Machine learning models of cerebral oxygenation (rcSO2) for brain injury detection in neonates with hypoxic-ischaemic encephalopathy.

The present study was designed to test the potential utility of regional cerebral oxygen saturation (rcSO2) in detecting term infants with brain injury. The study also examined whether quantitative rcSO2 features are associated with grade of hypoxic ischaemic encephalopathy (HIE). We analysed 58 term infants with HIE (>36 weeks of gestational age) enrolled in a prospective observational study. All newborn infants had a period of continuous rcSO2 monitoring and magnetic resonance imaging (MRI) assessment during the first week of life. rcSO2 Signals were pre-processed and quantitative features were extracted. Machine-learning and deep-learning models were developed to detect adverse outcome (brain injury on MRI or death in the first week) using the leave-one-out cross-validation approach and to assess the association between rcSO2 and HIE grade (modified Sarnat - at 1 h). The machine-learning model (rcSO2 excluding prolonged relative desaturations) significantly detected infant MRI outcome or death in the first week of life [area under the curve (AUC) = 0.73, confidence interval (CI) = 0.59-0.86, Matthew's correlation coefficient = 0.35]. In agreement, deep learning models detected adverse outcome with an AUC = 0.64, CI = 0.50-0.79. We also report a significant association between rcSO2 features and HIE grade using a machine learning approach (AUC = 0.81, CI = 0.73-0.90). We conclude that automated analysis of rcSO2 using machine learning methods in term infants with HIE was able to determine, with modest accuracy, infants with adverse outcome. De novo approaches to signal analysis of NIRS holds promise to aid clinical decision making in the future. KEY POINTS: Hypoxic-induced neonatal brain injury contributes to both short- and long-term functional deficits. Non-invasive continuous monitoring of brain oxygenation using near-infrared- spectroscopy offers a potential new insight to the development of serious injury. In this study, characteristics of the NIRS signal were summarised using either predefined features or data-driven feature extraction, both were combined with a machine learning approach to predict short-term brain injury. Using data from a cohort of term infants with hypoxic ischaemic encephalopathy, the present study illustrates that automated analysis of regional cerebral oxygen saturation rcSO2, using either machine learning or deep learning methods, was able to determine infants with adverse outcome.

Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy.

OBJECTIVE: To assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE). METHODS: Clinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC). RESULTS: The study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720. SIGNIFICANCE: Early EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.

Neonatal Seizure Management: Is the Timing of Treatment Critical?

OBJECTIVE: To assess the impact of the time to treatment of the first electrographic seizure on subsequent seizure burden and describe overall seizure management in a large neonatal cohort. STUDY DESIGN: Newborns (36-44 weeks of gestation) requiring electroencephalographic (EEG) monitoring recruited to 2 multicenter European studies were included. Infants who received antiseizure medication exclusively after electrographic seizure onset were grouped based on the time to treatment of the first seizure: antiseizure medication within 1 hour, between 1 and 2 hours, and after 2 hours. Outcomes measured were seizure burden, maximum seizure burden, status epilepticus, number of seizures, and antiseizure medication dose over the first 24 hours after seizure onset. RESULTS: Out of 472 newborns recruited, 154 (32.6%) had confirmed electrographic seizures. Sixty-nine infants received antiseizure medication exclusively after the onset of electrographic seizure, including 21 infants within 1 hour of seizure onset, 15 between 1 and 2 hours after seizure onset, and 33 at >2 hours after seizure onset. Significantly lower seizure burden and fewer seizures were noted in the infants treated with antiseizure medication within 1 hour of seizure onset (P = .029 and .035, respectively). Overall, 258 of 472 infants (54.7%) received antiseizure medication during the study period, of whom 40 without electrographic seizures received treatment exclusively during EEG monitoring and 11 with electrographic seizures received no treatment. CONCLUSIONS: Treatment of neonatal seizures may be time-critical, but more research is needed to confirm this. Improvements in neonatal seizure diagnosis and treatment are also needed.

Evolution of early cerebral NIRS in hypoxic ischaemic encephalopathy.

