studies have linked its use with cardiac side effects including PR prolongation and atrioventricular (AV) block. RESULTS: We present the case of a three-week-old female neonatal patient born at 25 weeks' gestation who developed second-degree AV heart block and cardiac arrest after initiating lacosamide therapy. The patient was being treated for neonatal seizure complicated by intraventricular hemorrhage (grade II) and electrolyte disturbances with phenobarbital, levetiracetam, and phenytoin. Before addition of lacosamide therapy, the patient had an unremarkable electrocardiogram and no known cardiac risk factors for lacosamide. After medication discontinuation, the patient experienced no reoccurring episodes or other cardiac events. CONCLUSION: Use of lacosamide for neonatal populations is currently under evaluation. This is the first report of adverse cardiac event (AV block) in the setting of neonatal lacosamide use. Risk of future adverse cardiac events should be evaluated when determining the safety and efficacy of lacosamide in the neonatal population.

Neonatal Seizure Pattern, Outcome, and its Predictors Among Neonates Admitted to NICU of Ayder Comprehensive Specialized Hospital, Mekelle, Tigray, Ethiopia.

Background: Seizure is the most frequently observed symptom of neurological disorders and an important determinant of outcome during neonatal period. In clinical practice, it is prevalent and observed in neonates admitted to hospital in low-resources countries, but due to the paucity of studies in these regions, little is known about its pattern, clinical outcomes of hospitalization, and its predictors. Therefore, aims to evaluate seizure patterns, clinical outcomes, and its predictors among neonates admitted to the NICU of ACSH, Mekelle, and Tigray. Methods: A hospital-based cross-sectional study design was conducted among neonates with neonatal seizures admitted to NICU of Ayder Comprehensive Specialized Hospital. Data collection was done from record reviews. SPSS Version 25 was used. Descriptive statistics and bivariate logistic regressions where a p-value of <0.05 is considered statistically significant. Results: Out of 1622 NICU admissions, 155 (9.6%) were cases of neonatal seizure. The most frequently observed types of seizure in this study were subtle 70 (45.1%) and tonic 49 (31.6%) respectively. At the end of hospitalization 70.3% of neonates were discharged improved, 21.3% of neonates died and 8.4% of neonates had severe neurologic deficits. Poorly controlled seizures (AOR 4.8, 95% CI 2.6-9.2), prolonged duration of labor (AOR 4.3, 95% CI 2.2-8.8) and seizure onset <72 hours (AOR 3.7, 95% CI 1.6-8.5), respectively, were found to be independent predictors of poor neonatal outcome. Conclusion: Of all neonatal admissions, neonatal seizure was observed in close to 9.6%. The most frequently observed type of seizure was subtle. Of those admitted neonates, 30% had poor outcomes following the end of their hospitalization or when they leave against medical advice for lack of improvement). Poorly controlled seizures, prolonged duration of labor, and seizure onset <72 hours were independent predictors of poor neonatal outcomes.

A Modified Aquila-Based Optimized XGBoost Framework for Detecting Probable Seizure Status in Neonates.

Electroencephalography (EEG) is increasingly being used in pediatric neurology and provides opportunities to diagnose various brain illnesses more accurately and precisely. It is thought to be one of the most effective tools for identifying newborn seizures, especially in Neonatal Intensive Care Units (NICUs). However, EEG interpretation is time-consuming and requires specialists with extensive training. It can be challenging and time-consuming to distinguish between seizures since they might have a wide range of clinical characteristics and etiologies. Technological advancements such as the Machine Learning (ML) approach for the rapid and automated diagnosis of newborn seizures have increased in recent years. This work proposes a novel optimized ML framework to eradicate the constraints of conventional seizure detection techniques. Moreover, we modified a novel meta-heuristic optimization algorithm (MHOA), named Aquila Optimization (AO), to develop an optimized model to make our proposed framework more efficient and robust. To conduct a comparison-based study, we also examined the performance of our optimized model with that of other classifiers, including the Decision Tree (DT), Random Forest (RF), and Gradient Boosting Classifier (GBC). This framework was validated on a public dataset of Helsinki University Hospital, where EEG signals were collected from 79 neonates. Our proposed model acquired encouraging results showing a 93.38% Accuracy Score, 93.9% Area Under the Curve (AUC), 92.72% F1 score, 65.17% Kappa, 93.38% sensitivity, and 77.52% specificity. Thus, it outperforms most of the present shallow ML architectures by showing improvements in accuracy and AUC scores. We believe that these results indicate a major advance in the detection of newborn seizures, which will benefit the medical community by increasing the reliability of the detection process.

