Hendrik J. Niemarkt

Maturational Changes in Automated EEG Spectral Power Analysis in Preterm Infants

Our study aimed at automated power spectral analysis of the EEG in preterm infants to identify changes of spectral measures with maturation. Weekly (10–20 montage) 4-h EEG recordings were performed in 18 preterm infants with GA <32 wk and normal neurological follow-up at 2 y, resulting in 79 recordings studied from 27+4 to 36+3 wk of postmenstrual age (PMA, GA + postnatal age). Automated spectral analysis was performed on 4-h EEG recordings. The frequency spectrum was divided in delta 1 (0.5–1 Hz), delta 2 (1–4 Hz), theta (4–8 Hz), alpha (8–13 Hz), and beta (13–30 Hz) band. Absolute and relative power of each frequency band and spectral edge frequency were calculated. Maturational changes in spectral measures were observed most clearly in the centrotemporal channels. With advancing PMA, absolute powers of delta 1 to 2 and theta decreased. With advancing PMA, relative power of delta 1 decreased and relative powers of alpha and beta increased, respectively. In conclusion, with maturation, spectral analysis of the EEG showed a significant shift from the lower to the higher frequencies. Computer analysis of EEG will allow an objective and reproducible analysis for long-term prognosis and/or stratification of clinical treatment.

Quantitative Analysis of Amplitude-Integrated Electroencephalogram Patterns in Stable Preterm Infants, with Normal Neurological Development at One Year

Background: The amplitude-integrated EEG (aEEG) is feasible for monitoring cerebral activity in preterm infants. However, quantitative data on normal patterns in these infants are limited. Objective: To study maturational aEEG changes in a cohort of stable preterm infants by automated quantification. Methods: In a cohort of stable preterm infants with gestational age (GA) <32 weeks and normal neurological follow-up at 1 year, weekly 4 h EEG recordings were performed. aEEG traces were obtained from channel C3-C4. The upper margin amplitude (UMA), lower margin amplitude (LMA) and bandwidth (BW) were quantitatively calculated using an expert software system. In addition, the relative duration of discontinuous background pattern (discontinuous background defined as activity with LMA <5 µV, expressed as DC-%) was calculated. Results: 79 aEEG recordings (4–6 recordings/infant) were obtained in 18 infants. Analysis of the first week recordings demonstrated a strong positive correlation between GA and LMA, while DC-% decreased significantly. Longitudinally, all infants showed increase of LMA. Multivariate analysis showed that GA and postnatal age (PA) both contributed independently and equally to LMA and DC-%. We found a strong correlation between postmenstrual age (GA + PA) and LMA and DC-%, respectively. Conclusion: To our knowledge, this is the first study where aEEG development was studied by automated quantification of aEEG characteristics in a cohort of stable preterm infants with a normal neurological development at 1 year of age. LMA and DC-% are simple quantitative measures of neurophysiologic development and may be used to evaluate neurodevelopment in infants.

Quantitative analysis of maturational changes in EEG background activity in very preterm infants with a normal neurodevelopment at 1 year of age

BACKGROUND The electroencephalographic (EEG) background pattern of preterm infants changes with postmenstrual age (PMA) from discontinuous activity to continuous activity. However, changes in discontinuity have been investigated by visual analysis only. AIM To investigate the maturational changes in EEG discontinuity in healthy preterm infants using an automated EEG detection algorithm. STUDY DESIGN Weekly 4h EEG recordings were performed in preterm infants with a gestational age (GA)<32weeks and normal neurological follow-up at 1year. The channel C3-C4 was analyzed using an algorithm which automatically detects periods of EEG inactivity (interburst intervals). The interburst-burst ratio (IBR, percentage of EEG inactivity during a moving time window of 600s) and mean length of the interburst intervals were calculated. Using the IBR, discontinuous background activity (periods with high IBR) and continuous background activity (periods with low IBR) were automatically detected and their mean length during each recording was calculated. Data were analyzed with regression and multivariate analysis. RESULTS 79 recordings were performed in 18 infants. All recordings showed a cyclical pattern in EEG discontinuity. With advancing PMA, IBR (R(2)=0.64; p<0.001), interburst interval length (R(2)=0.43; p<0.001) and length of discontinuous activity (R(2)=0.38; p<0.001) decreased, while continuous activity increased (R(2)=0.50; p<0.001). Multivariate analysis showed that all EEG discontinuity parameters were equally influenced by GA and postnatal age. CONCLUSION Analyzing EEG background activity in preterm infants is feasible with an automated algorithm and shows maturational changes of several EEG derived parameters. The cyclical pattern in IBR suggests brain organisation in preterm infant.