AIM: To describe early cerebral oxygenation (cSO2 ) and fractional tissue oxygen extraction (FTOE) values and their evolution over the first days of life in infants with all grades of hypoxic-ischaemic encephalopathy (HIE) and to determine whether cSO2 and FTOE measured early (6 and 12 h) can predict short-term outcome. METHODS: Prospective, observational study of cerebral near-infrared spectroscopy (NIRS) in infants >36 weeks' gestation with HIE. Ten one-hour epochs of cSO2 and FTOE were extracted for each infant over the first 84 h. Infants with moderate and severe HIE received therapeutic hypothermia (TH). Abnormal outcome was defined as abnormal magnetic resonance imaging (MRI) and/or death. RESULTS: Fifty-eight infants were included (28 mild, 24 moderate, 6 severe). Median gestational age was 39.9 weeks (IQR 38.1-40.7) and birthweight was 3.35 kgs (IQR 2.97-3.71). cSO2 increased and FTOE decreased over the first 24 h in all grades of HIE. Compared to the moderate group, infants with mild HIE had significantly higher cSO2 at 6 h (p = 0.003), 9 h (p = 0.009) and 12 h (p = 0.032) and lower FTOE at 6 h (p = 0.016) and 9 h (0.029). cSO2 and FTOE at 6 and 12 h did not predict abnormal outcome. CONCLUSION: Infants with mild HIE have higher cSO2 and lower FTOE than those with moderate or severe HIE in the first 12 h of life. cSO2 increased in all grades of HIE over the first 24 h regardless of TH status.

Multichannel EEG abnormalities during the first 6 hours in infants with mild hypoxic-ischaemic encephalopathy.

BACKGROUND: Infants with mild HIE are at risk of significant disability at follow-up. In the pre-therapeutic hypothermia (TH) era, electroencephalography (EEG) within 6 hours of birth was most predictive of outcome. This study aims to identify and describe features of early EEG and heart rate variability (HRV) (<6 hours of age) in infants with mild HIE compared to healthy term infants. METHODS: Infants >36 weeks with mild HIE, not undergoing TH, with EEG before 6 hours of age were identified from 4 prospective cohort studies conducted in the Cork University Maternity Services, Ireland (2003-2019). Control infants were taken from a contemporaneous study examining brain activity in healthy term infants. EEGs were qualitatively analysed by two neonatal neurophysiologists and quantitatively assessed using multiple features of amplitude, spectral shape and inter-hemispheric connectivity. Quantitative features of HRV were assessed in both the groups. RESULTS: Fifty-eight infants with mild HIE and sixteen healthy term infants were included. Seventy-two percent of infants with mild HIE had at least one abnormal EEG feature on qualitative analysis and quantitative EEG analysis revealed significant differences in spectral features between the two groups. HRV analysis did not differentiate between the groups. CONCLUSIONS: Qualitative and quantitative analysis of the EEG before 6 hours of age identified abnormal EEG features in mild HIE, which could aid in the objective identification of cases for future TH trials in mild HIE. IMPACT: Infants with mild HIE currently do not meet selection criteria for TH yet may be at risk of significant disability at follow-up. In the pre-TH era, EEG within 6 hours of birth was most predictive of outcome; however, TH has delayed this predictive value. 72% of infants with mild HIE had at least one abnormal EEG feature in the first 6 hours on qualitative assessment. Quantitative EEG analysis revealed significant differences in spectral features between infants with mild HIE and healthy term infants. Quantitative EEG features may aid in the objective identification of cases for future TH trials in mild HIE.

No effect of a musical intervention on stress response to venepuncture in a neonatal population.