The association between maternal diabetes and neonatal seizures: a nested case-Control study.

Aim: We aimed to evaluate the association of pregestational diabetes mellitus (PGDM) and gestational diabetes mellitus (GDM) with neonatal seizures during neonatal hospitalization. Methods: In this nested case-control study, all data were collected from the data files of the National Vital Statistics System (NVSS) 2016-2021. Considering the effect of confounders, we used the propensity-score matching (PSM; case:control = 1:4) method to select the study population. The outcome was considered the occurrence of neonatal seizures. Univariate and multivariate logistic regression analyses were adopted to assess the association of PGDM and GDM with neonatal seizures. We also conducted stratified analyses according to gestational age, birthweight, 5 min Apgar score, and maternal age to explore the potential disparities. Results: After using the PSM method, a total of 6,674 cases of neonatal seizures and 26,696 controls were included. After adjusting for covariates, PGDM was associated with an increased risk of neonatal seizures [odds ratio (OR) = 1.51, 95% confidence interval (CI): 1.15-1.98], whereas the association between GDM and neonatal seizures is not statistically significant. In addition, the correlation between PGDM and increased risk of neonatal seizures was observed in neonates with a gestational age of 37-42 weeks and ≥42 weeks, with a 5 min Apgar score of ≥7, and with a maternal age of ≤40 years. Conclusion: PGDM was found to be closely associated with an increased risk of neonatal seizures. The findings of our study indicated that neonatologists should consider monitoring the incidence of neonatal seizures in neonates born to mothers with PGDM.

A Class-Imbalance Aware and Explainable Spatio-Temporal Graph Attention Network for Neonatal Seizure Detection.

Seizures are the most prevalent clinical indication of neurological disorders in neonates. In this study, a class-imbalance aware and explainable deep learning approach based on Convolutional Neural Networks (CNNs) and Graph Attention Networks (GATs) is proposed for the accurate automated detection of neonatal seizures. The proposed model integrates the temporal information of EEG signals with the spatial information on the EEG channels through the graph representation of the multi-channel EEG segments. One-dimensional CNNs are used to automatically develop a feature set that accurately represents the differences between seizure and nonseizure epochs in the time domain. By employing GAT, the attention mechanism is utilized to emphasize the critical channel pairs and information flow among brain regions. GAT coefficients were then used to empirically visualize the important regions during the seizure and nonseizure epochs, which can provide valuable insight into the location of seizures in the neonatal brain. Additionally, to tackle the severe class imbalance in the neonatal seizure dataset using under-sampling and focal loss techniques are used. Overall, the final Spatio-Temporal Graph Attention Network (ST-GAT) outperformed previous benchmarked methods with a mean AUC of 96.6% and Kappa of 0.88, demonstrating its high accuracy and potential for clinical applications.

Efficacy and safety of ketamine for neonatal refractory status epilepticus: case report and systematic review.

Background: Evidence-based data on treatment of neonatal status epilepticus (SE) are scarce. We aimed to collect data on the efficacy and safety of ketamine for the treatment of neonatal SE and to assess its possible role in the treatment of neonatal SE. Methods: We described a novel case and conducted a systematic literature review on neonatal SE treated with ketamine. The search was carried out in Pubmed, Cochrane, Clinical Trial Gov, Scopus and Web of Science. Results: Seven published cases of neonatal SE treated with ketamine were identified and analyzed together with our novel case. Seizures typically presented during the first 24 h of life (6/8). Seizures were resistant to a mean of five antiseizure medications. Ketamine, a NMDA receptor antagonist, appeared to be safe and effective in all neonates treated. Neurologic sequelae including hypotonia and spasticity were reported for 4/5 of the surviving children (5/8). 3/5 of them were seizure free at 1-17 months of life. Discussion: Neonatal brain is more susceptible to seizures due to a shift towards increased excitation because of a paradoxical excitatory effect of GABA, a greater density of NMDA receptors and higher extracellular concentrations of glutamate. Status epilepticus and neonatal encephalopathy could further enhance these mechanisms, providing a rationale for the use of ketamine in this setting. Conclusions: Ketamine in the treatment of neonatal SE showed a promising efficacy and safety profile. However, further in-depth studies and clinical trials on larger populations are needed.

