Journal articles: 'Neonatal Seizure Detector'

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Ansari, Amir H., Perumpillichira J. Cherian, Alexander Caicedo, Gunnar Naulaers, Maarten De Vos, and Sabine Van Huffel. "Neonatal Seizure Detection Using Deep Convolutional Neural Networks." International Journal of Neural Systems 29, no. 04 (May 2019): 1850011. http://dx.doi.org/10.1142/s0129065718500119.

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Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the output is the class label: seizure/nonseizure. By training this network, the required features are optimized, while fitting a nonlinear classifier on the features. After training the network with EEG recordings of 26 neonates, five end layers performing the classification were replaced with a random forest classifier in order to improve the performance. This resulted in a false alarm rate of 0.9 per hour and seizure detection rate of 77% using a test set of EEG recordings of 22 neonates that also included dubious seizures. The newly proposed CNN classifier outperformed three data-driven feature-based approaches and performed similar to a previously developed heuristic method.

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Borovac, Ana, Thomas Philip Runarsson, Gardar Thorvardsson, and Steinn Gudmundsson. "Neonatal seizure detection algorithms: The effect of channel count." Current Directions in Biomedical Engineering 8, no. 2 (August 1, 2022): 604–7. http://dx.doi.org/10.1515/cdbme-2022-1154.

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Abstract The number of electrodes used to acquire neonatal EEG signals varies between institutions. Therefore, tools for automatic EEG analysis, such as neonatal seizure detection algorithms, need to be able to handle different electrode montages in order to find widespread use. The aim of this study was to analyse the effect of montage on neonatal seizure detector performance. A full 18-channel montage was compared to reduced 3- and 8-channel montages using a convolutional neural network for seizure detection. Sensitivity decreased by 10 - 18 % for the reduced montages while specificity was mostly unaffected. Electrode artefacts and artefacts associated with biological rhythms caused incorrect classification of nonseizure activity in some cases, but these artefacts were filtered out in the 3-channel montage. Other types of artefacts had little effect. Reduced montages result in some reduction in classifier accuracy, but the performance may still be acceptable. Recording artefacts had a limited effect on detection accuracy.

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Rao, Marpi Suryaprasada, Gavara Chinna Rao, Ayesha Sultana, and Putrevu Jagannadha Karthik. "Clinical, etiological, biochemical, microbiological and neurosonogram factors in related with neonatal seizures in Visakhapatnam, India." International Journal of Contemporary Pediatrics 4, no. 2 (February 22, 2017): 568. http://dx.doi.org/10.18203/2349-3291.ijcp20170711.

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Background: Neonatal seizure is a common neurological problem in the neonatal period. Detection of seizure, its etiology, and clinical types is important for guiding therapy. A varied number of conditions are capable of causing seizures in the neonatal period. The aim was to study biochemical, microbiological and, nurosonogram factors related with neonatal seizures in Visakhapatanam, India.Methods: The study was carried out in the Department of Paediatrics, Andhra medical college, King George Hospital, Visakhapatnam, Andhra Pradesh. The study was done to assess the biochemical changes, nurosonogram factors and microbilogical organisms implicated in neonatal seizures.Results: The present study is descriptive in nature where clinical spectrum of neonatal seizures in neonates was studied. 1500 neonates were admitted in NICU during the study period, among them 200 (13.3%) developed neonatal seizures. Etiology in majority of the cases of neonatal seizures was hypoxic ischemic encephalopathy (45%) followed in frequency by intracranial haemorrhage (14%), meningitis (12%), hypoglycaemia (11%), hypocalcaemia (4%) and others (14%). The most common organism implicated in neonatal seizures was Escherichia coli (36%), followed by Klebsiella (30%), staphylococcus aureus (19%), Streptococci agalactiae (7%) and unknown (8%). Meningitis accounted for 12% of neonatal seizures. Most common biochemical abnormalities noted were hypoglycemia, hypocalcaemia and hyponatremia.Conclusions: Biochemical abnormalities may significantly contribute to seizure activity and possibly correction of these abnormalities may play a significant role in seizure control. A biochemical work up is necessary for all cases of neonatal seizures. Appropriate treatment with antibiotics is essential. Examination of cerebrospinal fluid is essential work up in cases of neonatal seizures. Neurosonogram had good potential in predicting neurological outcome in neonates with perinatal asphyxia. Neurosonogram should be incorporated in the routine evaluation of seizures.

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Temko, Andriy, William Marnane, Geraldine Boylan, and Gordon Lightbody. "A Data-Driven Energy Based Estimator of EEG Channel Importance for Improved Patient-Adaptive Neonatal Seizure Detector." IFAC Proceedings Volumes 44, no. 1 (January 2011): 13770–75. http://dx.doi.org/10.3182/20110828-6-it-1002.03457.

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Buttle, Sarah Grace, Brigitte Lemyre, Erick Sell, Stephanie Redpath, Srinivas Bulusu, Richard J. Webster, and Daniela Pohl. "Combined Conventional and Amplitude-Integrated EEG Monitoring in Neonates: A Prospective Study." Journal of Child Neurology 34, no. 6 (February 14, 2019): 313–20. http://dx.doi.org/10.1177/0883073819829256.

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Background/Objective: Seizure monitoring via amplitude-integrated EEG is standard of care in many neonatal intensive care units; however, conventional EEG is the gold standard for seizure detection. We compared the diagnostic yield of amplitude-integrated EEG interpreted at the bedside, amplitude-integrated EEG interpreted by an expert, and conventional EEG. Methods: Neonates requiring seizure monitoring received amplitude-integrated EEG and conventional EEG in parallel. Clinical events and amplitude-integrated EEG were interpreted at bedside. Subsequently, amplitude-integrated EEG and conventional EEG were independently analyzed by experienced neonatology and neurology readers. Sensitivity and specificity of bedside amplitude-integrated EEG as compared to expert amplitude-integrated EEG interpretation and conventional EEG were evaluated. Results: Thirteen neonates were monitored for an average duration of 33 hours (range 15-94, SD 25). Fourteen seizure-like events were detected by clinical observation, and 12 others by bedside amplitude-integrated EEG analysis. One of the clinical, and none of the bedside amplitude-integrated EEG events were confirmed as seizures on conventional EEG. Post hoc expert amplitude-integrated EEG interpretation revealed eight suspected seizures, all different from the ones detected by the bedside amplitude-integrated EEG team, of which one was confirmed via conventional EEG. Eight seizures were recorded on conventional EEG. Expert amplitude-integrated EEG interpretation had a sensitivity of 13% with 46% specificity for individual seizure detection, and a sensitivity of 50% with 46% specificity for detecting patients with seizures. Conclusion: Real-world bedside amplitude-integrated EEG monitoring failed to detect all seizures evidenced via conventional EEG, while misclassifying other events as seizures. Even post hoc expert amplitude-integrated EEG interpretation provided limited sensitivity and specificity. Considering the poor sensitivity and specificity of bedside amplitude-integrated EEG interpretation, combined monitoring may provide limited clinical benefit.

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Buraniqi, Ersida, Arnold J. Sansevere, Kush Kapur, Ann M. Bergin, Phillip L. Pearl, and Tobias Loddenkemper. "Electrographic Seizures in Preterm Neonates in the Neonatal Intensive Care Unit." Journal of Child Neurology 32, no. 10 (July 9, 2017): 880–85. http://dx.doi.org/10.1177/0883073817713918.