AIM: To investigate the effect of a musical intervention on neonatal stress response to venepuncture as measured by salivary cortisol levels and pain profile scores. METHODS: In a randomised control crossover trial, participants were randomised to both a control arm (sucrose) and intervention arm (sucrose and music) for routine venepuncture procedures. Salivary swabs were collected at baseline, 20 minutes post-venepuncture and 4 hours post-venepuncture. Pain levels were assessed using the Premature Infant Pain Profile (PIPP). A total of 16 preterm neonates participated in both arms to complete the study. RESULTS: Cortisol values were elevated at all timepoints in the intervention arm (baseline, 20 minutes, and 4 hours post-procedure) but not significantly so (P = .056, P = .3, and P = .575, respectively). Median change in cortisol values from baseline was +128.48 pg/mL (-47.66 to 517.02) at 20 minutes and +393.52 pg/mL (47.88-1221.34) at 4 hours post-procedure in the control arm compared to -69.564 pg/mL (-860.96 to 397.289) and +100.48 pg/mL (-560.46 to 842.99) at 20 minutes and 4 hours post-procedure in the intervention arm. There was no statistically significant difference observed between groups (P = .311 at 20 minutes, and P = .203 at 4 hours post-procedure). PIPP scores were not significantly different between study arms. CONCLUSION: Our findings did not support the additional benefit of music intervention on neonatal stress response to venepuncture in preterm infants.

Clamping the Umbilical Cord in Premature Deliveries (CUPiD): Neuromonitoring in the Immediate Newborn Period in a Randomized, Controlled Trial of Preterm Infants Born at <32 Weeks of Gestation.

OBJECTIVE: To compare cerebral activity and oxygenation in preterm infants (<32 weeks of gestation) randomized to different cord clamping strategies. STUDY DESIGN: Preterm infants born at <32 weeks of gestation were randomized to immediate cord clamping, umbilical cord milking (cord stripped 3 times), or delayed cord clamping for 60 seconds with bedside resuscitation. All infants underwent electroencephalogram (EEG) and cerebral near infrared spectroscopy for the first 72 hours after birth. Neonatal primary outcome measures were quantitative measures of the EEG (17 features) and near infrared spectroscopy over 1-hour time frames at 6 and 12 hours of life. RESULTS: Forty-five infants were recruited during the study period. Twelve infants (27%) were randomized to immediate cord clamping, 19 (42%) to umbilical cord milking, and 14 (31%) to delayed cord clamping with bedside resuscitation. There were no significant differences between groups for measures of EEG activity or cerebral near infrared spectroscopy. Three of the 45 infants (6.7%) were diagnosed with severe IVH (2 in the immediate cord clamping group, 1 in the umbilical cord milking group; P = .35). CONCLUSIONS: There were no differences in cerebral EEG activity and cerebral oxygenation values between cord management strategies at 6 and 12 hours. TRIAL REGISTRATION: ISRCTN92719670.

Importance of H-FABP in Early Diagnosis of Acute Myocardial Infarction.

Background: Over the years, troponins have aced the para-clinical tests for confirming the diagnosis of acute myocardial infarction. However, the rise in their levels is entirely time-dependent, which can cause a delay in the initiation of treatment protocols. Heart fatty acid binding protein (H-FABP) can serve comparatively as a better biological marker for overcoming this flaw of troponins, as it is quickly released into the bloodstream once the myocardial injury occurs due to decreased blood supply. This study aimed to evaluate the usefulness of this marker as well as establish the specificity and sensitivity of testing the H-FABP, if it adds to early diagnosis and can be relied upon in the future. Material and Methods: We evaluated 83 patients and their H-FABP levels, along with the standard cardiac markers like hsTni and CK-MB, in patients presenting with symptoms indicating an ongoing coronary event, who had presented to our hospital between August 2020 and June 2021. The patients were divided into two groups: group 1 comprised patients who had first medical contact within 4 hours of the onset of chest pain, and group 2 patients who had first medical contact after 4 hours of the appearance of symptoms. Statistical analysis was performed using MedCalc v20.023, considering statistical significance values of p <0.05. Results for targeted variables are presented using descriptive statistics (mean, standard deviation, range, median, and associated interquartile range) for continuous data, and counts with associated percentages for categorical data. Results: H-FABP was found to have better sensitivity and specificity of 89.67 and 95.65 in group 1 patients and 86.73 and 49.84, respectively, in group 2 patients. The other two cardiac biomarkers evaluated had lower values in response to H-FABP in the first 4 hours of presentation. Results for group 2 showed that specificitivity for hsTni is higher than that of H-FABP, that is, 69.98. Conclusion: Heart fatty acid binding protein (H-FABP) should be included in the protocol for biochemical evaluation of all patients presenting to the emergency services with a suspicion of possible myocardial infarction. Early detection of this protein can help in effective and timely management of myocardial infarction, thus further decreasing mortality rates and the financial burden on healthcare systems worldwide.