Clinical and electroencephalography characteristics of 45 patients with neonatal seizures.

OBJECTIVES: The aim of our study was to retrospectively research the semiology of neonatal seizures (NSs) based on the 2021 classification scheme of the International League Against Epilepsy, and the relationship between etiology and electroclinical features. METHODS: Patients admitted to Children's Hospital of Chongqing Medical University from May 1, 2020 to March 30, 2022 and diagnosed with NSs were included to retrospectively investigate the etiology, seizure characteristics, prognosis, and ictal and interictal video electroencephalography (EEG) characteristics. RESULTS: Of the 45 patients, 73.3% had definite etiology. Twenty-seven patients had electro-clinical seizures, of which two had both electro-clinical and electrographic-only seizures. Electrographic-only seizures were reported in 18 patients. The tonic, clonic, and electrographic-only seizures were associated with various etiologies. Both tonic and clonic seizures occurred in acute symptomatic seizures and were associated with neonatal epilepsy. 50% of tonic seizures were related to genetic factors. Among the clonic seizures, 50.0% occurred in acute symptomatic seizures. Epileptic spasms always indicated neonatal epilepsy. There were few patients who experienced automatisms and sequential seizures, and these two seizure types were associated with brain malformation and genetic factors, respectively. Patients with a normal interictal EEG had acute symptomatic seizures. whereas the interictal EEG of patients with neonatal epilepsy mainly showed burst-suppression or multifocal discharges. The ictal EEG recordings were related to seizure semiology. CONCLUSION: Seizure semiology and video EEG are suggestive of potential causes but do not provide a definite etiology.

Neonatal Seizure Detection Using a Wearable Multi-Sensor System.

Neonatal seizure is an important clinical symptom of brain dysfunction, which is more common in infancy than in childhood. At present, video electroencephalogram (VEEG) technology is widely used in clinical practice. However, video electroencephalogram technology has several disadvantages. For example, the wires connecting the medical instruments may interfere with the infant's movement and the gel patch electrode or disk electrode commonly used to monitor EEG may cause skin allergies or even tears. For the above reasons, we developed a wearable multi-sensor platform for newborns to collect physiological and movement signals. In this study, we designed a second-generation multi-sensor platform and developed an automatic detection algorithm for neonatal seizures based on ECG, respiration and acceleration. Data for 38 neonates were recorded at the Children's Hospital of Fudan University in Shanghai. The total recording time was approximately 300 h. Four of the patients had seizures during data collection. The total recording time for the four patients was approximately 34 h, with 30 seizure episodes recorded. These data were evaluated by the algorithm. To evaluate the effectiveness of combining ECG, respiration and movement, we compared the performance of three types of seizure detectors. The first detector included features from ECG, respiration and acceleration records; the second detector incorporated features based on respiratory movement from respiration and acceleration records; and the third detector used only ECG-based features from ECG records. Our study illustrated that, compared with the detector utilizing individual modal features, multi-modal feature detectors could achieve favorable overall performance, reduce false alarm rates and give higher F-measures.

Long-Term Outcome of Neonatal Seizure with PACS2 Mutation: Case Series and Literature Review.

Phosphofurin Acidic Cluster Sorting Protein 2 (PACS2)-related early infantile developmental and epileptic encephalopathy (EIDEE) is a rare neurodevelopmental disorder. EIDEE is characterized by seizures that begin during the first three months of life and are accompanied by developmental impairment over time. In this article, we present three patients with EIDEE who experienced neonatal-onset seizures that developed into intractable seizures during infancy. Whole exome sequencing revealed a de novo heterozygous missense variant in all three patients in the p.Glu209Lys variant of the PACS2 gene. We conducted a literature review and found 29 cases to characterize the seizure patterns, neuroimaging features, the usage of anticonvulsants, and the clinical neurodevelopmental outcomes of PACS2-related EIDEE. The seizures were characterized by brief, recurring tonic seizures in the upper limbs, sometimes accompanied by autonomic features. Neuroimaging abnormalities were observed in the posterior fossa region, including mega cisterna magna, cerebellar dysplasia, and vermian hypoplasia. The long-term prognosis ranges from low-average intelligence to severe developmental retardation, emphasizing the importance of early recognition and accurate diagnosis by pediatric neurologists to provide personalized patient management.