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Objective: Characterize clinical and electroencephalography (EEG) characteristics of preterm neonates undergoing continuous EEG in the neonatal intensive care unit. Methods: Retrospective study of preterm neonates born less than 37 weeks’ gestational age undergoing continuous EEG in the neonatal intensive care unit at Boston Children’s Hospital over a 2-year period. Results: Fifty-two preterms (46% male) had a mean gestational age of 32.8 weeks (standard deviation = 4.17). Seizures were detected in 12/52 (23%), with EEG seizures detected in 4/12 (33%). The median time from EEG to the first seizure was 0.5 hours (interquartile range 0.24-4). Factors associated with seizures were male gender (odds ratio = 4.65 [95% confidence interval = 1.02-21.24], P = .047) and lack of EEG state change (odds ratio = 0.043 [95% confidence interval = 0.005-0.377], P = .04). Conclusion: Twenty-three percent of preterms undergoing continuous EEG had EEG seizures or electrographic seizures with no clear clinical correlate. This confirms recent American Clinical Neurophysiology Society guidelines suggesting that preterm neonates are at high risk for seizures.

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Olmi, Benedetta, Claudia Manfredi, Lorenzo Frassineti, Carlo Dani, Silvia Lori, Giovanna Bertini, Cesarina Cossu, Maria Bastianelli, Simonetta Gabbanini, and Antonio Lanatà. "Heart Rate Variability Analysis for Seizure Detection in Neonatal Intensive Care Units." Bioengineering 9, no. 4 (April 7, 2022): 165. http://dx.doi.org/10.3390/bioengineering9040165.

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In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely clinical intervention. Over the years, several neonatal seizure detection systems were proposed to detect neonatal seizures automatically and speed up seizure diagnosis, most based on the EEG signal analysis. Recently, research has focused on other possible seizure markers, such as electrocardiography (ECG). This work proposes an ECG-based NSD system to investigate the usefulness of heart rate variability (HRV) analysis to detect neonatal seizures in the NICUs. HRV analysis is performed considering time-domain, frequency-domain, entropy and multiscale entropy features. The performance is evaluated on a dataset of ECG signals from 51 full-term babies, 29 seizure-free. The proposed system gives results comparable to those reported in the literature: Area Under the Receiver Operating Characteristic Curve = 62%, Sensitivity = 47%, Specificity = 67%. Moreover, the system’s performance is evaluated in a real clinical environment, inevitably affected by several artefacts. To the best of our knowledge, our study proposes for the first time a multi-feature ECG-based NSD system that also offers a comparative analysis between babies suffering from seizures and seizure-free ones.

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Howard, Rachel, Runci Li, Kelly Harvey-Jones, Vinita Verma, Frédéric Lange, Geraldine Boylan, Ilias Tachtsidis, and Subhabrata Mitra. "Optical Monitoring in Neonatal Seizures." Cells 11, no. 16 (August 21, 2022): 2602. http://dx.doi.org/10.3390/cells11162602.

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Background: Neonatal seizures remain a significant cause of morbidity and mortality worldwide. The past decade has resulted in substantial progress in seizure detection and understanding the impact seizures have on the developing brain. Optical monitoring such as cerebral near-infrared spectroscopy (NIRS) and broadband NIRS can provide non-invasive continuous real-time monitoring of the changes in brain metabolism and haemodynamics. Aim: To perform a systematic review of optical biomarkers to identify changes in cerebral haemodynamics and metabolism during the pre-ictal, ictal, and post-ictal phases of neonatal seizures. Method: A systematic search was performed in eight databases. The search combined the three broad categories: (neonates) AND (NIRS) AND (seizures) using the stepwise approach following PRISMA guidance. Results: Fifteen papers described the haemodynamic and/or metabolic changes observed with NIRS during neonatal seizures. No randomised controlled trials were identified during the search. Studies reported various changes occurring in the pre-ictal, ictal, and post-ictal phases of seizures. Conclusion: Clear changes in cerebral haemodynamics and metabolism were noted during the pre-ictal, ictal, and post-ictal phases of seizures in neonates. Further studies are necessary to determine whether NIRS-based methods can be used at the cot-side to provide clear pathophysiological data in real-time during neonatal seizures.

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Gacio, Sebastián. "Amplitude-integrated electroencephalography for neonatal seizure detection. An electrophysiological point of view." Arquivos de Neuro-Psiquiatria 77, no. 2 (February 2019): 122–30. http://dx.doi.org/10.1590/0004-282x20180150.

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ABSTRACT Seizures in the newborn are associated with high morbidity and mortality, making their detection and treatment critical. Seizure activity in neonates is often clinically obscured, such that detection of seizures is particularly challenging. Amplitude-integrated EEG is a technique for simplified EEG monitoring that has found an increasing clinical application in neonatal intensive care. Its main value lies in the relative simplicity of interpretation, allowing nonspecialist members of the care team to engage in real-time detection of electrographic seizures. Nevertheless, to avoiding misdiagnosing rhythmic artifacts as seizures, it is necessary to recognize the electrophysiological ictal pattern in the conventional EEG trace available in current devices. The aim of this paper is to discuss the electrophysiological basis of the differentiation of epileptic seizures and extracranial artifacts to avoid misdiagnosis with amplitude-integrated EEG devices.

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Tapani, Karoliina T., Sampsa Vanhatalo, and Nathan J. Stevenson. "Time-Varying EEG Correlations Improve Automated Neonatal Seizure Detection." International Journal of Neural Systems 29, no. 04 (May 2019): 1850030. http://dx.doi.org/10.1142/s0129065718500302.

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The aim of this study was to develop methods for detecting the nonstationary periodic characteristics of neonatal electroencephalographic (EEG) seizures by adapting estimates of the correlation both in the time (spike correlation; SC) and time–frequency domain (time–frequency correlation; TFC). These measures were incorporated into a seizure detection algorithm (SDA) based on a support vector machine to detect periods of seizure and nonseizure. The performance of these nonstationary correlation measures was evaluated using EEG recordings from 79 term neonates annotated by three human experts. The proposed measures were highly discriminative for seizure detection (median [Formula: see text]: 0.933 IQR: 0.821–0.975, median [Formula: see text]: 0.883 IQR: 0.707–0.931). The resultant SDA applied to multi-channel recordings had a median AUC of 0.988 (IQR: 0.931–0.998) when compared to consensus annotations, outperformed two state-of-the-art SDAs [Formula: see text] and was noninferior to the human expert for 73/79 of neonates.

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Buttle, SG, B. Lemyre, E. Sell, S. Redpath, S. Bulusu, R. Webster, and D. Pohl. "P.056 Combined conventional and amplitude-integrated EEG monitoring in neonates: a prospective study." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 46, s1 (June 2019): S29. http://dx.doi.org/10.1017/cjn.2019.156.