Temporal evolution of electrographic seizures in newborn infants with hypoxic-ischaemic encephalopathy requiring therapeutic hypothermia: a secondary analysis of the ANSeR studies.

BACKGROUND: Despite extensive research on neonatal hypoxic-ischaemic encephalopathy, detailed information about electrographic seizures during active cooling and rewarming of therapeutic hypothermia is sparse. We aimed to describe temporal evolution of seizures and determine whether there is a correlation of seizure evolution with 2-year outcome. METHODS: This secondary analysis included newborn infants recruited from eight European tertiary neonatal intensive care units for two multicentre studies (a randomised controlled trial [NCT02431780] and an observational study [NCT02160171]). Infants were born at 36+0 weeks of gestation with moderate or severe hypoxic-ischaemic encephalopathy and underwent therapeutic hypothermia with prolonged conventional video-electroencephalography (EEG) monitoring for 10 h or longer from the start of rewarming. Seizure burden characteristics were calculated based on electrographic seizures annotations: hourly seizure burden (minutes of seizures within an hour) and total seizure burden (minutes of seizures within the entire recording). We categorised infants into those with electrographic seizures during active cooling only, those with electrographic seizures during cooling and rewarming, and those without seizures. Neurodevelopmental outcomes were determined using the Bayley's Scales of Infant and Toddler Development, Third Edition (BSID-III), the Griffiths Mental Development Scales (GMDS), or neurological assessment. An abnormal outcome was defined as death or neurodisability at 2 years. Neurodisability was defined as a composite score of 85 or less on any subscales for BSID-III, a total score of 87 or less for GMDS, or a diagnosis of cerebral palsy (dyskinetic cerebral palsy, spastic quadriplegia, or mixed motor impairment) or epilepsy. FINDINGS: Of 263 infants recruited between Jan 1, 2011, and Feb 7, 2017, we included 129 infants: 65 had electrographic seizures (43 during active cooling only and 22 during and after active cooling) and 64 had no seizures. Compared with infants with seizures during active cooling only, those with seizures during and after active cooling had a longer seizure period (median 12 h [IQR 3-28] vs 68 h [35-86], p<0·0001), more seizures (median 12 [IQR 5-36] vs 94 [24-134], p<0·0001), and higher total seizure burden (median 69 min [IQR 22-104] vs 167 min [54-275], p=0·0033). Hourly seizure burden peaked at about 20-24 h in both groups, and infants with seizures during and after active cooling had a secondary peak at 85 h of age. When combined, worse EEG background (major abnormalities and inactive background) at 12 h and 24 h were associated with the seizure group: compared with infants with a better EEG background (normal, mild, or moderate abnormalities), infants with a worse EEG background were more likely to have seizures after cooling at 12 h (13 [54%] of 24 vs four [14%] of 28; odds ratio 7·09 [95% CI 1·88-26·77], p=0·0039) and 24 h (14 [56%] of 25 vs seven [18%] of 38; 5·64 [1·81-17·60], p=0·0029). There was a significant relationship between EEG grade at 12 h (four categories) and seizure group (p=0·020). High total seizure burden was associated with increased odds of an abnormal outcome at 2 years of age (odds ratio 1·007 [95% CI 1·000-1·014], p=0·046), with a medium negative correlation between total seizure burden and BSID-III cognitive score (rS=-0·477, p=0·014, n=26). INTERPRETATION: Overall, half of infants with hypoxic-ischaemic encephalopathy had electrographic seizures and a third of those infants had seizures beyond active cooling, with worse outcomes. These results raise the importance of prolonged EEG monitoring of newborn infants with hypoxic-ischaemic encephalopathy not only during active cooling but throughout the rewarming phase and even longer when seizures are detected. FUNDING: Wellcome Trust, Science Foundation Ireland, and the Irish Health Research Board.