A Case of Severe Neonatal Hypocalcemia Treated With Continuous Enteral Calcium.

Background/Objective: Hypocalcemia is a common, treatable cause of neonatal seizures. The rapid repletion of calcium is essential for restoring normal calcium homeostasis and resolving seizure activity. The accepted approach to administer calcium to a hypocalcemic newborn is via peripheral or central intravenous (IV) access. Case Report: We discuss a case of a 2-week-old infant who presented with hypocalcemia and status epilepticus. The etiology was determined to be neonatal hypoparathyroidism secondary to maternal hyperparathyroidism. Following an initial dose of IV calcium gluconate, the seizure activity abated. However, stable peripheral intravenous access could not be maintained. After weighing the risks and benefits of placing a central venous line for calcium replacement, it was decided to use continuous nasogastric calcium carbonate at a rate of 125 mg of elemental calcium/kg/d. Ionized calcium levels were used to guide the course of the therapy. The infant remained seizure-free and was discharged on day 5 on a treatment regimen that included elemental calcium carbonate, calcitriol, and cholecalciferol. He remained seizure free since discharge and all medications were discontinued by 8 weeks of age. Discussion: Continuous enteral calcium is an effective alternate therapy for restoration of calcium homeostasis in a neonate presenting with hypocalcemic seizures in the intensive care unit (ICU). Conclusion: We propose that continuous enteral calcium be considered as an alternative approach for calcium repletion in neonatal hypocalcemic seizures, one that avoids the potential complications of peripheral or central IV calcium administration.

The Role of Amplitude-Integrated Electroencephalography (aEEG) in Monitoring Infants with Neonatal Seizures and Predicting Their Neurodevelopmental Outcome.

Newborn monitoring in neonatal intensive care units (NICU) is mandatory, but neurological and especially electroencephalographic (EEG) monitoring can be overlooked or delayed until the newborn is clinically stable. However, the neonatal period is associated with the highest risk of seizures in humans, and the clinical symptoms may often be discrete, but the evolution and long-term neurodevelopmental disorders in these patients may be important. In response to this issue, we conducted a study to evaluate newborns who experienced neonatal seizures (NS) in the NICU and monitored their long-term neurological development. We enrolled 73 term and preterm newborns who underwent EEG monitoring using amplitude-integrated electroencephalography (aEEG). We then followed their neurological development until around 18 months of age, with 59 patients remaining in the long-term study. A total of 22% of patients with NS developed epilepsy, 12% cerebral palsy, 19% severe neurodevelopmental disabilities, and 8.5% died within the first 18 months of life. Our findings indicate that aEEG background pattern is a strong predictor of unfavorable neurological outcomes, with an odds ratio of 20.4174 (p < 0.05). Additionally, higher Apgar scores were associated with better outcomes (p < 0.05), with the odds of unfavorable neurological outcomes decreasing by 0.7-fold for every point increase in Apgar score. Furthermore, we found a statistically significant association between preterm birth and unfavorable neurological outcomes (p = 0.0104). Our study highlights the importance of early EEG monitoring in the NICU and provides valuable insights into predictors of unfavorable neurological outcomes in newborns who experienced NS.

