The newborn drug development initiative workshop: Summary proceedings from the neurology group on neonatal seizures

Emerging trends and knowledge structure of epilepsy during pregnancy research for 2000-2018: a bibliometric analysis

Background

Epilepsy during pregnancy presents a unique set of challenges for pregnant women, the fetus, and the health care community. As research in this area advances rapidly, it is critical to keep up with the emerging trends and key turning points of the development of the domain knowledge. This study aimed to construct a series of science maps to quantitatively and qualitatively evaluate the intellectual landscape and research frontiers in the field of epilepsy during pregnancy research.

Methods

All publications were extracted from the Web of Science Core Collection database. Bibliometric analysis was used to analyze the scientific research outputs, including journals, countries/regions, institutions, authors (cited authors), intellectual base and research hotspots.

Results

A total of 2,225 publications related to epilepsy during pregnancy were identified as published between 2000 and 2018. The overall trend of the number of publications showed a fluctuating growth from 59 articles in 2000 to 198 in 2018. Neurology was the leading journal in the field of epilepsy and pregnancy research both in terms of impact factor score (8.055) and H-index value (77). The US retained its leading position and exerted a pivotal influence in this area. The University of Melbourne was identified as a good research institution for research collaboration. Prof. Pennell and Tomson have made great achievements in this area, and Prof. Tomson laid a foundation for the development of this domain. The keyword “neonatal seizures” ranked first in research hotspots, and the keyword “autism spectrum disorders (ASD)” ranked first in research frontiers.

Conclusions

Epilepsy during pregnancy is a fascinating and rapid development of subject matter. A more recent emerging trend focused on comprehensive management of pregnant and lactating women, evaluation of the safety and efficacy of newer antiepileptic drugs. The keywords “management issue,” “brain injury,” “meta-analysis,” “in utero exposure,” and “ASD” were the latest research frontiers and should be closely observed.

Age- and sex-dependent susceptibility to phenobarbital-resistant neonatal seizures: role of chloride co-transporters

Ischemia in the immature brain is an important cause of neonatal seizures. Temporal evolution of acquired neonatal seizures and their response to anticonvulsants are of great interest, given the unreliability of the clinical correlates and poor efficacy of first-line anti-seizure drugs. The expression and function of the electroneutral chloride co-transporters KCC2 and NKCC1 influence the anti-seizure efficacy of GABAA-agonists. To investigate ischemia-induced seizure susceptibility and efficacy of the GABAA-agonist phenobarbital (PB), with NKCC1 antagonist bumetanide (BTN) as an adjunct treatment, we utilized permanent unilateral carotid-ligation to produce acute ischemic-seizures in post-natal day 7, 10, and 12 CD1 mice. Immediate post-ligation video-electroencephalograms (EEGs) quantitatively evaluated baseline and post-treatment seizure burdens. Brains were examined for stroke-injury and western blot analyses to evaluate the expression of KCC2 and NKCC1. Severity of acute ischemic seizures post-ligation was highest at P7. PB was an efficacious anti-seizure agent at P10 and P12, but not at P7. BTN failed as an adjunct, at all ages tested and significantly blunted PB-efficacy at P10. Significant acute post-ischemic downregulation of KCC2 was detected at all ages. At P7, males displayed higher age-dependent seizure susceptibility, associated with a significant developmental lag in their KCC2 expression. This study established a novel neonatal mouse model of PB-resistant seizures that demonstrates age/sex-dependent susceptibility. The age-dependent profile of KCC2 expression and its post-insult downregulation may underlie the PB-resistance reported in this model. Blocking NKCC1 with low-dose BTN following PB treatment failed to improve PB-efficacy.

