Levetiracetam versus Phenobarbital. Effects in the neurodevelopment in newborns treated for neonatal seizures: a clinical trial

Purpose: To analyze if the use of Phenobarbital compared with Levetiracetam, it’s associated with more neurodevelopmental problems in newborns treated for neonatal seizures. As a secondary objective identify which are the most affected areas of the neurodevelopment: cognition, socio-­‐emotional, motor or language skills.Design: A 5 years long clinical trial administering, with double-­‐blind and a randomized distribution of the sample, Phenobarbital or Levetiracetam for the management of neonatal seizures

Levetiracetam versus Phenobarbital. Effects in the neurodevelopment in newborns treated for neonatal seizures: a clinical trial

Purpose: To analyze if the use of Phenobarbital compared with Levetiracetam, it’s associated with more neurodevelopmental problems in newborns treated for neonatal seizures. As a secondary objective identify which are the most affected areas of the neurodevelopment: cognition, socio-­‐emotional, motor or language skills.Design: A 5 years long clinical trial administering, with double-­‐blind and a randomized distribution of the sample, Phenobarbital or Levetiracetam for the management of neonatal seizures

Therapy resistant neonatal seizures, linear vesicular rash, and unusually early neuroradiological changes: incontinentia pigmenti : A case report, literature review and insight into pathogenesis

CASE PRESENTATION: A substance abusing G2P1 mother spontaneously delivered at term an appropriate for gestational age girl. Neonatal seizures appeared at 21 hours and empiric anticonvulsive and antimicrobial treatment was started. At 25 hours, first vesicles appeared. While routine evaluations remained normal, a head CT revealed multifocal ischemic injuries, and a later MRI showed multifocal petechiae and diffusion abnormalities in the corticospinal tracts. The clinical diagnosis of incontinentia pigmenti (stage 1) was secured by histopathology. Follow-up at 13 months showed global developmental delay. DISCUSSION: We discuss the unusually early bilateral, fronto-occipital corticomedullar ischemias (CT day 3). On the MR imaging (day 7) extensive symmetric cerebral corticomedullar destruction and diffusion sequences with corticospinal tracts abnormalities are seen, which then evolve (day 26) to extensive symmetric cerebral destruction. We review the literature, genetics, suspected pathophysiology and possible neonatal manifestation. CONCLUSION: Incontinentia pigmenti is rare and, therefore, diagnosis is frequently delayed. Nevertheless, in the setting of therapy refractory seizures, excluded infections, and linear vesicular rash, a high index of suspicion is needed. This is the first report of simultaneous corticomedullar involvement as early as the third day of life.

A paradoxical rise of neonatal seizures after treatment with vitamin B6

We report the case of a newborn with intractable epileptic seizures developing a paradoxical rise of seizure frequency and electroencephalogram alterations after administration of vitamin B6. We have been unable to determine the aetiology of this disorder. In a newborn presenting with drug-resistant epileptic seizures, the first therapeutic option remains the application of intravenous pyridoxine, but the physician should be aware of the risk of an increase in seizure frequency.

Incidence, etiology and risk factors of neonatal seizures Harris County, Texas, 1992--1994

This study was conducted to determine the incidence and etiology of neonatal seizures, and evaluate risk factors for this condition in Harris County, Texas, between 1992 and 1994. Potential cases were ascertained from four sources: discharge diagnoses at local hospitals, birth certificates, death certificates, and a clinical study of neonatal seizures conducted concurrent with this study at a large tertiary care center in Houston, Texas. The neonatal period was defined as the first 28 days of life for term infants, and up to 44 weeks gestation for preterm infants.^ There were 207 cases of neonatal seizures ascertained among 116,048 live births, yielding and incidence of 1.8 per 1000. Half of the seizures occurred by the third day of life, 70% within the first week, and 93% within the first 28 days of life. Among 48 preterm infants with seizures 15 had their initial seizure after the 28th day of life. About 25% of all seizures occurred after discharge from the hospital of birth.^ Idiopathic seizures occurred most frequently (0.5/1000 births), followed by seizures attributed to perinatal hypoxia/ischemia (0.4/1000 births), intracranial hemorrhage (0.2/1000 births), infection of the central nervous system (0.2/1000 births), and metabolic abnormalities (0.1/1000 births).^ Risk factors were evaluated based on birth certificate information, using univariate and multivariate analysis (logistic regression). Factors considered included birth weight, gender, ethnicity, place of birth, mother's age, method of delivery, parity, multiple birth and, among term infants, small birth weight for gestational age (SGA). Among preterm infants, very low birth weight (VLBW, $<$1500 grams) was the strongest risk factor, followed by birth in private/university hospitals with a Level III nursery compared with hospitals with a Level II nursery (RR = 2.9), and male sex (RR = 1.8). The effect of very low birth weight varied according to ethnicity. Compared to preterm infants weighing 2000-2999 grams, non-white VLBW infants were 12.0 times as likely to have seizures; whereas white VLBW infants were 2.5 times as likely. Among term infants, significant risk factors included SGA (RR = 1.8), birth in Level III nursery private/university hospitals versus hospitals with Level II nursery (RR = 2.0), and birth by cesarean section (RR = 2.2). ^