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Background: Seizure monitoring via amplitude-integrated EEG (aEEG) is standard of care in many NICUs; however, conventional EEG (cEEG) is the gold standard for seizure detection. We compared the diagnostic yield of aEEG interpreted at the bedside, aEEG interpreted by an expert, and cEEG. Methods: Neonates received aEEG and cEEG in parallel. Clinical events and aEEG were interpreted at bedside and subsequently independently analyzed by experienced neonatology and neurology readers. Sensitivity and specificity of bedside aEEG as compared to expert aEEG interpretation and cEEG were evaluated. Results: Thirteen neonates were monitored for an average duration of 33 hours (range 15-94). Fourteen seizure-like events were detected by clinical observation, and 12 others by bedside aEEG analysis. None of the bedside aEEG events were confirmed as seizures on cEEG. Expert aEEG interpretation had a sensitivity of 13% with 46% specificity for individual seizure detection (not adjusting for patient differences), and a sensitivity of 50% with 46% specificity for detecting patients with seizures. Conclusions: Real-world bedside aEEG monitoring failed to detect seizures evidenced via cEEG, while misclassifying other events as seizures. Even post-hoc expert aEEG interpretation provided limited sensitivity and specificity. Considering the poor sensitivity and specificity of bedside aEEG interpretation, combined monitoring may provide limited clinical benefit.

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Ezeanosike, Obumneme, Ifeyinwa C. Akamike, Ijeoma N. Okedo-Alex, Datonye C. Briggs, Dorathy Chinwe Obu, Onyinye U. Anyanwu, Olapeju W. Daniyan, and Edward Alikor. "A protocol for systematic review and meta-analysis on the burden of neonatal seizures in Nigeria." Nigerian Journal of Paediatrics 48, no. 4 (November 7, 2022): 201–5. http://dx.doi.org/10.4314/njp.v48i4.6.

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Neonatal seizures are a significant contributor to neonatal morbidity and mortality in Nigeria and the magnitude of the burden is unknown. A comprehensive systematic review is needed to determine the pooled magnitude and causes of neonatal seizures in Nigeria since the true estimate is yet to be determined. Therefore, this study aims to develop a protocol to assess the burden and causes of neonatal seizures in Nigeria. A search strategy is developed using MeSH terms, text words, and entry terms. Nine databases will be searched including Pub- Med, African journals online, Google Scholar, Cumulative Index to Nursing and Allied Health Literature, EMBASE, Psych Info, Web of Science, Scopus, and Research Gate. Only observational studies, retrievable in the English language and conducted in Nigerian neonates will be included. The primary outcome of this study is the pooled prevalence of neonatal seizures in Nigeria. The secondary outcomes include the seizure types, causes, method of detection, and outcome in the neonates. Screening of identified studies will be done in End Note version 20 and duplicates removed, before exporting to Microsoft 365 excel sheet for data extraction by independent reviewers. Studies will be assessed for methodological, clinical, and statistical heterogeneity and if required, a meta-analysis will be done. Stata 16 IC will be used for data analysis. Various subgroup analyses will also be done. A funnel plot will be used for the assessment of publication bias. Results will be presented in tabular formats, narrative synthesis, and regression plots. The data from this review will reveal the pooled prevalence of neonatal seizures in Nigeria. It will create an avenue for discussion on the types, causes, and outcome of neonatal seizures. The findings will also enable discussions on how to address the causes of neonatal seizures in Nigeria and provide evidence for policy recommendations to reduce morbidity and mortality resulting from neonatal seizures in Nigeria. Trial registration number: This protocol is registered in PROSPERO with registration number CRD42020220097.

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Bashir, RA, L. Espinoza, S. Vayalthrikkovil, J. Buchhalter, L. Bello-Espinosa, and K. Mohammad. "The Impact of Continuous Digital Video Electroencephalogram (CEEG) Introduction on the Use of Anti-Epileptic Drugs (AEDS) in Neonates with Hypoxic Ischemic Encephalopathy (HIE)." Paediatrics & Child Health 21, Supplement_5 (June 1, 2016): e81d-e82. http://dx.doi.org/10.1093/pch/21.supp5.e81d.

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Abstract BACKGROUND: Use of AEDs in neonates may disrupt neuronal development by synaptic re-organization and altering brain plasticity. Introduction of cEEG as part of neonatal neurocritical care long term monitoring (LTM) aims to improve seizure detection and control in neo-nates with HIE. OBJECTIVES: To assess the impact of cEEG on seizure detection and the use of AEDs in neonates with HIE DESIGN/METHODS: A retrospective cohort study of neonates admitted with HIE to a level III NICU two years before and after introduction of LTM in August 2013. The cEEGs were read remotely by a pediatric epileptologist. Before LTM, a 60 minute routine EEG (rEEG) was the standard practice. Primary outcome was the number of AEDs used. Secondary outcomes were AEDs used as maintenance and on discharge, and AEDs burden (total mg/kg used during hospital stay). HIE staging was based on modified Sarnat scoring system. Drug burden for each AED was calculated. Categorical variables were analysed using Chi-square test and continuous variables using student&#39;s t test. RESULTS: n=157 (total number of HIE patients); median gestation 40 weeks (IQR 38-40); 71 infants(45%) had LTM monitoring;103 infants(66%) were cooled. Baseline and clinical characteristics including disease severity and cooling were similar. In the pre LTM era, 12 of 52 (23%) infants with clinical seizures, only 12 had seizures by rEEG . Using cEEG, 17 out of 33 (52%) clinical seizures were confirmed by cEEG; 5/36(1%) had subclinical seizures compared to none before LTM. Detection of EEG seizures increased significantly with LTM (p 0.02). Discharge on any AEDs was less in the LTM group and the mean AEDs burden was reduced from 176 mg/kg in the pre LTM to 91 mg/kg in the post LTM group. CONCLUSION: Introduction of cEEG improved seizure detection and control; but decreased the overall use and burden of AEDs. p value <0.05 is denoted as *

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Frassineti, Lorenzo, Antonio Lanatà, Benedetta Olmi, and Claudia Manfredi. "Multiscale Entropy Analysis of Heart Rate Variability in Neonatal Patients with and without Seizures." Bioengineering 8, no. 9 (September 9, 2021): 122. http://dx.doi.org/10.3390/bioengineering8090122.

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The complex physiological dynamics of neonatal seizures make their detection challenging. A timely diagnosis and treatment, especially in intensive care units, are essential for a better prognosis and the mitigation of possible adverse effects on the newborn’s neurodevelopment. In the literature, several electroencephalographic (EEG) studies have been proposed for a parametric characterization of seizures or their detection by artificial intelligence techniques. At the same time, other sources than EEG, such as electrocardiography, have been investigated to evaluate the possible impact of neonatal seizures on the cardio-regulatory system. Heart rate variability (HRV) analysis is attracting great interest as a valuable tool in newborns applications, especially where EEG technologies are not easily available. This study investigated whether multiscale HRV entropy indexes could detect abnormal heart rate dynamics in newborns with seizures, especially during ictal events. Furthermore, entropy measures were analyzed to discriminate between newborns with seizures and seizure-free ones. A cohort of 52 patients (33 with seizures) from the Helsinki University Hospital public dataset has been evaluated. Multiscale sample and fuzzy entropy showed significant differences between the two groups (p-value < 0.05, Bonferroni multiple-comparison post hoc correction). Moreover, interictal activity showed significant differences between seizure and seizure-free patients (Mann-Whitney Test: p-value < 0.05). Therefore, our findings suggest that HRV multiscale entropy analysis could be a valuable pre-screening tool for the timely detection of seizure events in newborns.

