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.

Parent-led massage and sleep EEG for term-born infants: A randomized controlled parallel-group study.

AIM: To examine the impact of parent-led massage on the sleep electroencephalogram (EEG) features of typically developing term-born infants at 4 months. METHOD: Infants recruited at birth were randomized to intervention (routine parent-led massage) and control groups. Infants had a daytime sleep EEG at 4 months and were assessed using the Griffiths Scales of Child Development, Third Edition at 4 and 18 months. Comparative analysis between groups and subgroup analysis between regularly massaged and never-massaged infants were performed. Groups were compared for sleep stage, sleep spindles, quantitative EEG (primary analysis), and Griffiths using the Mann-Whitney U test. RESULTS: In total, 179 out of 182 infants (intervention: 83 out of 84; control: 96 out of 98) had a normal sleep EEG. Median (interquartile range) sleep duration was 49.8 minutes (39.1-71.4) (n = 156). A complete first sleep cycle was seen in 67 out of 83 (81%) and 72 out of 96 (75%) in the intervention and control groups respectively. Groups did not differ in sleep stage durations, latencies to sleep and to rapid eye movement sleep. Sleep spindle spectral power was greater in the intervention group in main and subgroup analyses. The intervention group showed greater EEG magnitudes, and lower interhemispherical coherence on subgroup analyses. Griffiths assessments at 4 months (n = 179) and 18 months (n = 173) showed no group differences in the main and subgroup analyses. INTERPRETATION: Routine massage is associated with distinct functional brain changes at 4 months. WHAT THIS PAPER ADDS: Routine massage of infants is associated with differences in sleep electroencephalogram biomarkers at 4 months. Massaged infants had higher sleep spindle spectral power, greater sleep EEG magnitudes, and lower interhemispherical coherence. No differences between groups were observed in total nap duration or first cycle macrostructure.

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.

Cerebral oxygen saturation and autoregulation during hypotension in extremely preterm infants.

BACKGROUND: The impact of the permissive hypotension approach in clinically well infants on regional cerebral oxygen saturation (rScO2) and autoregulatory capacity (CAR) remains unknown. METHODS: Prospective cohort study of blinded rScO2 measurements within a randomized controlled trial of management of hypotension (HIP trial) in extremely preterm infants. rScO2, mean arterial blood pressure, duration of cerebral hypoxia, and transfer function (TF) gain inversely proportional to CAR, were compared between hypotensive infants randomized to receive dopamine or placebo and between hypotensive and non-hypotensive infants, and related to early intraventricular hemorrhage or death. RESULTS: In 89 potentially eligible HIP trial patients with rScO2 measurements, the duration of cerebral hypoxia was significantly higher in 36 hypotensive compared to 53 non-hypotensive infants. In 29/36 hypotensive infants (mean GA 25 weeks, 69% males) receiving the study drug, no significant difference in rScO2 was observed after dopamine (n = 13) compared to placebo (n = 16). Duration of cerebral hypoxia was associated with early intraventricular hemorrhage or death.  Calculated TF gain (n = 49/89) was significantly higher reflecting decreased CAR in 16 hypotensive compared to 33 non-hypotensive infants. CONCLUSIONS: Dopamine had no effect on rScO2 compared to placebo in hypotensive infants. Hypotension and cerebral hypoxia are associated with early intraventricular hemorrhage or death. IMPACT: Treatment of hypotension with dopamine in extremely preterm infants increases mean arterial blood pressure, but does not improve cerebral oxygenation. Hypotensive extremely preterm infants have increased duration of cerebral hypoxia and reduced cerebral autoregulatory capacity compared to non-hypotensive infants. Duration of cerebral hypoxia and hypotension are associated with early intraventricular hemorrhage or death in extremely preterm infants. Since systematic treatment of hypotension may not be associated with better outcomes, the diagnosis of cerebral hypoxia in hypotensive extremely preterm infants might guide treatment.

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.

Electrographic Seizures during the Early Postnatal Period in Preterm Infants.