A scoring system for early prognostic assessment after neonatal seizures

OBJECTIVE: The aim of this study was to devise a scoring system that could aid in predicting neurologic outcome at the onset of neonatal seizures. METHODS: A total of 106 newborns who had neonatal seizures and were consecutively admitted to the NICU of the University of Parma from January 1999 through December 2004 were prospectively followed-up, and neurologic outcome was assessed at 24 months’ postconceptional age. We conducted a retrospective analysis on this cohort to identify variables that were significantly related to adverse outcome and to develop a scoring system that could provide early prognostic indications. RESULTS: A total of 70 (66%) of 106 infants had an adverse neurologic outcome. Six variables were identified as the most important independent risk factors for adverse outcome and were used to construct a scoring system: birth weight, Apgar score at 1 minute, neurologic examination at seizure onset, cerebral ultrasound, efficacy of anticonvulsant therapy, and presence of neonatal status epilepticus. Each variable was scored from 0 to 3 to represent the range from “normal” to “severely abnormal.” A total composite score was computed by addition of the raw scores of the 6 variables. This score ranged from 0 to 12. A cutoff score of =4 provided the greatest sensitivity and specificity. CONCLUSIONS: This scoring system may offer an easy, rapid, and reliable prognostic indicator of neurologic outcome after the onset of neonatal seizures. A final assessment of the validity of this score in routine clinical practice will require independent validation in other centers.

Mortality risk after neonatal seizures in very preterm newborns

We analyzed clinical and instrumental data of 403 consecutive newborns with gestational age from 24 to 32 weeks, admitted to the University-Hospital of Parma between January 2000 and December 2007, to evaluate the possible relationship between neonatal mortality and occurrence of neonatal seizures in very preterm newborns. Seventy-four subjects died during hospital stay. Seizures were present in 35 neonates, in whom the mortality rate was 37.1%. Multivariate analysis revealed that birth-weight

Neonatal seizures and post-neonatal epilepsy:a seven-year follow-up study

BACKGROUND: Seizures are one of the most common symptoms of acute neurological disorders in newborns. This study aims at evaluating predictors of epilepsy in newborns with neonatal seizures. METHODS: we recruited consecutively eighty-five neonates with repeated neonatal video-EEG-confirmed seizures between Jan 1999 and Dec 2004. The relationship between clinical, EEG and ultrasound data in neonatal period and the development of post-neonatal epilepsy was investigated at 7 years of age. RESULTS: Fifteen patients (17.6%) developed post-neonatal epilepsy. Partial or no response to anticonvulsant therapy (OR 16.7, 95% CI: 1.8-155.8, p= .01; OR 47, 95% CI: 5.2-418.1, p<.01 respectively), severely abnormal cerebral ultrasound scan findings (OR: 5.4; 95% CI: 1.1-27.4; p<.04), severely abnormal EEG background activity (OR: 9.5; 95% CI: 1.6-54.2; p= .01) and the presence of status epilepticus (OR: 6.1; 95% CI: 1.8-20.3; p<.01) were found to be predictors of epilepsy. However, only the response to therapy seemed to be an independent predictor of post-neonatal epilepsy. CONCLUSION: Neonatal seizures seem to be related to post-neonatal epilepsy. Recurrent and prolonged neonatal seizures may act on an epileptogenic substrate, causing further damage, which is responsible for the subsequent clinical expression of epilepsy.

