Noncontact respiration monitoring techniques in young children: A scoping review

Pediatric sleep-related breathing disorders, or sleep-disordered breathing (SDB), cover a range of conditions, including obstructive sleep apnea, central sleep apnea, sleep-related hypoventilation disorders, and sleep-related hypoxemia disorder. Pediatric SDB is often underdiagnosed, potentially due to difficulties associated with performing the gold standard polysomnography in children. This scoping review aims to: (1) provide an overview of the studies reporting on safe, noncontact monitoring of respiration in young children, (2) describe the accuracy of these techniques, and (3) highlight their respective advantages and limitations. PubMed and EMBASE were searched for studies researching techniques in children <12 years old. Both quantitative data and the quality of the studies were analyzed. The evaluation of study quality was conducted using the QUADAS-2 tool. A total of 19 studies were included. Techniques could be grouped into bed-based methods, microwave radar, video, infrared (IR) cameras, and garment-embedded sensors. Most studies either measured respiratory rate (RR) or detected apneas; n = 2 aimed to do both. At present, bed-based approaches are at the forefront of research in noncontact RR monitoring in children, boasting the most sophisticated algorithms in this field. Yet, despite extensive studies, there remains no consensus on a definitive method that outperforms the rest. The accuracies reported by these studies tend to cluster within a similar range, indicating that no single technique has emerged as markedly superior. Notably, all identified methods demonstrate capability in detecting body movements and RR, with reported safety for use in children across the board. Further research into contactless alternatives should focus on cost-effectiveness, ease-of-use, and widespread availability.

Characterising the motion and cardiorespiratory interaction of preterm infants can improve the classification of their sleep state

AIM

This study aimed to classify quiet sleep, active sleep and wake states in preterm infants by analysing cardiorespiratory signals obtained from routine patient monitors.

METHODS

We studied eight preterm infants, with an average postmenstrual age of 32.3 ± 2.4 weeks, in a neonatal intensive care unit in the Netherlands. Electrocardiography and chest impedance respiratory signals were recorded. After filtering and R-peak detection, cardiorespiratory features and motion and cardiorespiratory interaction features were extracted, based on previous research. An extremely randomised trees algorithm was used for classification and performance was evaluated using leave-one-patient-out cross-validation and Cohen's kappa coefficient.

RESULTS

A sleep expert annotated 4731 30-second epochs (39.4 h) and active sleep, quiet sleep and wake accounted for 73.3%, 12.6% and 14.1% respectively. Using all features, and the extremely randomised trees algorithm, the binary discrimination between active and quiet sleep was better than between other states. Incorporating motion and cardiorespiratory interaction features improved the classification of all sleep states (kappa 0.38 ± 0.09) than analyses without these features (kappa 0.31 ± 0.11).

CONCLUSION

Cardiorespiratory interactions contributed to detecting quiet sleep and motion features contributed to detecting wake states. This combination improved the automated classifications of sleep states.

Automatic Max-Likelihood Envelope Detection Algorithm for Quantitative High-Frame-Rate Ultrasound for Neonatal Brain Monitoring

OBJECTIVE

Post-operative brain injury in neonates may result from disturbed cerebral perfusion, but accurate peri-operative monitoring is lacking. High-frame-rate (HFR) cerebral ultrasound could visualize and quantify flow in all detectable vessels using spectral Doppler; however, automated quantification in small vessels is challenging because of low signal amplitude. We have developed an automatic envelope detection algorithm for HFR pulsed wave spectral Doppler signals, enabling neonatal brain quantitative parameter maps during and after surgery.

METHODS

HFR ultrasound data from high-risk neonatal surgeries were recorded with a custom HFR mode (frame rate = 1000 Hz) on a Zonare ZS3 system. A pulsed wave Doppler spectrogram was calculated for each pixel containing blood flow in the image, and spectral peak velocity was tracked using a max-likelihood estimation algorithm of signal and noise regions in the spectrogram, where the most likely cross-over point marks the blood flow velocity. The resulting peak systolic velocity (PSV), end-diastolic velocity (EDV) and resistivity index (RI) were compared with other detection schemes, manual tracking and RIs from regular pulsed wave Doppler measurements in 10 neonates.