OBJECTIVE: To investigate the frequency and characteristics of electrographic seizures in preterm infants in the early postnatal period. STUDY DESIGN: Infants <32 weeks gestational age (GA) (n = 120) were enrolled for continuous multichannel electroencephalography (EEG) recording initiated as soon as possible after birth and continued for approximately up to 72 hours of age. Electrographic seizures were identified visually, annotated, and analyzed. Quantitative descriptors of the temporal evolution of seizures, including total seizure burden, seizure duration, and maximum seizure burden, were calculated. RESULTS: Median GA was 28.9 weeks (IQR, 26.6-30.3 weeks) and median birth weight was 1125 g (IQR, 848-1440 g). Six infants (5%; 95% CI, 1.9-10.6%) had electrographic seizures. Median total seizure burden, seizure duration, and maximum seizure burden were 40.3 minutes (IQR, 5.0-117.5 minutes), 49.6 seconds (IQR, 43.4-76.6 seconds), and 10.8 minutes/hour (IQR, 1.6-20.2 minutes/hour), respectively. Seizure burden was highest in 2 infants with significant abnormalities on neuroimaging. CONCLUSION: Electrographic seizures are infrequent within the first few days of birth in very preterm infants. Seizures in this population are difficult to detect accurately without continuous multichannel EEG monitoring.

A Randomized Controlled Trial of End-Tidal Carbon Dioxide Detection of Preterm Infants in the Delivery Room.

OBJECTIVE: To compare the ability of qualitative versus quantitative methods of end-tidal carbon dioxide (EtCO2) detection to maintain normocarbia during face mask ventilation (FMV) of preterm infants (<32 weeks) in the delivery room. STUDY DESIGN: Preterm infants <32 weeks were randomly assigned to the use of a disposable PediCap EtCO2 detector (Covidien, Dublin, Ireland) (qualitative) or a Microstream side stream capnography device (Covidien) (quantitative) for FMV in the delivery room, via a NeoPuff T-piece resuscitator (Fisher and Paykel, Auckland, New Zealand). The primary outcome was the presence of normocarbia, based on partial pressure of CO2 (PaCO2) readings obtained in the neonatal intensive care unit within an hour of birth. Normocarbia was defined as a PaCO2 measure between 37.5 and 60 mm Hg (5-8 kPa). RESULTS: Of the 59 infants included, 59% (35/59) were within the PaCO2 target range within an hour of birth. There was no difference in the primary outcome; 64% (21/33) of infants in the quantitative group were within the PaCO2 range compared with 54% (14/26) in the qualitative group (P = .594); and 93% of participants <28 weeks' gestation were within the PaCO2 normocarbic range (90% [9/10] in quantitative group and 100% [5/5] in the qualitative group [P = 1]). There was no difference in the intubation rate, days of ventilation, or bronchopulmonary dysplasia rates between the 2 groups. CONCLUSIONS: Quantitative or qualitative EtCO2 detection methods are both feasible for FMV in the delivery room. Although there was no difference in the incidence of normocarbia, the use of either form of EtCO2 monitoring should be considered during newborn stabilization, especially in infants less than 28 weeks' gestation. TRIAL REGISTRATION: ISRCTN: ISRCTN10934870.

Decreased Variability and Low Values of Perfusion Index on Day One Are Associated with Adverse Outcome in Extremely Preterm Infants.

OBJECTIVE: To develop new quantitative features for the Perfusion Index signal recorded continuously over the first 24 hours of life in a cohort of extremely low gestational age newborns and to assess the association of these features with normal and adverse short-term outcome. STUDY DESIGN: A cohort study of extremely low gestational age newborns. Adverse outcome was defined as early mortality before 72 hours of life, acquired severe periventricular-intraventricular hemorrhage, or severe cystic leukomalacia. Perfusion Index values were obtained from the plethysmographic signal of a pulse oximeter. Perfusion Index signals were separated into low-frequency (trend) and high-frequency (detrend) components. Three features were extracted during four 6-hour epochs: mean of the trend component (mean-trend), SD of the trend component (SD-trend), and SD of the detrend component (SD-detrend). The SD features represent long-term variability (SD-trend) and short-term variability (SD-detrend) of the Perfusion Index. A mixed-effects model was fitted to each feature. RESULTS: Ninety-nine infants were included in the analysis. Quadratic-time mixed-effects models provided the best fit for all 3 features. The mean-trend component was lower for the adverse outcome compared with the normal outcome group with a difference of 0.142 Perfusion Index (P = .001). SD-detrend component was also lower for the adverse compared with the normal outcome group, although this difference of 0.031 Perfusion Index/days2 was dependent on time (P < .001). CONCLUSION: Low values and reduced short-term variability of Perfusion Index on day 1 are associated with adverse outcome.

Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring.