Phenobarbital for neonatal seizures:response rate and predictors of refractoriness

Background : Phenobarbital is the first-line choice for neonatal seizures treatment, despite a response rate of approximately 45%. Failure to respond to acute anticonvulsants is associated with poor neurodevelopmental outcome, but knowledge on predictors of refractoriness is limited. Objective : To quantify response rate to phenobarbital and to establish variables predictive of its lack of efficacy. Methods : We retrospectively evaluated newborns with electrographically confirmed neonatal seizures admitted between January 1999 and December 2012 to the neonatal intensive care unit of Parma University Hospital (Italy), excluding neonates with status epilepticus. Response was categorized as complete (cessation of clinical and electrographic seizures after phenobarbital administration), partial (reduction but not cessation of electrographic seizures with the first bolus, response to the second bolus), or absent (no response after the second bolus). Multivariate analysis was used to identify independent predictors of refractoriness. Results : Out of 91 newborns receiving phenobarbital, 57 (62.6%) responded completely, 15 (16.5%) partially, and 19 (20.9%) did not respond. Seizure type (p = 0.02), background electroencephalogram (EEG; p ≤ 0.005), and neurologic examination (p ≤ 0.005) correlated with response to phenobarbital. However, EEG (p ≤ 0.02) and seizure type (p ≤ 0.001) were the only independent predictors. Conclusion : Our results suggest a prominent role of neurophysiological variables (background EEG and electrographic-only seizure type) in predicting the absence of response to phenobarbital in high-risk newborns.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection

Objective: Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. Methods: The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. Results: Post-phenobarbital seizures showed significantly lower amplitude (p < 0.001) and involved fewer EEG channels at the peak of seizure (p < 0.05). No other features or SDA detection rates showed a statistical difference. Conclusion: These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. Significance: The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration.

An in-depth characterisation of neonatal seizures by early continuous video-EEG analysis

Introduction Seizures are harmful to the neonatal brain; this compels many clinicians and researchers to persevere further in optimizing every aspects of managing neonatal seizures. Aims To delineate the seizure profile between non-cooled versus cooled neonates with hypoxic-ischaemic encephalopathy (HIE), in neonates with stroke, the response of seizure burden to phenobarbitone and to quantify the degree of electroclinical dissociation (ECD) of seizures. Methods The multichannel video-EEG was used in this research study as the gold standard to detect seizures, allowing accurate quantification of seizure burden to be ascertained in term neonates. The entire EEG recording for each neonate was independently reviewed by at least 1 experienced neurophysiologist. Data were expressed in medians and interquartile ranges. Linear mixed models results were presented as mean (95% confidence interval); p values <0.05 were deemed as significant. Results Seizure burden in cooled neonates was lower than in non-cooled neonates [60(39-224) vs 203(141-406) minutes; p=0.027]. Seizure burden was reduced in cooled neonates with moderate HIE [49(26-89) vs 162(97-262) minutes; p=0.020] when compared with severe HIE. In neonates with stroke, the background pattern showed suppression over the infarcted side and seizures demonstrated a characteristic pattern. Compared with 10 mg/kg, phenobarbitone doses at 20 mg/kg reduced seizure burden (p=0.004). Seizure burden was reduced within 1 hour of phenobarbitone administration [mean (95% confidence interval): -14(-20 to -8) minutes/hour; p<0.001], but seizures returned to pre-treatment levels within 4 hours (p=0.064). The ECD index in cooled, non-cooled neonates with HIE, stroke and in neonates with other diagnoses were 88%, 94%, 64% and 75% respectively. Conclusions Further research exploring the treatment effects on seizure burden in the neonatal brain is required. A change to our current treatment strategy is warranted as we continue to strive for more effective seizure control, anchored with use of the multichannel EEG as the surveillance tool.