Three-tiered fetal heart rate interpretation system and adverse neonatal and maternal outcomes: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to evaluate the rate of adverse neonatal or maternal outcomes in parturients with fetal heart rate tracings categorized as I, II or, III within the last 30 to 120 minutes of delivery. DATA SOURCES: The MEDLINE Ovid, Scopus, Embase, CINAHL, and Clinicaltrials.gov databases were searched electronically up to May 2022, using combinations of the relevant medical subject heading terms, keywords, and word variants that were considered suitable for the topic. STUDY ELIGIBILITY CRITERIA: Only observational studies of term infants reporting outcomes of interest with category I, II, or III fetal heart rate tracings were included. STUDY APPRAISAL AND SYNTHESIS METHODS: The coprimary outcome was the rate of either Apgar score <7 at 5 minutes or umbilical artery pH <7.00. Secondary outcomes were divided into neonatal and maternal adverse outcomes. Quality assessment of the included studies was performed using the Newcastle-Ottawa Scale. Random-effect meta-analyses of proportions were used to estimate the pooled rates of each categorical outcome in fetal heart rate tracing category I, II, and III patterns, and random-effect head-to-head meta-analyses were used to directly compare fetal heart rate tracings category I vs II and fetal heart rate tracing category II vs III, expressing the results as summary odds ratio or as mean differences with relative 95% confidence intervals. RESULTS: Of the 671 articles reviewed, 3 publications met the inclusion criteria. Among them were 47,648 singletons at ≥37 weeks' gestation. Fetal heart rate tracings in the last 30 to 120 minutes before delivery were characterized in the following manner: 27.0% of deliveries had category I tracings, 72.9% had category II tracings, and 0.1% had category III tracings. A single study, which was rated to be of poor quality, contributed 82.1% of the data and it did not provide any data for category III fetal heart rate tracings. When compared with category I fetal heart rate tracings (0.74%), the incidence of an Apgar score <7 at 5 minutes were significantly higher among deliveries with category II fetal heart rate tracings (1.51%) (odds ratio, 1.56; 95% confidence interval, 1.23-1.99) and among those with category III tracings (14.63%) (odds ratio, 14.46; 95% confidence interval, 2.77-75.39). When compared with category II tracings, category III tracings also had a significantly higher likelihood of a low Apgar score at 5 minutes (odds ratio, 14.46; 95% confidence interval, 2.77-75.39). The incidence of an umbilical artery pH <7.00 were similar among those with category I and those with category II tracings (0.08% vs 0.24%; odds ratio, 2.85; 95% confidence interval, 0.41-19.55). When compared with category I tracings, the incidence of an umbilical artery pH <7.00 was significantly more common among those with category III tracings (31.04%; odds ratio, 161.56; 95% confidence interval, 25.18-1036.42); likewise, when compared with those with category II tracings, those with category III tracings had a significantly higher likelihood of having an umbilical artery pH <7.00 (odds ratio, 42.29; 95% confidence interval, 14.29-125.10). Hypoxic-ischemic encephalopathy occurred with similar frequency among those with categories I and those with category II tracings (0 vs 0.81%; odds ratio, 5.86; 95% confidence interval, 0.75-45.89) but was significantly more common among those with category III tracings (0 vs 18.97%; odds ratio, 61.43; 95% confidence interval, 7.49-503.50). Cesarean delivery occurred with similar frequency among those with category I (13.41%) and those with category II tracings (11.92%) (odds ratio, 0.87; 95% confidence interval, 0.72-1.05) but was significantly more common among those with with category III tracings (14.28%) (odds ratio, 3.97; 95% confidence interval, 1.62-9.75). When compared with those with category II tracings, cesarean delivery was more common among those with category III tracings (odds ratio, 4.55; 95% confidence interval, 1.88-11.01). CONCLUSION: Although the incidence of an Apgar score <7 at 5 minutes and umbilical artery pH <7.00 increased significantly with increasing fetal heart rate tracing category, about 98% of newborns with category II tracings do not have these adverse outcomes. The 3-tiered fetal heart rate tracing interpretation system provides an approximate but imprecise measurement of neonatal prognosis.

Application of the International League Against Epilepsy Neonatal Seizure Framework to an international panel of medical personnel.

OBJECTIVE: The International League Against Epilepsy (ILAE) Neonatal Seizure Framework was tested by medical personnel. METHODS: Attendees at the 2016 ILAE European Congress on Epileptology in Prague, the International Video-EEG Course in Pediatric Epilepsies in Madrid 2017, and a local meeting in Utrecht 2018, were introduced to the proposed ILAE neonatal classification system with teaching videos covering the seven types of clinical seizures in the proposed neonatal classification system. Five test digital video recordings of electroencephalography (EEG)-confirmed motor neonatal seizures were then shown and classified by the rater based on their knowledge of the proposed ILAE Neonatal Seizure Framework. A multi-rater Kappa statistic was used to assess the agreement between observers and the true diagnosis. RESULTS: The responses of 194 raters were obtained. There was no single predominant classification system that was currently used by the raters. Using the ILAE framework, 78%-93% of raters correctly identified the clinical seizure type for each neonate; the overall inter-rater agreement (Kappa statistic) was 0.67. The clonic motor seizure type was most frequently accurately identified (93% of the time; κ = 0.870). EEG technicians correctly identified all presented motor seizure types more frequently than any other group (accuracy = 0.9). SIGNIFICANCE: The ILAE Neonatal Seizure Framework was judged by most raters to be better than other systems for the classification of clinical seizures. Among all seizure types presented, clonic seizures appeared to be the easiest to accurately identify. Average accuracy across the five seizure types was 84.5%. These data suggest that the ILAE neonatal seizure classification may be used by all healthcare professionals to correctly identify the predominant clinical seizure type.