BACKGROUND: Preterm infants are at risk of adverse outcome. The aim of this study is to develop a multimodal model, including physiological signals from the first days of life, to predict 2-y outcome in preterm infants. METHODS: Infants <32 wk gestation had simultaneous multi-channel electroencephalography (EEG), peripheral oxygen saturation (SpO2), and heart rate (HR) monitoring. EEG grades were combined with gestational age (GA) and quantitative features of HR and SpO2 in a logistic regression model to predict outcome. Bayley Scales of Infant Development-III assessed 2-y neurodevelopmental outcome. A clinical course score, grading infants at discharge as high or low morbidity risk, was used to compare performance with the model. RESULTS: Forty-three infants were included: 27 had good outcomes, 16 had poor outcomes or died. While performance of the model was similar to the clinical course score graded at discharge, with an area under the receiver operator characteristic (AUC) of 0.83 (95% confidence intervals (CI): 0.69-0.95) vs. 0.79 (0.66-0.90) (P = 0.633), the model was able to predict 2-y outcome days after birth. CONCLUSION: Quantitative analysis of physiological signals, combined with GA and graded EEG, shows potential for predicting mortality or delayed neurodevelopment at 2 y of age.

Effects of Fractional Inspired Oxygen on Cerebral Oxygenation in Preterm Infants following Delivery.

OBJECTIVES: To explore regional cerebral oxygen saturations (rcSO2) in preterm neonates initially stabilized with 0.3 fractionated inspired oxygen (FiO2) concentrations. We hypothesized that those infants who received >0.3 FiO2 during stabilization following delivery would have relatively higher rcSO2 postdelivery compared with those stabilized with a lower FiO2. STUDY DESIGN: A single center prospective observational study of 47 infants born before 32 weeks. Using near infrared spectroscopy, rcSO2 values were recorded immediately after birth. All preterm infants were initially given 0.3 FiO2 and were divided into 2 groups according to subsequent FiO2 requirements of either ≤0.3 or >0.3 FiO2. Using a mixed-effects model, we compared the difference between the groups over time. Also, the area measures below 55% (hypoxia) and above 85% (hyperoxia) were compared between the groups. RESULTS: The mean (SD) gestation was 29.4 (1.6) weeks and the mean (SD) weight was 1.3 (0.4) kg. Less than one-half of the infants (20/45; 43%) required ≤0.3 FiO2. In the delivery suite, the median (IQR) rcSO2 in the low and high FiO2 groups were 81% (66%-86%) and 72% (62%-86%), respectively. Patients in the high FiO2 group had a larger rcSO2 area below 55% (P = .01). There was a significant difference in rcSO2 between the groups (P < .05), with the low group having higher rcSO2 values initially, but this difference changed over time. In the neonatal intensive care unit (NICU), rcSO2 values were lower by 7.1% (CI 12.13 to 2.06%) P = .008 in the high FiO2 group. CONCLUSIONS: Infants given >0.3 FiO2 had more cerebral hypoxia than infants requiring ≤0.3 FiO2 but no difference in the degree of cerebral hyperoxia, both in the delivery suite and the NICU. This suggests that a more rapid increase in oxygen titration maybe be required initially for preterm infants.

Advances in Electroencephalographic Biomarkers of Neonatal Hypoxic Ischemic Encephalopathy.

Electroencephalography (EEG) is a key objective biomarker of newborn brain function, delivering critical, cotside insights to aid the management of encephalopathy. Access to continuous EEG is limited, forcing reliance on subjective clinical assessments. In hypoxia ischaemia, the primary cause of encephalopathy, alterations in EEG patterns correlate with. injury severity and evolution. As HIE evolves, causing secondary neuronal death, EEG can track injury progression, informing neuroprotective strategies, seizure management and prognosis. Despite its value, challenges with interpretation and lack of on site expertise has limited its broader adoption. Technological advances, particularly in digital EEG and machine learning, are enhancing real-time analysis. This will allow EEG to expand its role in HIE diagnosis, management and outcome prediction.

Quantitative analysis of high-frequency activity in neonatal EEG.