Automatic burst detection for the EEG of the preterm infant

To aid with prognosis and stratification of clinical treatment for preterm infants, a method for automated detection of bursts, interburst-intervals (IBIs) and continuous patterns in the electroencephalogram (EEG) is developed. Results are evaluated for preterm infants with normal neurological follow-up at 2 years. The detection algorithm (MATLAB®) for burst, IBI and continuous pattern is based on selection by amplitude, time span, number of channels and numbers of active electrodes. Annotations of two neurophysiologists were used to determine threshold values. The training set consisted of EEG recordings of four preterm infants with postmenstrual age (PMA, gestational age + postnatal age) of 29-34 weeks. Optimal threshold values were based on overall highest sensitivity. For evaluation, both observers verified detections in an independent dataset of four EEG recordings with comparable PMA. Algorithm performance was assessed by calculation of sensitivity and positive predictive value. The results of algorithm evaluation are as follows: sensitivity values of 90% ± 6%, 80% ± 9% and 97% ± 5% for burst, IBI and continuous patterns, respectively. Corresponding positive predictive values were 88% ± 8%, 96% ± 3% and 85% ± 15%, respectively. In conclusion, the algorithm showed high sensitivity and positive predictive values for bursts, IBIs and continuous patterns in preterm EEG. Computer-assisted analysis of EEG may allow objective and reproducible analysis for clinical treatment.

Furosemide in preterm infants treated with indomethacin for patent ductus arteriosus

Objective: To evaluate the effect of furosemide on renal function and water balance in preterm infants treated with indomethacin (3 × 0.2 mg/kg at 12‐h intervals) for symptomatic patent ductus arteriosus.

Necrotizing enterocolitis: a clinical review on diagnostic biomarkers and the role of the intestinal microbiota

AbstractNecrotizing enterocolitis (NEC) remains one of the most frequent gastrointestinal diseases in the neonatal intensive care unit, with a continuing unacceptable high mortality and morbidity rates. Up to 20% to 40% of infants with NEC will need surgical intervention at some point. Although the exact pathophysiology is not yet elucidated, prematurity, use of formula feeding, and an altered intestinal microbiota are supposed to induce an inflammatory response of the immature intestine. The clinical picture of NEC has been well described. However, an early diagnosis and differentiation against sepsis is challenging. Besides, it is difficult to timely identify NEC cases that will deteriorate and need surgical intervention. This may interfere with the most optimal treatment of infants with NEC. In this review, we discuss the pathogenesis, diagnosis, and treatment of NEC with a focus on the role of microbiota in the development of NEC. An overview of different clinical prediction models and biomarkers is given. Some of these are promising tools for accurate diagnosis of NEC and selection of appropriate therapy.

Effects of less-invasive surfactant administration on oxygenation, pulmonary surfactant distribution, and lung compliance in spontaneously breathing preterm lambs.