Fingolimod Administration Following Hypoxia Induced Neonatal Seizure Can Restore Impaired Long-term Potentiation and Memory Performance in Adult Rats.

Neonatal seizures commonly caused by hypoxia can lead to long-term neurological outcomes. Early inflammation plays an important role in the pathology of these outcomes. Therefore, in the current study, we explored the long-term effects of Fingolimod (FTY720), an analog of sphingosine and potent sphingosine 1-phosphate (S1P) receptors modulator, as an anti-inflammatory and neuroprotective agent in attenuating anxiety, memory impairment, and possible alterations in gene expression of hippocampal inhibitory and excitatory receptors following hypoxia-induced neonatal seizure (HINS). Seizure was induced in 24 male and female pups (6 in each experimental group) at postnatal day 10 (P10) by premixed gas (5% oxygen/ 95% nitrogen) in a hypoxic chamber for 15 minutes. Sixty minutes after the onset of hypoxia, FTY720 (0.3 mg/kg) or saline (100 µl) was administered for 12 days (from P10 up to P21). Anxiety-like behavior and hippocampal memory function were assessed at P90 by elevated plus maze (EPM) and novel object recognition (NOR), respectively. Long-term potentiation (LTP) was recorded from hippocampal dentate gyrus region (DG) following stimulation of perforant pathway (PP). In addition, the hippocampal concentration of superoxide dismutase activity (SOD), malondialdehyde (MDA), and thiol as indices of oxidative stress were evaluated. Finally, the gene expression of NR2A subunit of N-Methyl-D-aspartic acid (NMDA) receptor, GluR2 subunit of (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) AMPA receptor and γ2 subunit of γ-Aminobutyric acid (GABAA) receptor were assessed at P90 by the quantitative real-time PCR. FTY720 significantly reduced later-life anxiety-like behavior, ameliorated object recognition memory and increased the amplitude and slope of the field excitatory postsynaptic potential (fEPSP) in the rats following HINS. These effects were associated with restoration of the hippocampal thiol content to the normal values and the regulatory role of FTY720 in the expression of hippocampal GABA and glutamate receptors subunits. In conclusion, FTY720 could restore the dysregulated gene expression of excitatory and inhibitory receptors. It also increased the reduced hippocampal thiol content, which was accompanied with attenuation of HINS-induced anxiety, reduced the impaired hippocampal related memory, and prevented hippocampal LTP deficits in later life following HINS.

De Novo Variant in the KCNJ9 Gene as a Possible Cause of Neonatal Seizures.

BACKGROUND: The reduction in next-generation sequencing (NGS) costs allows for using this method for newborn screening for monogenic diseases (MDs). In this report, we describe a clinical case of a newborn participating in the EXAMEN project (ClinicalTrials.gov Identifier: NCT05325749). METHODS: The child presented with convulsive syndrome on the third day of life. Generalized convulsive seizures were accompanied by electroencephalographic patterns corresponding to epileptiform activity. Proband WES expanded to trio sequencing was performed. RESULTS: A differential diagnosis was made between symptomatic (dysmetabolic, structural, infectious) neonatal seizures and benign neonatal seizures. There were no data in favor of the dysmetabolic, structural, or infectious nature of seizures. Molecular karyotyping and whole exome sequencing were not informative. Trio WES revealed a de novo variant in the KCNJ9 gene (1:160087612T > C, p.Phe326Ser, NM_004983), for which, according to the OMIM database, no association with the disease has been described to date. Three-dimensional modeling was used to predict the structure of the KCNJ9 protein using the known structure of its homologs. According to the predictions, Phe326Ser change possibly disrupts the hydrophobic contacts with the valine side chain. Destabilization of the neighboring structures may undermine the formation of GIRK2/GIRK3 tetramers necessary for their proper functioning. CONCLUSIONS: We believe that the identified variant may be the cause of the disease in this patient but further studies, including the search for other patients with the KCNJ9 variants, are needed.