RESULTS

Envelope detection was successful in both high- and low-quality arterial and venous flow spectrograms. Our technique had the lowest root mean square error for EDV, PSV and RI (0.46 cm/s, 0.53 cm/s and 0.15, respectively) when compared with manual tracking. There was good agreement between the clinical pulsed wave Doppler RI and HFR measurement with a mean difference of 0.07.

CONCLUSION

The max-likelihood algorithm is a promising approach to accurate, automated cerebral blood flow monitoring with HFR imaging in neonates.

A comparison of ultrafast and conventional spectral Doppler ultrasound to measure cerebral blood flow velocity during inguinal hernia repair in infants

BACKGROUND

Ultrafast cerebral Doppler ultrasound enables simultaneous quantification and visualization of cerebral blood flow velocity. The aim of this study is to compare the use of conventional and ultrafast spectral Doppler during anesthesia and their potential to show the effect of anesthesiologic procedures on cerebral blood flow velocities, in relation to blood pressure and cerebral oxygenation in infants undergoing inguinal hernia repair.

METHODS

A single-center prospective observational cohort study in infants up to six months of age. We evaluated conventional and ultrafast spectral Doppler cerebral ultrasound measurements in terms of number of successful measurements during the induction of anesthesia, after sevoflurane induction, administration of caudal analgesia, a fluid bolus and emergence of anesthesia. Cerebral blood flow velocity was quantified in pial arteries using conventional spectral Doppler and in the cerebral cortex using ultrafast Doppler by peak systolic velocity, end diastolic velocity and resistivity index.

RESULTS

Twenty infants were included with useable conventional spectral Doppler images in 72/100 measurements and ultrafast Doppler images in 51/100 measurements. Intraoperatively, the success rates were 53/60 (88.3%) and 41/60 (68.3%), respectively. Cerebral blood flow velocity increased after emergence for both conventional (end diastolic velocity, from 2.01 to 2.75 cm/s, p < 0.001) and ultrafast spectral Doppler (end diastolic velocity, from 0.59 to 0.94 cm/s), whereas cerebral oxygenation showed a reverse pattern with a decrease after the emergence of the infant (85% to 68%, p < 0.001).

CONCLUSION

It is possible to quantify cortical blood flow velocity during general anesthesia using conventional and ultrafast spectral Doppler cerebral ultrasound. Cerebral blood flow velocity and blood pressure decreased, while regional cerebral oxygenation increased during general anesthesia. Ultrafast spectral Doppler ultrasound offers novel insights into perfusion within the cerebral cortex, unattainable through conventional spectral ultrasound. Yet, ultrafast Doppler is curtailed by a lower success rate and a more rigorous learning curve compared to conventional method.

Effect of Systemic Hydrocortisone on Brain Abnormalities and Regional Brain Volumes in Ventilator-dependent Infants Born Preterm: Substudy of the SToP-BPD Study

OBJECTIVE

To evaluate whether a high cumulative dose of systemic hydrocortisone affects brain development compared with placebo when initiated between 7 and 14 days after birth in ventilated infants born preterm.

STUDY DESIGN

A double-blind, placebo-controlled, randomized trial was conducted in 16 neonatal intensive care units among infants born at <30 weeks of gestation or with a birth weight of <1250 g who were ventilator-dependent in the second week after birth. Three centers performed MRI at term-equivalent age. Brain injury was assessed on MRI using the Kidokoro scoring system and compared between the 2 treatment groups. Both total and regional brain volumes were calculated using an automatic segmentation method and compared using multivariable regression analysis adjusted for baseline variables.