Background:A new technique was proposed to administer surfactant to spontaneous breathing preterm infants by placing a thin catheter through the vocal cords. This technique was not studied with respect to oxygenation, gas exchange, surfactant distribution, and lung mechanics. We tested the technique of less-invasive surfactant administration (LISA) in a spontaneous breathing preterm lamb model.Methods:Preterm lambs (n = 12) of 133–134 d gestational age were randomized to the following three groups: (i) continuous positive airway pressure (CPAP) only, (ii) CPAP + LISA, and (iii) intubation and mechanical ventilation with surfactant administration. Surfactant was labeled with samarium oxide. During the next 180 min, blood gas analyses were performed. Postmortem, lungs were removed and surfactant distribution was assessed, and pressure–volume curves were performed.Results:Pao2 in the LISA-treated lambs was significantly higher than in the lambs that exclusively received CPAP. Moreover, Pao2 values were similar between the LISA-treated and the intubated lambs. Overall, surfactant deposition was less in the LISA lambs, with significantly less surfactant distributed to the right upper lobe. Lung compliance was better in the intubated lambs compared with the LISA-treated lambs, although this did not reach significance.Conclusion:LISA improved oxygenation, similar to conventional surfactant application techniques, despite lower surfactant deposition and lung compliance.

Amplitude-integrated electroencephalographic changes in a newborn induced by overdose of morphine and corrected with naloxone

The amplitude‐integrated electroencephalogram (aEEG) is a useful tool to assess brain function after perinatal asphyxia in term infants.

Multi-channel amplitude-integrated EEG characteristics in preterm infants with a normal neurodevelopment at two years of corrected age

AIM To analyze quantitatively multi-channel amplitude-integrated EEG (aEEG) characteristics and assess regional differences. METHODS We investigated 40 preterm infants (postmenstrual age, PMA: range 27-37 weeks) with normal follow-up at 24 months of age, at a median postnatal age of 8 days using 4-h EEG recordings according to the international 10-20 system reduced montage. Nine (3 transverse and 6 longitudinal) channels were selected and converted to aEEG registrations. For each aEEG registration, lower margin amplitude (LMA), upper margin amplitude (UMA) and bandwidth (UMA-LMA) were calculated. RESULTS In all channels PMA and LMA showed strong positive correlations. Below 32 weeks of PMA, LMA was ≤5μV. Linear regression analysis showed a maximum LMA difference between channels of approximately 2 and 1μV at 27 and 37 weeks of PMA, respectively. The lowest are LMA values in the occipital channel and the highest values are in centro-occipital channels. In the frontal, centro-temporal and centro-occipital channels, UMA and bandwidth changed with PMA. No differences in LMA, UMA and bandwidth were found between hemispheres. Skewness of LMA values strongly correlated with PMA, positive skewness indicating an immature brain (PMA≤32 weeks) and negative skewness a maturing (PMA>32 weeks) brain. CONCLUSIONS We detected symmetric increase of aEEG characteristics, indicating symmetric brain maturation of the left and right hemispheres. Our findings demonstrate the clinical potential of computer-assisted analyses of aEEG recordings in detecting maturational features which are not readily identified visually. This may provide an objective and reproducible method for assessing brain maturation and long-term prognosis.

Topography of maturational changes in EEG burst spectral power of the preterm infant with a normal follow-up at 2 years of age

OBJECTIVE To quantify the electroencephalography (EEG) burst frequency spectrum of preterm infants by automated analysis and to describe the topography of maturational change in spectral parameters. METHODS Eighteen preterm infants <32weeks gestation and normal neurological follow-up at 2years underwent weekly 4-h EEG recordings (10-20 system). The recordings (n=77) represent a large variability in postmenstrual age (PMA, 28-36weeks). We applied an automated burst detection algorithm and performed spectral analysis. The frequency spectrum was divided into δ1 (0.5-1Hz), δ2 (1-4Hz), θ (4-8Hz), α (8-13Hz) and β (13-30Hz) bands. Spectral parameters were evaluated as a function of PMA by regression analysis. Results were interpolated and topographically visualised. RESULTS The majority of spectral parameters show significant change with PMA. Highest correlation is found for δ and θ band. Absolute band powers decrease with increasing PMA, while relative α and β powers increase. Maturational change is largest in frontal and temporal region. CONCLUSIONS Topographic distribution of maturational changes in spectral parameters corresponds with studies showing ongoing gyration and postnatal white matter maturation in frontal and temporal lobes. SIGNIFICANCE Computer analysis of EEG may allow objective and reproducible analysis for long-term prognosis and/or stratification of clinical treatment.