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Din, F., S. MacFarland, D. Wilson, and CD Hahn. "P.096 Optimizing the Use of Continuous EEG Monitoring in Neonatal Encephalopathy." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 48, s3 (November 2021): S46—S47. http://dx.doi.org/10.1017/cjn.2021.374.

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Background: Newborns with hypoxic-ischemic encephalopathy (HIE) are at high risk for seizures, the majority of which have no clinical signs and therefore require continuous electroencephalographic (cEEG) monitoring for their detection. We sought to determine which neonates are at highest risk for seizures in order to optimize allocation of scarce cEEG resources. Methods: We identified term neonates diagnosed with HIE who underwent at least 24 hours of protocol-based cEEG monitoring between 2016 and 2019. We quantified seizure incidence, timing and burden, and correlated these with potential risk factors such as HIE severity, use of therapeutic hypothermia, preceding suspected clinical seizures, amplitude-integrated EEG (aEEG) background and patterns suspicious for seizures, and use of anti-seizure drugs. Results: cEEG monitoring was completed in 218 neonates with HIE, of whom 164 (75%) underwent therapeutic hypothermia. Preceding clinical/aEEG seizures occurred in 147 (67%), 99 (67%) of whom had been cooled but only 22 (10%) had cEEG-confirmed seizures. Characterization of seizure burden and correlation with potential risk factors is ongoing. Conclusions: Although seizures are commonly suspected in neonates with HIE, they are infrequently confirmed during cEEG monitoring, creating opportunities for more efficient risk-based allocation of cEEG resources.

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Mendelsohn, R., D. Pohl, K. Mabilangan, and B. Lemyre. "P.055 A clinical pathway of combined EEG monitoring in high-risk critically ill neonates." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 46, s1 (June 2019): S28—S29. http://dx.doi.org/10.1017/cjn.2019.155.

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Background: overtreatment of neonatal seizures may result in neurological morbidity. aEEG, despite low sensitivity, is widely used, for ease of bedside interpretation. vEEG, is a limited resource needing expert interpretation. We hypothesize that using aEEG combined with vEEG will increase the sensitivity and specificity of seizure detection and reduce anti-convulsants use compared to aEEG alone. Methods: Prospective cohort of neonates admitted to CHEO NICU with suspected seizures between April 1st 2018 to present. Seizures (clinical/aEEG) were documented by bedside clinicians and compared to the vEEG. Bedside clinicians could call a neurologist for remote review of the vEEG. Outcomes include concordance of aEEG and vEEG events and number of episodes where management was changed based on both readings Results: 27 patients had both modalities recording simultaneously. No seizure was identified by either modality in 23 recordings. Seizures were identified in 4 vEEG recordings; the aEEG partially identified these seizures.aEEG specificity of 0.87, negative predictive value 0.8, sensitivity 0.44 and positive predictive value 0.57Bedside clinician contacted a neurologist 9 times; in 2 cases, this prevented unnecessary treatment.Conclusions: In this small sample, aEEG had good specificity for ruling out seizures, but low sensitivity for detecting them. The new combined pathway may prevent unnecessary treatment.

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van Putten, Michel J. A. M. "Neonatal seizure detection." Clinical Neurophysiology 119, no. 11 (November 2008): 2417–18. http://dx.doi.org/10.1016/j.clinph.2008.08.012.

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Goswami, I., L. Bello-Espinosa, J. Buchhalter, H. Amin, A. Howlett, M. Esser, S. Thomas, et al. "P.058 Introduction of continuous video EEG monitoring into two different NICU models by training neonatal nurses." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 45, s2 (June 2018): S31. http://dx.doi.org/10.1017/cjn.2018.160.

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Background: Continuous video-EEG (cvEEG) monitoring is the standard of care for diagnosis and management of neonatal seizures. However, it is labour-intensive. We aimed to establish consistency in monitoring of newborns utilising NICU nurses. Methods: Neonatal nurses were trained to apply scalp electrodes, troubleshoot technical issues. Guidelines, checklists and visual training modules were developed. A central network system allowed remote access to the cvEEGs by the epileptologist for timely interpretation and feedback. We compared 100 infants with moderate to severe HIE before and after the training program. Results: 192 cvEEGs were performed. Of the 100 infants compared; time to initiate brain monitoring decreased by average of 31.5 hours, in electrographic seizure detection increased(20% compared to 34% a), seizure clinical misdiagnosis decreased (65% compared to 36% ), and Anti-Seizure burden decreased. Conclusions: Training experienced NICU nurses to set-up, start and monitor cvEEG can decrease the time to initiate cvEEG which may lead to better seizure diagnosis and management.

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Elakkiya, R. "Machine learning based intelligent automated neonatal epileptic seizure detection." Journal of Intelligent & Fuzzy Systems 40, no. 5 (April 22, 2021): 8847–55. http://dx.doi.org/10.3233/jifs-200800.

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Epilepsy is found to be the fourth most common chronic neurological disorder that tends to abnormal and unpredictable brain activity and seizure states. According to statistics, 70% of the epilepsy patients can be cured if identified and treated with anti-epileptic drugs or shock stimulations. Only about 7% to 8% need to be operated. Electroencephalogram (EEG) is a cheap and effective way to record the prolonged activities of the brain through electrical impulses between neural cells. Seizure is difficult to detect in neonates as the signal involves a lot of disturbances and the existing high accuracy system for adults can’t be used for neonates. In an attempt to build an impregnable system to detect seizure in early stages, EEG signals of neonates procured from Neonatal Intensive Care Unit (NICU) at the Helsinki University Hospital. These signals were processed and fed into three different robust algorithms –Support Vector Machine (SVM), Artificial Neural Network (ANN) and 1-Dimensional Convolutional Neural Network (1D-CNN). The experimental results were compared and the proposed CNN model with 95.99% accuracy outperforms all the state-of-art models for automated Epileptic Seizure prediction in Neonates. Deep CNN has been a powerful tool in extracting robust features from EEG signals. This generalized system can be used by medical experts for detecting Seizure in neonates with better accuracy and reliability.

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Boylan, G. B., and J. M. Rennie. "Automated neonatal seizure detection." Clinical Neurophysiology 117, no. 7 (July 2006): 1412–13. http://dx.doi.org/10.1016/j.clinph.2006.03.001.

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Asaduzzaman, Mohammad, Md Mizanur Rahman, and Mohammad Nadim Hasan. "Clinical Predictors of Poorly-Controlled Childhood Epilepsy: A Case-Control Study." Medicine Today 32, no. 2 (August 29, 2020): 85–90. http://dx.doi.org/10.3329/medtoday.v32i2.48819.