Clinical management of seizures in newborns : diagnosis and treatment

Neonatal seizures can be classified as tonic, clonic, myoclonic, and subtle. A clinical diagnosis is not easy as seizures are usually subtle in neonates. In the majority of newborn infants seizures are subclinical. On the other hand, not all abnormal movements identified by clinicians as clinical seizures are accompanied by electroencephalographic seizure discharges in the EEG. Precise incidence is difficult to delineate and depends on study population and criteria used for diagnosis of seizures. Controversy exists as to whether neonatal seizures themselves cause damage to the developing brain, or if the damage is primarily due to the underlying cause of the seizures. As a result of this controversy there is ongoing discussion whether all seizures (both clinical and subclinical) should be treated. In addition, when (sub)clinical seizures are treated, there is no consensus about the most appropriate treatment for neonatal seizures and how to assess the efficacy of treatment. Current therapeutic options to treat neonatal seizures (i.e. primarily first-generation antiepileptic drugs [AEDs]) are relatively ineffective. In practice, phenobarbital still remains the drug of first choice for EEG confirmed or suspected seizures. Benzodiazepines are also used in (phenobarbital) refractory cases. Several (small) studies indicate that lidocaine is an effective drug for refractory seizures as second- or third-line treatment. Although data are scarce, some AEDs with a wide acceptance in adult and pediatric neurology practice are being used to treat neonatal seizures (i.e. second-generation AEDs). These drugs are chemically different from all first-generation AEDs and they have an effect on other pathways so they provide new pharmacological targets for controlling seizures in newborns. Levetiracetam, topiramate, felbamate, bumetanide, lamotrigine and vigabatrin are examples of these second-generation AEDs. There is an urgent need for prospective, randomized, controlled trials to assess the efficacy and safety of these second-generation AEDs in neonates. The aim of this review is to provide an overview of the current knowledge of diagnosis, the effect on brain injury, and the treatment of neonatal seizures.

Detection of neonatal EEG seizure using multichannel matching pursuit

It is unusual for a newborn to have the classic "tonic-clonic" seizure experienced by adults and older children. Signs of seizure in newborns are either subtle or may become clinically silent. Therefore, the electroencephalogram (EEG) is becoming the most reliable tool for detecting neonatal seizure. Being non-stationary and multicomponent, EEG signals are suitably analyzed using time-frequency (TF) based methods. In this paper, we present a seizure detection method using a new measure based on the matching pursuit (MP) decomposition of EEG data. Signals are represented in the TF domain where seizure structural characteristics are extracted to form a new coherent TF dictionary to be used in the MP decomposition. A new approach to set data-dependent thresholds, used in the seizure detection process, is proposed. To enhance the performance of the detector, the concept of areas of incidence is utilized to determine the geometrical correlation between EEG recording channels.

Characterisation of heart rate changes and their correlation with EEG during neonatal seizures

The effect of seizures on instantaneous HR (iHR) in 12 neonates is investigated here. HR can be readily extracted from the ECG and can be employed as an additional signal in seizure detection algorithms. The change in instantaneous HR and its correlation with the change in RMS EEG amplitude were examined. Two methods were employed to classify significant iHR changes. Significant correlation (p 0.05) during seizure was observed in 100% of patients (83.33% of seizures). Overall, significant iHR changes (classified by either method) were found in 83% of patients (50% of seizures). It was found that a markedly higher iHR was observed in patients whose seizures were not classified as having significant iHR changes.

Neonatal seizures: dilemmas in workup and management

There is a pressing need for consistent, evidence-based guidelines in the management of neonatal seizures by pediatric neurologists and neonatologists. Israeli pediatric neurologists and neonatologists completed a 20-item, self-administered questionnaire on choices of antiepileptic drugs, treatment of intractable neonatal seizures (unremitting seizures after 3 medications), treatment duration, and recommended workup. The responding 36/55 (65%) neurologists and 66/112 (59%) neonatologists made similar antiepileptic drug choices (phenobarbital as first line, phenytoin as second line, and benzodiazepines as third line). Antiepileptic treatment duration was similar for both groups, but varied considerably within them (range, 1-52 weeks). Neurologists tended to recommend longer treatment for seizures secondary to asphyxia or hemorrhage. Neurologists and neonatologists recommended different antiepileptic drugs for intractable neonatal seizures: valproic acid and topiramate by neurologists, vs lidocaine and benzodiazepines by neonatologists (P = 0.0023). Fewer neurologists recommended continuous electroencephalography monitoring after asphyxia than neonatologists (40% vs 70.5%, P = 0.013). These responses reflect both similarities and inconsistencies of the two groups in diagnosing and treating neonatal seizures. Our findings call for controlled clinical trials to establish protocols for (1) diagnosing neonatal seizures, (2) studying the efficacy and safety of new-generation antiepileptic drugs, and (3) determining optimal duration of drug administration.

Seizure detection in neonates: Improved classification through supervised adaptation

The goal of neonatal seizure detection is the development of a patient independent system to alert staff in the neonatal intensive care unit of ongoing seizures. This study demonstrates the potential in adapting a patient independent classifier using patient specific data. Supervised adaptation is investigated using the basic gradient descent algorithm and least mean squares procedures. An increase in mean ROC area of 3% is obtained for the best performing learning algorithm, yielding an increase in mean accuracy of 7.7% compared to the patient independent algorithm.