Treatment trials for neonatal seizures: the effect of design on sample size

Neonatal seizures are common in the neonatal intensive care unit. Clinicians treat these seizures with several anti-epileptic drugs (AEDs) to reduce seizures in a neonate. Current AEDs exhibit sub-optimal efficacy and several randomized control trials (RCT) of novel AEDs are planned. The aim of this study was to measure the influence of trial design on the required sample size of a RCT. We used seizure time courses from 41 term neonates with hypoxic ischaemic encephalopathy to build seizure treatment trial simulations. We used five outcome measures, three AED protocols, eight treatment delays from seizure onset (Td) and four levels of trial AED efficacy to simulate different RCTs. We performed power calculations for each RCT design and analysed the resultant sample size. We also assessed the rate of false positives, or placebo effect, in typical uncontrolled studies. We found that the false positive rate ranged from 5 to 85% of patients depending on RCT design. For controlled trials, the choice of outcome measure had the largest effect on sample size with median differences of 30.7 fold (IQR: 13.7–40.0) across a range of AED protocols, Td and trial AED efficacy (p<0.001). RCTs that compared the trial AED with positive controls required sample sizes with a median fold increase of 3.2 (IQR: 1.9–11.9; p<0.001). Delays in AED administration from seizure onset also increased the required sample size 2.1 fold (IQR: 1.7–2.9; p<0.001). Subgroup analysis showed that RCTs in neonates treated with hypothermia required a median fold increase in sample size of 2.6 (IQR: 2.4–3.0) compared to trials in normothermic neonates (p<0.001). These results show that RCT design has a profound influence on the required sample size. Trials that use a control group, appropriate outcome measure, and control for differences in Td between groups in analysis will be valid and minimise sample size.

Preterm infants with video-EEG confirmed seizures:outcome at 30 months of age

Our aim was to identify early predictors of poor neurodevelopmental outcome and of subsequent epilepsy in very early preterm and late preterm newborns with neonatal seizures.

Dynamic classifiers for neonatal brain monitoring

Brain injury due to lack of oxygen or impaired blood flow around the time of birth, may cause long term neurological dysfunction or death in severe cases. The treatments need to be initiated as soon as possible and tailored according to the nature of the injury to achieve best outcomes. The Electroencephalogram (EEG) currently provides the best insight into neurological activities. However, its interpretation presents formidable challenge for the neurophsiologists. Moreover, such expertise is not widely available particularly around the clock in a typical busy Neonatal Intensive Care Unit (NICU). Therefore, an automated computerized system for detecting and grading the severity of brain injuries could be of great help for medical staff to diagnose and then initiate on-time treatments. In this study, automated systems for detection of neonatal seizures and grading the severity of Hypoxic-Ischemic Encephalopathy (HIE) using EEG and Heart Rate (HR) signals are presented. It is well known that there is a lot of contextual and temporal information present in the EEG and HR signals if examined at longer time scale. The systems developed in the past, exploited this information either at very early stage of the system without any intelligent block or at very later stage where presence of such information is much reduced. This work has particularly focused on the development of a system that can incorporate the contextual information at the middle (classifier) level. This is achieved by using dynamic classifiers that are able to process the sequences of feature vectors rather than only one feature vector at a time.

A Nonstationary Model of Newborn EEG

The detection of seizure in the newborn is a critical aspect of neurological research. Current automatic detection techniques are difficult to assess due to the problems associated with acquiring and labelling newborn electroencephalogram (EEG) data. A realistic model for newborn EEG would allow confident development, assessment and comparison of these detection techniques. This paper presents a model for newborn EEG that accounts for its self-similar and non-stationary nature. The model consists of background and seizure sub-models. The newborn EEG background model is based on the short-time power spectrum with a time-varying power law. The relationship between the fractal dimension and the power law of a power spectrum is utilized for accurate estimation of the short-time power law exponent. The newborn EEG seizure model is based on a well-known time-frequency signal model. This model addresses all significant time-frequency characteristics of newborn EEG seizure which include; multiple components or harmonics, piecewise linear instantaneous frequency laws and harmonic amplitude modulation. Estimates of the parameters of both models are shown to be random and are modelled using the data from a total of 500 background epochs and 204 seizure epochs. The newborn EEG background and seizure models are validated against real newborn EEG data using the correlation coefficient. The results show that the output of the proposed models has a higher correlation with real newborn EEG than currently accepted models (a 10% and 38% improvement for background and seizure models, respectively).