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Introduction:The aim of the present study was to determine clinical factors associated with poorly controlled epilepsy. Materials and Methods: This retrospective study was performed from January 2007 to December 2008 at Paediatric Neurology outpatient department in Bangabandhu Sheikh Mujib Medical University, Dhaka, among the children with epilepsy of 7 months to 15 years age who had history of at least 6 months treatment with rational antiepileptic drugs daily with adequate compliance. There were two groups of patients; group 1, consisted of 50 poorly controlled epilepsy patients and group 2, comprised 50 well-controlled epilepsy patients. We retrospectively reviewed EEGs and medical records from these children. Features of clinical findings were compared between the two groups. Results: In this study, age of onset of initial seizure before 1 year, mixed type of seizure, infantile spasm, high initial seizure frequency (daily seizure), symptomatic etiology, mental retardation, neonatal seizure and more than 20 seizures before starting treatment were also found to be significant clinical predictors of poorly controlled epilepsy. Multivariate analysis detected 2 independent clinical predictors of poorly controlled epilepsy: mixed seizures and more than 20 seizures before starting treatment. Conclusions: The study showed several clinical factors that can be identified early in the course of childhood epilepsy which can predict development of poor seizure control. Knowledge of these factors will help us to discriminate our patients and pay more attention to those at risk of developing poorly controlled epilepsy. Medicine Today 2020 Vol.32(2): 85-90

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Harsono, Mimily, Massroor Pourcyrous, Elliott J. Jolly, Amy de Jongh Curry, Alexander L. Fedinec, Jianxiong Liu, Shyamali Basuroy, Daming Zhuang, Charles W. Leffler, and Helena Parfenova. "Selective head cooling during neonatal seizures prevents postictal cerebral vascular dysfunction without reducing epileptiform activity." American Journal of Physiology-Heart and Circulatory Physiology 311, no. 5 (November 1, 2016): H1202—H1213. http://dx.doi.org/10.1152/ajpheart.00227.2016.

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Epileptic seizures in neonates cause cerebrovascular injury and impairment of cerebral blood flow (CBF) regulation. In the bicuculline model of seizures in newborn pigs, we tested the hypothesis that selective head cooling prevents deleterious effects of seizures on cerebral vascular functions. Preventive or therapeutic ictal head cooling was achieved by placing two head ice packs during the preictal and/or ictal states, respectively, for the ∼2-h period of seizures. Head cooling lowered the brain and core temperatures to 25.6 ± 0.3 and 33.5 ± 0.1°C, respectively. Head cooling had no anticonvulsant effects, as it did not affect the bicuculline-evoked electroencephalogram parameters, including amplitude, duration, spectral power, and spike frequency distribution. Acute and long-term cerebral vascular effects of seizures in the normothermic and head-cooled groups were tested during the immediate (2–4 h) and delayed (48 h) postictal periods. Seizure-induced cerebral vascular injury during the immediate postictal period was detected as terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling-positive staining of cerebral arterioles and a surge of brain-derived circulating endothelial cells in peripheral blood in the normothermic group, but not in the head-cooled groups. During the delayed postictal period, endothelium-dependent cerebral vasodilator responses were greatly reduced in the normothermic group, indicating impaired CBF regulation. Preventive or therapeutic ictal head cooling mitigated the endothelial injury and greatly reduced loss of postictal cerebral vasodilator functions. Overall, head cooling during seizures is a clinically relevant approach to protecting the neonatal brain by preventing cerebrovascular injury and the loss of the endothelium-dependent control of CBF without reducing epileptiform activity.

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Greene, Barry R., Philip de Chazal, Geraldine B. Boylan, Sen Connolly, and Richard B. Reilly. "Electrocardiogram Based Neonatal Seizure Detection." IEEE Transactions on Biomedical Engineering 54, no. 4 (April 2007): 673–82. http://dx.doi.org/10.1109/tbme.2006.890137.

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Garg, Ashish, Renu Suthar, Venkataseshan Sundaram, Praveen Kumar, and Suresh K. Angurana. "Clinical profile, aetiology, short-term outcome and predictors of poor outcome of neonatal seizures among out-born neonates admitted to a neonatal unit in Paediatric emergency of a tertiary care hospital in North India: A prospective observational study." Tropical Doctor 51, no. 3 (May 21, 2021): 365–71. http://dx.doi.org/10.1177/00494755211016226.

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Neonatal seizures are common manifestations of several neurological or systemic disorders and associated with high morbidity, mortality and poor short- and long-term developmental outcomes. It is important to determine the aetiology and factors that determine the poor outcome, more so in a newly developed setting. The early detection of predictors of poor outcome will help in planning acute management, counselling, follow-up and rehabilitation services. In this prospective observational study, we looked at the clinical profile, aetiology, short-term outcomes and predictors of poor outcome of neonatal seizures among out-born neonates. The common causes were hypoxic ischaemic encephalopathy, sepsis and metabolic disturbances. One-third of neonates had poor outcome. Abnormal neurological and cardiorespiratory examination at admission; low oxygen saturation, glucose and pH; and hypoxic ischemic encephalopathy-III were predictors of poor outcome.

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Anne, Rifat Taher, Md Zakirul Islam, Farhana Noman, Ferdousi Hasnat, Shamima Sharmin Shova, and Anjuman Ara. "Neonatal COVID-19 with Rare Presentation in COVID Dedicated Hospital of Bangladesh: A Case Report." Journal of National Institute of Neurosciences Bangladesh 7, no. 1 (January 1, 2021): 87–89. http://dx.doi.org/10.3329/jninb.v7i1.54760.

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Although Coronavirus disease (COVID-19) can affect all age groups, severity of clinical presentation among children and newborns are milder than in adults. Along with classical symptoms, atypical presentation could be noted in the neonate. We report here a case of neonatal COVID-19 where a newborn infant presented with fever, lethargy, respiratory distress and recurrent seizure. Early detection and prompt management is the prerequisite for limiting transmission and reducing neonatal death rate. Journal of National Institute of Neurosciences Bangladesh, January 2021, Vol. 7, No. 1, pp. 87-89

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Kozhanova, T. V., S. S. Zhilina, T. I. Mescheryakova, E. G. Lukyanova, K. V. Osipova, S. O. Ayvazyan, and A. G. Prityko. "Mutation of the ALDH7A1 gene in a patient with pyridoxal phosphate-dependent neonatal epileptic encephalopathy: a clinical case." Epilepsia and paroxysmal conditions 11, no. 1 (April 27, 2019): 70–78. http://dx.doi.org/10.17749/2077-8333.2019.11.1.70-78.

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The article presents a clinical case of severe infantile generalized idiopathic epilepsy with status-like seizures, muscular dystonia and developmental delay. The examination included a phenotypic analysis: the course of the perinatal period, the nature of seizures, cognitive and behavioral disorders; video electroencephalography, and brain MRI. Using the targeted exome sequencing of genes associated with epileptic encephalopathy (NGS), we detected a nucleotide heterozygous variant of the ALDH7A1 gene (previously not described). This mutation led to the appearance of a stop codon in position 82 of the protein p.Arg82Ter and the amino acid substitution in position 399 of the protein p.Glu399Gln. This clinical observation demonstrates the importance of DNA-based diagnosis involving the targeted exome sequencing to identify molecular defects, especially in severe neonatal drug-resistant seizures. In the case of confirmed mutations in the ALDH7A1 gene, the patient should be given vitamin B6 at the therapeutic doses for seizure relief.

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Millichap, J. Gordon. "Automatic Neonatal Seizure Detection by EEG." Pediatric Neurology Briefs 11, no. 10 (October 1, 1997): 78. http://dx.doi.org/10.15844/pedneurbriefs-11-10-11.

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Edwards, David A., Hina P. Shah, Wengang Cao, Nikolaus Gravenstein, Christoph N. Seubert, and Anatoly E. Martynyuk. "Bumetanide Alleviates Epileptogenic and Neurotoxic Effects of Sevoflurane in Neonatal Rat Brain." Anesthesiology 112, no. 3 (March 1, 2010): 567–75. http://dx.doi.org/10.1097/aln.0b013e3181cf9138.