Does Early Cerebral Near-Infrared Spectroscopy Monitoring Predict Outcome in Neonates with Hypoxic Ischaemic Encephalopathy? A Systematic Review of Diagnostic Test Accuracy.

INTRODUCTION: Hypoxic ischaemic encephalopathy (HIE) remains one of the top 10 contributors to the global burden of disease. Early objective biomarkers are required. Near-infrared spectroscopy (NIRS) may provide a valuable insight into cerebral perfusion and metabolism. We aimed to determine whether early NIRS monitoring (<6 h of age) can predict outcome as defined by grade of encephalopathy, brain MRI findings, and/or neurodevelopmental outcome at 1-2 years in infants with HIE. METHODS: We searched PubMed, Scopus, Web of Science, Embase, and The Cochrane Library databases (July 2019). Studies of infants born ≥36+0 weeks gestation with HIE who had NIRS recording commenced before 6 h of life were included. We planned to provide a narrative of all the studies included, and if similar clinically and methodologically, the results would be pooled in a meta-analysis to determine test accuracy. RESULTS: Seven studies were included with a combined total of 161 infants. Only 1 study included infants with mild HIE. A range of different oximeters and probes were utilized with varying outcome measures making comparison difficult. Although some studies showed a trend towards higher cSO2 values before 6 h in infants with adverse neurodevelopmental outcomes, in the majority, this was not significant until beyond 24 h of life. CONCLUSION: Very little data currently exists to assess the use of early NIRS to predict outcome in infants with HIE. Further studies using a standardized approach are required before NIRS can be evaluated as a potential objective assessment tool for early identification of at-risk infants.

Non-invasive continuous cardiac output monitoring in infants with hypoxic ischaemic encephalopathy.

OBJECTIVE: To describe early, continuous, non-invasive measures of cardiac output (CO) and evolution over time in infants with hypoxic-ischaemic encephalopathy (HIE). STUDY DESIGN: Prospective observational study of 44 infants with HIE (23 mild, 17 moderate, 4 severe) and 17 term controls. Infants with HIE had non-invasive CO monitoring (NICOM) continuously in the neonatal unit. Term controls had NICOM recorded at 6 and 24 h. A mixed-modelling approach was used to assess change in CO over time by group. RESULTS: Infants with moderate HIE have significantly lower CO than the mild group at all timepoints (10.7 mls/kg/min lower, 95% CI:1.0,20.4, p = 0.03) which increases over time, driven by a gradual increase in stroke volume (SV). CO increased further during rewarming predominantly due to an increase in HR. CONCLUSION: TH has a significant impact on HR but SV appears largely unaffected. NICOM may provide a non-invasive, continuous, low-cost alternative to monitoring CO in infants with HIE however further research is warranted.

Case Report: Early Neonatal EEG in Two Infants with Pallister Killian Syndrome (PKS).

Pallister Killian Syndrome (PKS) is a rare genetic disorder caused by a mosaic tetrasomy of the short arm of chromosome 12. The syndrome is characterised by typical craniofacial dysmorphism, congenital anomalies and intellectual disability. Epilepsy is a known complication, with onset usually occurring in early childhood and characterised most commonly by spasms and myoclonic seizures. To the best of our knowledge, there have been no cases describing the early neonatal EEG in PKS and  electrographic seizures, to date. Here, we report two cases of PKS presenting in the neonatal period with distinctive EEG features and seizures.

Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12†h of birth.