OBJECTIVE: To determine the presence and potential utility of independent high-frequency activity recorded from scalp electrodes in the electroencephalogram (EEG) of newborns. METHODS: We compare interburst intervals and continuous activity at different frequencies for EEGs retrospectively recorded at 256 Hz from 4 newborn groups: 1) 36 preterms (<32 weeks' gestational age, GA); 2) 12 preterms (32-37 weeks' GA); 3) 91 healthy full terms; 4) 15 full terms with hypoxic-ischemic encephalopathy (HIE). At 4 standard frequency bands (delta, 0.5-3 Hz; theta, 3-8 Hz; alpha, 8-15 Hz; beta, 15-30 Hz) and 3 higher-frequency bands (gamma1, 30-48 Hz; gamma2, 52-99 Hz; gamma3, 107-127 Hz), we compared power spectral densities (PSDs), quantitative features, and machine learning model performance. Feature selection and further machine learning methods were performed on one cohort. RESULTS: We found significant (P < 0.01) differences in PSDs, quantitative analysis, and machine learning modelling at the higher-frequency bands. Machine learning models using only high-frequency features performed best in preterm groups 1 and 2 with a median (95% confidence interval, CI) Matthews correlation coefficient (MCC) of 0.71 (0.12-0.88) and 0.66 (0.36-0.76) respectively. Interburst interval-detector models using both high- and standard-bandwidths produced the highest median MCCs in all four groups. High-frequency features were largely independent of standard-bandwidth features, with only 11/84 (13.1%) of correlations statistically significant. Feature selection methods produced 7 to 9 high-frequency features in the top 20 feature set. CONCLUSIONS: This is the first study to identify independent high-frequency activity in newborn EEG using in-depth quantitative analysis. Expanding the EEG bandwidths of analysis has the potential to improve both quantitative and machine-learning analysis, particularly in preterm EEG.

Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy.

This report describes a set of neonatal electroencephalogram (EEG) recordings graded according to the severity of abnormalities in the background pattern. The dataset consists of 169 hours of multichannel EEG from 53 neonates recorded in a neonatal intensive care unit. All neonates received a diagnosis of hypoxic-ischaemic encephalopathy (HIE), the most common cause of brain injury in full term infants. For each neonate, multiple 1-hour epochs of good quality EEG were selected and then graded for background abnormalities. The grading system assesses EEG attributes such as amplitude, continuity, sleep-wake cycling, symmetry and synchrony, and abnormal waveforms. Background severity was then categorised into 4 grades: normal or mildly abnormal EEG, moderately abnormal EEG, majorly abnormal EEG, and inactive EEG. The data can be used as a reference set of multi-channel EEG for neonates with HIE, for EEG training purposes, or for developing and evaluating automated grading algorithms.

Machine Learning Detects Intraventricular Haemorrhage in Extremely Preterm Infants.

OBJECTIVE: To test the potential utility of applying machine learning methods to regional cerebral (rcSO2) and peripheral oxygen saturation (SpO2) signals to detect brain injury in extremely preterm infants. STUDY DESIGN: A subset of infants enrolled in the Management of Hypotension in Preterm infants (HIP) trial were analysed (n = 46). All eligible infants were <28 weeks' gestational age and had continuous rcSO2 measurements performed over the first 72 h and cranial ultrasounds performed during the first week after birth. SpO2 data were available for 32 infants. The rcSO2 and SpO2 signals were preprocessed, and prolonged relative desaturations (PRDs; data-driven desaturation in the 2-to-15-min range) were extracted. Numerous quantitative features were extracted from the biosignals before and after the exclusion of the PRDs within the signals. PRDs were also evaluated as a stand-alone feature. A machine learning model was used to detect brain injury (intraventricular haemorrhage-IVH grade II-IV) using a leave-one-out cross-validation approach. RESULTS: The area under the receiver operating characteristic curve (AUC) for the PRD rcSO2 was 0.846 (95% CI: 0.720-0.948), outperforming the rcSO2 threshold approach (AUC 0.593 95% CI 0.399-0.775). Neither the clinical model nor any of the SpO2 models were significantly associated with brain injury. CONCLUSION: There was a significant association between the data-driven definition of PRDs in rcSO2 and brain injury. Automated analysis of PRDs of the cerebral NIRS signal in extremely preterm infants may aid in better prediction of IVH compared with a threshold-based approach. Further investigation of the definition of the extracted PRDs and an understanding of the physiology underlying these events are required.

Electroencephalographic sleep macrostructure and sleep spindles in early infancy.