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Background We tested the hypothesis that in newborn rats, sevoflurane may cause seizures, neurotoxicity, and impairment in synaptic plasticity-effects that may be diminished by the Na-K-2Cl cotransporter 1 inhibitor, bumetanide. Methods Electroencephalography, activated caspase-3, and hippocampal long-term potentiation were measured in rats exposed to 2.1% sevoflurane for 0.5-6 h at postnatal days 4-17 (P4-P17). Results Arterial blood gas samples drawn at a sevoflurane concentration of 2.1% showed no evidence of either hypoxia or hypoventilation in spontaneously breathing rats. Higher doses of sevoflurane (e.g., 2.9%) caused respiratory depression. During anesthesia maintenance, the electroencephalography exhibited distinctive episodes of epileptic seizures in 40% of P4-P8 rats. Such seizure-like activity was not detected during anesthesia maintenance in P10-P17 rats. Emergence from 3 h of anesthesia with sevoflurane resulted in tonic/clonic seizures in some P10-P17 rats but not in P4-P8 rats. Bumetanide (5 micromol/kg, intraperitoneally) significantly decreased seizures in P4-P9 rats but did not affect the emergence seizures in P10-P17 rats. Anesthesia of P4 rats with sevoflurane for 6 h caused a significant increase in activated caspase-3 and impairment of long-term potentiation induction measured at 1 and 14-17 days after exposure to sevoflurane, respectively. Pretreatment of P4 rats with bumetanide nearly abolished the increase in activated caspase-3 but did not alleviate impairment of long-term potentiation. Conclusion These results support the possibility that excitatory output of sevoflurane-potentiated gamma-aminobutyric acid type A/glycine systems may contribute to epileptogenic and neurotoxic effects in early postnatal rats.

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Lees, D., R. Moberg, S. Kassam, and R. Clancy. "AUTOMATED DETECTION OF NEONATAL SEIZURES." Journal of Neurosurgical Anesthesiology 9, no. 1 (January 1997): 90. http://dx.doi.org/10.1097/00008506-199701000-00044.

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Sastry, C. P. V. Ramana, and R. Manohar Reddy. "Study of prevalence and clinical spectrum of seizures in children in a teaching hospital in rural Telangana, India." International Journal of Contemporary Pediatrics 5, no. 3 (April 20, 2018): 862. http://dx.doi.org/10.18203/2349-3291.ijcp20181503.

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Background: To study the prevalence and clinical spectrum of seizures and treatment outcome in children.Methods: A hospital based prospective study was done at Maheshwara Medical College and Hospital, Patancheru, Telangana in the department of Paediatrics over one-year period. A total of 75 cases presenting with seizures were studied for demographics, clinical features, imaging studies where possible and patient response to treatment. Results: T Patient age ranged from one week to 14 years with male to female ratio of 1:4. Majority were in the age group of 1-3 years 25/75 (33.3%). Fever was present on admission in 66.6% of cases in 1 month to 6 years. Unprovoked seizure was common 20/75 (26.6%) in age group 6 to14 years. Neonatal seizures were seen in 6.6% cases. Generalized tonic clonic seizures were common and were seen in 63.3% cases. Only 5 (6.6 %) cases presented with status epilepticus. CT scan was done in 20 cases in unprovoked seizures and showed various etiologies. Conclusions: Seizures in children are a common indication for hospital admission. They can be febrile or unprovoked. CNS infections and space occupying lesions are common causes for paediatric seizures. Early detection of the cause of seizures helps in instituting appropriate treatment. Children with unprovoked seizures should be on regular long term follow up and treatment.

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Simeone, Claire, Deborah Fauquier, Jennifer Skidmore, Peter Cook, Kathleen Colegrove, Frances Gulland, Sophie Dennison, and Teresa K. Rowles. "Clinical signs and mortality of non-released stranded California sea lions housed in display facilities: the suspected role of prior exposure to algal toxins." Veterinary Record 185, no. 10 (August 19, 2019): 304. http://dx.doi.org/10.1136/vr.105371.

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Stranded California sea lions considered unable to survive in the wild are often placed in public display facilities. Exposure to the biotoxin domoic acid (DA) is a common cause of stranding, and chronic effects are observed long after initial exposure. Medical records for 171 sea lions placed in US institutions between 2000 and 2016 were reviewed, including results from clinical examinations, histopathology, behavioural testing and advanced imaging. There was a statistically significant increase in neurological disease detected in neonates (24%) compared with other age classes (11%). Sixty per cent of all neurological cases died during the study period. In the 11 neurological neonate cases, six died (55%) and five are still alive with three of five developing epilepsy during placement. Of the six neurological neonate cases that died, one was attributed to DA toxicosis, one to seizures and four to acute unexplained neurological disease. This survey suggests delayed neurological disease can develop in sea lions after stranding as neonates. These data coupled with stranding records and epidemiological data on DA-producing algal blooms suggest further research into effects of neonatal exposure to DA on risk of neurological disease in later life is warranted. California sea lions offer a natural model of DA exposure to study such effects.

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Zimova, Z., K. Matasova, and M. Zibolen. "Amplitude-Integrated Electroencephalography: Classification and Possibilities of Use in Practice." Acta Medica Martiniana 5, no. 1 (May 1, 2015): 27–35. http://dx.doi.org/10.1515/acm-2015-0004.

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Abstract Amplitude-integrated electroencephalography (aEEG) is a simplified bedside neurophysiology tool that has become widely used in neonates in the last few years. Although aEEG cannot replace conventional EEG (cEEG) for background monitoring and detection of seizures, it remains a useful apparatus that complements conventional EEG, is being widely adopted by neonatologists, and should be supported by neonatal neurologists. Limited channel leads are applied to the patient and data are displayed in a semilogarithmic, time-compressed scale. In term neonates, aEEG has been used to determine the prognosis and treatment for those affected by hypoxic-ischemic encephalopathy, seizures, meningitis and even congenital heart disease. In preterm infants, normative values and pattern corresponding to gestational age are being established. The senzitivity and specificity of aEEG are enhanced by the display of a simultaneous raw EEG.

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Morozova, E. A., R. R. Sergeeva, and D. V. Morozov. "Practical aspects of diagnosis and treatment of neonatal seizures." Epilepsia and paroxyzmal conditions 10, no. 4 (March 1, 2019): 17–25. http://dx.doi.org/10.17749/2077-8333.2018.10.4.017-025.

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Aim– analyze the current practice of management in patients with neonatal seizures and perinatal brain disorders, and determine the ways to prevent long-term neurological complications.Materials and methods.The study group included 140 children (aged from 2 weeks to 18 months) with neonatal seizures and perinatal brain abnormalities. In these cases, the obstetric and early postnatal history was analyzed; all patients underwent video-EEG monitoring, cervical spine X-ray, neuroimaging, and a Doppler ultrasound test.Results.We found a number of reliable ante- and intra- partum predictors of neonatal seizures. According to the medical documentation from the neonatal pathology departments, local neonatologists have difficulties in diagnosing and verifying the type and duration of seizures. In most patients with neonatal seizures, we detected epileptiform EEG activity, signs of birth defects (according to X-ray) and marked changes (according to neuroimaging) in the cervical spine.Conclusion.The results confirm that neonatal seizures are one of the first symptoms of severe brain damage, including intra-natal damage. Evolution of neonatal seizures into drug-resistant epilepsy and further disability is associated with insufficient knowledge of neonatal seizures, standards for their diagnosis, therapy and multidisciplinary observation.