Background and aims: Heart rate variability (HRV) has previously been assessed as a biomarker for brain injury and prognosis in neonates. The aim of this cohort study was to use HRV to predict the electroencephalography (EEG) grade in neonatal hypoxic-ischaemic encephalopathy (HIE) within the first 12 h. Methods: We included 120 infants with HIE recruited as part of two European multi-centre studies, with electrocardiography (ECG) and EEG monitoring performed before 12 h of age. HRV features and EEG background were assessed using the earliest 1 h epoch of ECG-EEG monitoring. HRV was expressed in time, frequency and complexity features. EEG background was graded from 0-normal, 1-mild, 2-moderate, 3-major abnormalities to 4-inactive. Clinical parameters known within 6 h of birth were collected (intrapartum complications, foetal distress, gestational age, mode of delivery, gender, birth weight, Apgar at 1 and 5, assisted ventilation at 10 min). Using logistic regression analysis, prediction models for EEG severity were developed for HRV features and clinical parameters, separately and combined. Multivariable model analysis included 101 infants without missing data. Results: Of 120 infants included, 54 (45%) had normal-mild and 66 (55%) had moderate-severe EEG grade. The performance of HRV model was AUROC 0.837 (95% CI: 0.759-0.914) and clinical model was AUROC 0.836 (95% CI: 0.759-0.914). The HRV and clinical model combined had an AUROC of 0.895 (95% CI: 0.832-0.958). Therapeutic hypothermia and anti-seizure medication did not affect the model performance. Conclusions: Early HRV and clinical information accurately predicted EEG grade in HIE within the first 12 h of birth. This might be beneficial when EEG monitoring is not available in the early postnatal period and for referral centres who may want some objective information on HIE severity.

Signal Quality of Electrical Cardiometry and Perfusion Index in Very Preterm Infants.

OBJECTIVE: The use of noninvasive monitoring of neonatal hemodynamics is increasing in neonatal care. Methods include noninvasive cardiac output estimated by electrical cardiometry (EC) and peripheral perfusion as perfusion index (PI) using pulse oximetry. Our aim was to evaluate the feasibility to continuously monitor preterm infants with EC and PI during the first 2 postnatal days and the effects of averaging EC data in signal quality (SigQ) analysis. DESIGN: Prospective observational study. SETTING: Tertiary neonatal academic hospital. PATIENTS: Preterm infants <32 weeks gestation from birth until 48 h. MAIN OUTCOME MEASURES: Continuous EC and PI measurements. Feasibility was quantified as the time with high SigQ, classified using SigQ index in EC and exception codes in PI. Our predefined threshold for good feasibility was minimum of 24 h with high SigQ for both. RESULTS: Twenty-two preterm infants (median [IQR] gestational age 28 + 6 (26 + 0, 30 + 4) weeks + days, birth weight 960 [773, 1,500] g) were included. We recorded a minimum of 24 h with high SigQ in 14 infants for EC (unaveraged data) and 22 infants for PI measurements. The median (range) % of recording time with high SigQ was 74% (50%, 88%) for EC and 94% (82%, 96%) for PI. Using 1 minute averaging for EC data resulted in an increase of infants with minimum 24 h of high SigQ to 21 infants. CONCLUSIONS: EC and PI monitoring are feasible in preterm infants within the first 48 h, but SigQ remains problematic for EC. Signal dropout is masked in averaged EC values.

Case Report: Electroencephalography in a neonate with isolated sulfite oxidase deficiency - a case report and literature review.

Isolated sulfite oxidase deficiency (ISOD) is a rare autosomal recessive neuro-metabolic disorder caused by a mutation in the sulfite oxidase (SUOX) gene situated on chromosome 12. Due to the deficiency of this mitochondrial enzyme (sulfite oxidase), the oxidative degradation of toxic sulfites is disrupted. The most common form of this disease has an early onset (classical ISOD) in the neonatal period, with hypotonia, poor feeding and intractable seizures, mimicking hypoxic-ischaemic encephalopathy. The evolution is rapidly progressive to severe developmental delay, microcephaly and early death. Unfortunately, there is no effective treatment and the prognosis is very poor. In this article, we described the evolution of early continuous electroencephalography (EEG) in a case of ISOD with neonatal onset, as severely encephalopathic background, with refractory seizures and distinct delta-beta complexes. The presence of the delta-beta complexes might be a diagnostic marker in ISOD. We also performed a literature review of published cases of neonatal ISOD that included EEG monitoring.

Novel Point-of-Care Diagnostic Method for Neonatal Encephalopathy Using Purine Nucleosides.