STUDY OBJECTIVES: Sleep features in infancy are potential biomarkers for brain maturation but poorly characterized. We describe normative values for sleep macrostructure and sleep spindles at 4-5 months of age. METHODS: Healthy term infants were recruited at birth and had daytime sleep electroencephalograms (EEGs) at 4-5 months. Sleep staging was performed and five features were analyzed. Sleep spindles were annotated and seven quantitative features were extracted. Features were analyzed across sex, recording time (am/pm), infant age, and from first to second sleep cycles. RESULTS: We analyzed sleep recordings from 91 infants, 41% females. Median (interquartile range [IQR]) macrostructure results: sleep duration 49.0 (37.8-72.0) min (n = 77); first sleep cycle duration 42.8 (37.0-51.4) min; rapid eye movement (REM) percentage 17.4 (9.5-27.7)% (n = 68); latency to REM 36.0 (30.5-41.1) min (n = 66). First cycle median (IQR) values for spindle features: number 241.0 (193.0-286.5), density 6.6 (5.7-8.0) spindles/min (n = 77); mean frequency 13.0 (12.8-13.3) Hz, mean duration 2.9 (2.6-3.6) s, spectral power 7.8 (4.7-11.4) µV2, brain symmetry index 0.20 (0.16-0.29), synchrony 59.5 (53.2-63.8)% (n = 91). In males, spindle spectral power (µV2) was 24.5% lower (p = .032) and brain symmetry index 24.2% higher than females (p = .011) when controlling for gestational and postnatal age and timing of the nap. We found no other significant associations between studied sleep features and sex, recording time (am/pm), or age. Spectral power decreased (p < .001) on the second cycle. CONCLUSION: This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy. Clinical Trial Registration: BABY SMART (Study of Massage Therapy, Sleep And neurodevelopMenT) (BabySMART)URL: https://clinicaltrials.gov/ct2/show/results/NCT03381027?view=results.ClinicalTrials.gov Identifier: NCT03381027.

Agreement of Cardiac Output Estimates between Electrical Cardiometry and Transthoracic Echocardiography in Very Preterm Infants.

INTRODUCTION: The aim was to evaluate the agreement between cardiac output estimates obtained by electrical cardiometry (EC) and transthoracic echocardiography (TTE) in very preterm infants. METHODS: This is a single-center prospective observational study in infants born<32 weeks gestational age within 48 h of birth. Continuous EC was recorded and simultaneous TTE obtained on day 1 and day 2 of life. Blinded TTE measurements were performed within a 10 s timeframe using beat-to-beat EC data. The primary outcome was %error of left ventricular (LV) output in milliliters per kilogram per minute (cardiac index (CI)) obtained by TTE compared to LV-CI from EC. Secondary outcome parameters were bias, %bias, limits of agreement and include measures of right ventricular (RV) output and LV systolic time intervals. RESULTS: Analysis was performed for 34 infants (median (IQR) gestational age 29 + 0 (24 + 5 to 30 + 6) weeks + days, birthweight 960 (748 to 1,490) grams) including 44 pairwise LV output measurements on 24 participants (22 on day 1 and day 2). The %error was 54% for LV-CI (EC: 214 (38) mL/kg/min vs. TTE: 163 (47) mL/kg/min). The %error was 78% for RV-CI (EC: 213 (37) mL/kg/min vs. TTE: 241 (77) mL/kg/min). While only LV-CI values affected LV-CI bias, signal quality, heart rate, and RV-CI values affected RV-CI bias. CONCLUSION: EC is not interchangeable with TTE to estimate indices of LV or RV output in very preterm infants within the first 48 h postnatally. EC may not measure LV output distinctly in very preterm infants with intra- and extracardiac shunts.

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.

In-Silico Evaluation of Anthropomorphic Measurement Variations on Electrical Cardiometry in Neonates.

Non-invasive cardiac output methods such as Electrical Cardiometry (EC) are relatively novel assessment tools for neonates and they enable continuous monitoring of stroke volume (SV). An in-silico comparison of differences in EC-derived SV in relation to preset length and weight was performed. EC (ICON, Osypka Medical) was simulated using the "demo" mode for various combinations of length and weight representative of term and preterm infants. One-centimetre length error resulted in a SV-change of 1.8-3.6% (preterm) or 1.6-2.0% (term) throughout the tested weight ranges. One-hundred gram error in weight measurement resulted in a SV-change of 5.0-7.1% (preterm) or 1.5-1.8% (term) throughout the tested length ranges. Algorithms to calculate EC-derived SV incorporate anthropomorphic measurements. Therefore, inaccuracy in physical measurement can impact absolute EC measurements. This should be considered in the interpretation of previous findings and the design of future clinical studies of EC-derived cardiac parameters in neonates, particularly in the preterm cohorts where a proportional change was noted to be greatest.