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Temko, A., E. Thomas, W. Marnane, G. Lightbody, and G. B. Boylan. "Performance assessment for EEG-based neonatal seizure detectors." Clinical Neurophysiology 122, no. 3 (March 2011): 474–82. http://dx.doi.org/10.1016/j.clinph.2010.06.035.

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Pradhan, Janaki Ballav, and C. N. Kamalarathnam. "Clinical profiles and outcomes of neonates with neonatal hyperbilirubinemia and treated with double volume exchange transfusion: a retrospective study." International Journal of Contemporary Pediatrics 6, no. 5 (August 23, 2019): 2178. http://dx.doi.org/10.18203/2349-3291.ijcp20193748.

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Background: Double volume exchange transfusion (DVET) for severe unconjugated hyperbilirubinemia has become less common events now days in pediatric practices. But kernicterus is still common in low income country like India. The aim of the study was to determine the clinical profile and outcome in neonates who were treated with DVET.Methods: This was a retrospective study in neonate’s ≥34 weeks of gestation that were treated with DVET for severe neonatal hyperbilirubinemia over a period of four years.Results: In our study, 37 neonates underwent DVET. Male neonates (62.13%) and normal vaginal delivery (NVD) (70.2%) are common. ABO Isoimmunisation was commonest cause (56.75%) of exchange transfusion. The mean TSBR at pre exchange and Post Exchange were 27.39 ± 5.99mg/dl and 15.16 ± 4.00mg/dl (p<0.05). Ten neonates (27%) among 37 neonates required twice DVET.Thrombocytopenia14 (37.83%); Seizure 5(13.5%) and Hypocalcaemia 3(8.1%) were common complication noted among total 17 (45.94%) neonates. BIND occurred in 15 neonates (40.5%) at the time of admission and seven (18.9%) neonates had persistent neurological abnormality at discharge. Neonate with BIND had early onset of jaundice (44.13±15.37 hours vs. 61.22±28.23hrs, p<0.05), with higher pre exchange TSBR value(28.96 ±8.5mg/dl vs. 26.22±3.17mg/dl). Neonates admitted with BIND had higher percentage of persistent encephalopathy (40% vs. 4.5%,p<0.05), abnormal tone (33.3% vs. 4.5%,p<0.05), abnormal feeding (33.3% vs. 4.5%,p<0.05) and abnormal posture (26.6% vs. 0%,p<0.05) at discharge as compared to those without BIND. No death occurred in this study population.Conclusions: Early detection and aggressive therapy with DVET can prevent neonates from brain injury.

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TEMKO, ANDRIY, GERALDINE BOYLAN, WILLIAM MARNANE, and GORDON LIGHTBODY. "ROBUST NEONATAL EEG SEIZURE DETECTION THROUGH ADAPTIVE BACKGROUND MODELING." International Journal of Neural Systems 23, no. 04 (June 9, 2013): 1350018. http://dx.doi.org/10.1142/s0129065713500184.

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Adaptive probabilistic modeling of the EEG background is proposed for seizure detection in neonates with hypoxic ischemic encephalopathy. The decision is made based on the temporal derivative of the seizure probability with respect to the adaptively modeled level of background activity. The robustness of the system to long duration "seizure-like" artifacts, in particular those due to respiration, is improved. The system was developed using statistical leave-one-patient-out performance assessment, on a large clinical dataset, comprising 38 patients of 1479 h total duration. The developed technique was then validated by a single test on a separate totally unseen randomized prospective dataset of 51 neonates totaling 2540 h of duration. By exploiting the proposed adaptation, the ROC area is increased from 93.4% to 96.1% (41% relative improvement). The number of false detections per hour is decreased from 0.42 to 0.24, while maintaining the correct detection of seizure burden at 70%. These results on the unseen data were predicted from the rigorous leave-one-patient-out validation and confirm the validity of our algorithm development process.

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Pisani, Francesco, and Elena Pavlidis. "The role of electroencephalogram in neonatal seizure detection." Expert Review of Neurotherapeutics 18, no. 2 (December 8, 2017): 95–100. http://dx.doi.org/10.1080/14737175.2018.1413352.

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Temko, Andriy, William Marnane, Geraldine Boylan, and Gordon Lightbody. "Clinical implementation of a neonatal seizure detection algorithm." Decision Support Systems 70 (February 2015): 86–96. http://dx.doi.org/10.1016/j.dss.2014.12.006.

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Faul, Stephen, Geraldine Boylan, Sean Connolly, Liam Marnane, and Gordon Lightbody. "An evaluation of automated neonatal seizure detection methods." Clinical Neurophysiology 116, no. 7 (July 2005): 1533–41. http://dx.doi.org/10.1016/j.clinph.2005.03.006.

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Low, E., N. J. Stevenson, A. Temko, G. Lightbody, W. P. Marnane, V. Livingstone, S. R. Mathieson, C. A. Ryan, J. M. Rennie, and G. B. Boylan. "Clinical Validation of a Neonatal Seizure Detection Algorithm." Pediatric Research 70 (November 2011): 135. http://dx.doi.org/10.1038/pr.2011.360.

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Bogaarts, G., E. Gommer, V. van Kranen-Mastenbroek, D. Hilkman, and J. Reulen. "P119: Feature pre-processing for neonatal seizure detection." Clinical Neurophysiology 125 (June 2014): S79. http://dx.doi.org/10.1016/s1388-2457(14)50264-7.

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Ramantani, Georgia, Bernhard Schmitt, Barbara Plecko, Ronit M. Pressler, Gabriele Wohlrab, Katrin Klebermass-Schrehof, Cornelia Hagmann, Francesco Pisani, and Geraldine B. Boylan. "Neonatal Seizures—Are We there Yet?" Neuropediatrics 50, no. 05 (July 24, 2019): 280–93. http://dx.doi.org/10.1055/s-0039-1693149.

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AbstractNeonatal seizures are the most prevalent and distinctive sign of neurologic dysfunction in early life and pose an immense challenge for clinicians. Improvements in neonatal care have increased the survival rate of extremely premature infants, considerably changing the spectrum of underlying etiologies, and instigating a gradual shift from mortality to morbidity. Recognizing neonatal seizures can be challenging due to variability in presentation but clinical features can often provide valuable clues about etiology. Yet, the majority of neonatal seizures are subclinical. Even though conventional electroencephalography (EEG) with simultaneous video detection of seizures still represents the diagnostic gold standard, continuous monitoring using a one- to two-channel amplitude-integrated EEG with concurrent unprocessed EEG can be crucial for early recognition and intervention. Furthermore, tremendous progress has been made in neuroimaging, and all infants with seizures should have a magnetic resonance imaging (MRI) to help identify the underlying etiology. While the majority of neonatal seizures are caused by hypoxic-ischemic events, stroke, hemorrhage, or infection, approximately 15% of patients will require more sophisticated algorithms for diagnostic workup, including metabolic and genetic screening. These recent developments have led to renew interest in the classification of neonatal seizures, which aim to help identify etiology and guide appropriate therapeutic and prognostic decisions. In this review, we outline recent progress made in the etiology, diagnosis, and treatment of neonatal seizures and highlight areas that deserve further research.