Background: Evidence suggests that earlier diagnosis and initiation of treatment immediately after birth is critical for improved neurodevelopmental outcomes following neonatal encephalopathy (NE). Current diagnostic tests are, however, mainly restricted to clinical diagnosis with no molecular tests available. Purines including adenosine are released during brain injury such as hypoxia and are also present in biofluids. Whether blood purine changes can be used to diagnose NE has not been investigated to date. Methods: Blood purines were measured in a mouse model of neonatal hypoxia and infants with NE using a novel point-of-care diagnostic technology (SMARTChip) based on the summated electrochemical detection of adenosine and adenosine metabolites in the blood. Results: Blood purine concentrations were ∼2-3-fold elevated following hypoxia in mice [2.77 ± 0.48 µM (Control) vs. 7.57 ± 1.41 µM (post-hypoxia), p = 0.029]. Data in infants with NE had a 2-3-fold elevation when compared to healthy controls [1.63 ± 0.47 µM (Control, N = 5) vs. 4.87 ± 0.92 µM (NE, N = 21), p = 0.0155]. ROC curve analysis demonstrates a high sensitivity (81%) and specificity (80%) for our approach to identify infants with NE. Moreover, blood purine concentrations were higher in infants with NE and seizures [8.13 ± 3.23 µM (with seizures, N = 5) vs. 3.86 ± 0.56 µM (without seizures, N = 16), p = 0.044]. Conclusion: Our data provides the proof-of-concept that measurement of blood purine concentrations via SMARTChip technology may offer a low-volume bedside test to support a rapid diagnosis of NE.

A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.

BACKGROUND: Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could improve detection. We aimed to assess the diagnostic accuracy of an automated seizure detection algorithm called Algorithm for Neonatal Seizure Recognition (ANSeR). METHODS: This multicentre, randomised, two-arm, parallel, controlled trial was done in eight neonatal centres across Ireland, the Netherlands, Sweden, and the UK. Neonates with a corrected gestational age between 36 and 44 weeks with, or at significant risk of, seizures requiring EEG monitoring, received cEEG plus ANSeR linked to the EEG monitor displaying a seizure probability trend in real time (algorithm group) or cEEG monitoring alone (non-algorithm group). The primary outcome was diagnostic accuracy (sensitivity, specificity, and false detection rate) of health-care professionals to identify neonates with electrographic seizures and seizure hours with and without the support of the ANSeR algorithm. Neonates with data on the outcome of interest were included in the analysis. This study is registered with ClinicalTrials.gov, NCT02431780. FINDINGS: Between Feb 13, 2015, and Feb 7, 2017, 132 neonates were randomly assigned to the algorithm group and 132 to the non-algorithm group. Six neonates were excluded (four from the algorithm group and two from the non-algorithm group). Electrographic seizures were present in 32 (25·0%) of 128 neonates in the algorithm group and 38 (29·2%) of 130 neonates in the non-algorithm group. For recognition of neonates with electrographic seizures, sensitivity was 81·3% (95% CI 66·7-93·3) in the algorithm group and 89·5% (78·4-97·5) in the non-algorithm group; specificity was 84·4% (95% CI 76·9-91·0) in the algorithm group and 89·1% (82·5-94·7) in the non-algorithm group; and the false detection rate was 36·6% (95% CI 22·7-52·1) in the algorithm group and 22·7% (11·6-35·9) in the non-algorithm group. We identified 659 h in which seizures occurred (seizure hours): 268 h in the algorithm versus 391 h in the non-algorithm group. The percentage of seizure hours correctly identified was higher in the algorithm group than in the non-algorithm group (177 [66·0%; 95% CI 53·8-77·3] of 268 h vs 177 [45·3%; 34·5-58·3] of 391 h; difference 20·8% [3·6-37·1]). No significant differences were seen in the percentage of neonates with seizures given at least one inappropriate antiseizure medication (37·5% [95% CI 25·0 to 56·3] vs 31·6% [21·1 to 47·4]; difference 5·9% [-14·0 to 26·3]). INTERPRETATION: ANSeR, a machine-learning algorithm, is safe and able to accurately detect neonatal seizures. Although the algorithm did not enhance identification of individual neonates with seizures beyond conventional EEG, recognition of seizure hours was improved with use of ANSeR. The benefit might be greater in less experienced centres, but further study is required. FUNDING: Wellcome Trust, Science Foundation Ireland, and Nihon Kohden.