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Kanta, Shayla Imam, MAK Azad Chowdhury, Dilara Begum, and Naila Z. khan. "Collaborative Services of Pediatric Neurosciences Department for the Early Detection of Neurodevelopmental High-Risk Neonates in Dhaka Shishu (Children) Hospital (DSH)." Scholars Journal of Applied Medical Sciences 9, no. 6 (June 3, 2021): 794–98. http://dx.doi.org/10.36347/sjams.2021.v09i06.005.

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Introduction: A majority of neonates present with histories of brain insult in the antenatal, natal and post-natal periods. Identification, appropriate assessment and intervention are crucial for best neurodevelopmental outcomes. In DSH the Pediatric Neuroscience Department (PND) is working in this regard in the neonatal ward as well as in its Child Development Center (CDC) with a multi-disciplinary team of professionals. Objectives: To describe the activities of PND in the management of high risk neonates. Methods: This was an observational study. From July 2017- December 2017every high risk neonate admitted in the neonatology department of Dhaka Shishu Hospital, the largest children hospital was assessed for neurodevelopmental assessment by the Rapid Neurodevelopmental Assessment (RNDA) tool by a Developmental Therapist. RNDA is a validated tool for neurodevelopmental assessment applied for ages between 0-16 Years. Different domains like gross motor, fine motor, vision, hearing, speech, cognition, behavior and seizures are seen and categorized into normal, mild, moderate and severe impairments. Neonates with moderate to severe impairments are then referred to the CDC for a general developmental assessment under the supervision of a pediatric neurologist; with regular follow ups. Interventions for different comorbidities are provided nutritional and feeding advice. Mild groups are also followed up by developmental therapists up to a maximum of 2 years. In the walk-in OPD of the department this same protocol is followed. Result: Approximately 650 patients were seen; among them 220 needed general developmental assessment on the basis of moderate to severe impairment. Among the impaired and non-impaired group there were difference in Term, preterm, birth weight and gestational age, Soocoidemography showed irregular antenatal care, bad obstetrical history and malnutrition has important impact. Conclusion: Every neonate who is at high risk needs assessment, evaluation,

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Zwanenburg, Alex, Peter Andriessen, Reint K. Jellema, Hendrik J. Niemarkt, Tim GAM Wolfs, Boris W. Kramer, and Tammo Delhaas. "Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model." Physiological Measurement 36, no. 3 (February 5, 2015): 369–84. http://dx.doi.org/10.1088/0967-3334/36/3/369.

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Mathieson, Sean R., Vicki Livingstone, Evonne Low, Ronit Pressler, Janet M. Rennie, and Geraldine B. Boylan. "Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection." Clinical Neurophysiology 127, no. 10 (October 2016): 3343–50. http://dx.doi.org/10.1016/j.clinph.2016.07.007.

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Grass, Beate, Blondel Crosdale, Matthew Keyzers, Poorva Deshpande, Cecil Hahn, Linh G. Ly, and Patrick J. McNamara. "Implementation of amplitude-integrated electroencephalography in tertiary Canadian Neonatal Intensive Care Units—a longitudinal study." Paediatrics & Child Health 25, no. 8 (October 10, 2019): 511–17. http://dx.doi.org/10.1093/pch/pxz091.

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Abstract Aim To investigate the implementation of amplitude-integrated electroencephalography (aEEG) as bedside monitoring tool of cerebral function in tertiary Canadian Neonatal Intensive Care Units (NICU) over the past decade. Methods Longitudinal study consisting of online surveys of neonatologists on the use of aEEG in 2009 and 2018. Results The response rate to the survey was 72 of 149 (49%) in 2009 and 18 of 30 (60%) in 2018, respectively. aEEG has been implemented in almost all (2009: 62.5%; 2018: 94%) tertiary Canadian NICUs. Two-thirds (2009: 67%; 2018: 71%) of the respondents considered information from aEEG tracing helpful in clinical practice. The main indications for aEEG were term neonates with hypoxic ischemic encephalopathy (2009 and 2018: 76%) and seizure detection/surveillance (2009: 88%; 2018: 94%). Teaching on aEEG has been implemented for neonatologists (2018: 100%) and health care providers (2018: 50%) in tertiary Canadian NICUs but there is a lack of standardization of training. Use of aEEG in preterm neonates (2009: 37%, 2018: 33%) and application of aEEG in research (18% reported occasional use) is less common. Conclusion aEEG is well established in tertiary Canadian NICUs to monitor cerebral function and detect seizure activity. There is a need to develop formalized aEEG training programs and methods to assess competence. Further implementation of aEEG in preterm neonates and research is desirable.

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Beck, Jonathan, Cecile Grosjean, Nathalie Bednarek, and Gauthier Loron. "Amplitude-Integrated EEG Monitoring in Pediatric Intensive Care: Prognostic Value in Meningitis before One Year of Age." Children 9, no. 5 (May 5, 2022): 668. http://dx.doi.org/10.3390/children9050668.

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Pediatric morbidity from meningitis remains considerable. Preventing complications is a major challenge to improve neurological outcome. Seizures may reveal the meningitis itself or some complications of this disease. Amplitude-integrated electroencephalography (aEEG) is gaining interest for the management of patients with acute neurological distress, beyond the neonatal age. This study aimed at evaluating the predictive value of aEEG monitoring during the acute phase in meningitis among a population of infants hospitalized in the pediatric intensive care unit (PICU), and at assessing the practicability of the technique. AEEG records of 25 infants younger than one year of age hospitalized for meningitis were retrospectively analyzed and correlated to clinical data and outcome. Recording was initiated, on average, within the first six hours for n = 18 (72%) patients, and overall quality was considered as good. Occurrence of seizure, of status epilepticus, and the background pattern were significantly associated with unfavorable neurological outcomes. AEEG may help in the management and prognostic assessment of pediatric meningitis. It is an easily achievable, reliable technique, and allows detection of subclinical seizures with minimal training. However, it is important to consider the limitations of aEEG, and combinate it with conventional EEG for the best accuracy.

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Tanveer, M. Asjid, Muhammad Jawad Khan, Hasan Sajid, and Noman Naseer. "Convolutional neural networks ensemble model for neonatal seizure detection." Journal of Neuroscience Methods 358 (July 2021): 109197. http://dx.doi.org/10.1016/j.jneumeth.2021.109197.

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Altenburg, Josje, R. Jeroen Vermeulen, Rob L. M. Strijers, Willem P. F. Fetter, and Cornelis J. Stam. "Seizure detection in the neonatal EEG with synchronization likelihood." Clinical Neurophysiology 114, no. 1 (January 2003): 50–55. http://dx.doi.org/10.1016/s1388-2457(02)00322-x.

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Alegre, M., and E. Urrestarazu. "Neonatal automated seizure detection: Going ahead into clinical use." Clinical Neurophysiology 122, no. 8 (August 2011): 1480–81. http://dx.doi.org/10.1016/j.clinph.2011.01.044.

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Journal articles on the topic 'Neonatal Seizure Detector'

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