RESULTS

From the 3 centers, 78 infants participated in the study and 59 had acceptable MRI scans (hydrocortisone group, n = 31; placebo group, n = 28). Analyses of the median global brain abnormality score of the Kidokoro score showed no difference between the hydrocortisone and placebo groups (median, 7; IQR, 5-9 vs median, 8, IQR, 4-10, respectively; P = .92). In 39 infants, brain tissue volumes were measured, showing no differences in the adjusted mean total brain tissue volumes, at 352 ± 32 mL in the hydrocortisone group and 364 ± 51 mL in the placebo group (P = .80).

CONCLUSIONS

Systemic hydrocortisone started in the second week after birth in ventilator-dependent infants born very preterm was not found to be associated with significant differences in brain development compared with placebo treatment.

TRIAL REGISTRATION

The SToP-BPD study was registered with the Netherlands Trial Register (NTR2768; registered on 17 February 2011; https://www.trialregister.nl/trial/2640) and the European Union Clinical Trials Register (EudraCT, 2010-023777-19; registered on 2 November 2010; https://www.clinicaltrialsregister.eu/ctr-search/trial/2010-023777-19/NL).

Machine Learning-Derived Active Sleep as an Early Predictor of White Matter Development in Preterm Infants

White matter dysmaturation is commonly seen in preterm infants admitted to the neonatal intensive care unit (NICU). Animal research has shown that active sleep is essential for early brain plasticity. This study aimed to determine the potential of active sleep as an early predictor for subsequent white matter development in preterm infants. Using heart and respiratory rates routinely monitored in the NICU, we developed a machine learning-based automated sleep stage classifier in a cohort of 25 preterm infants (12 females). The automated classifier was subsequently applied to a study cohort of 58 preterm infants (31 females) to extract active sleep percentage over 5-7 consecutive days during 29-32 weeks of postmenstrual age. Each of the 58 infants underwent high-quality T2-weighted magnetic resonance brain imaging at term-equivalent age, which was used to measure the total white matter volume. The association between active sleep percentage and white matter volume was examined using a multiple linear regression model adjusted for potential confounders. Using the automated classifier with a superior sleep classification performance [mean area under the receiver operating characteristic curve (AUROC) = 0.87, 95% CI 0.83-0.92], we found that a higher active sleep percentage during the preterm period was significantly associated with an increased white matter volume at term-equivalent age [β = 0.31, 95% CI 0.09-0.53, false discovery rate (FDR)-adjusted p-value = 0.021]. Our results extend the positive association between active sleep and early brain development found in animal research to human preterm infants and emphasize the potential benefit of sleep preservation in the NICU setting.

Evaluation of Sleep Practices and Knowledge in Neonatal Healthcare

BACKGROUND

Developmental care is designed to optimize early brain maturation by integrating procedures that support a healing environment. Protecting preterm sleep is important in developmental care. However, it is unclear to what extent healthcare professionals are aware of the importance of sleep and how sleep is currently implemented in the day-to-day care in the neonatal intensive care unit (NICU).

PURPOSE

Identifying the current state of knowledge among healthcare professionals regarding neonatal sleep and how this is transferred to practice.

METHODS

A survey was distributed among Dutch healthcare professionals. Three categories of data were sought, including (1) demographics of respondents; (2) questions relating to sleep practices; and (3) objective knowledge questions relating to sleep physiology and importance of sleep. Data were analyzed using Spearman's rho test and Cramer's V test. Furthermore, frequency tables and qualitative analyses were employed.

RESULTS

The survey was completed by 427 participants from 34 hospitals in 25 Dutch cities. While healthcare professionals reported sleep to be especially important for neonates admitted in the NICU, low scores were achieved in the area of knowledge of sleep physiology. Most healthcare professionals (91.8%) adapted the timing of elective care procedures to sleep. However, sleep assessments were not based on scientific knowledge. Therefore, the difference between active sleep and wakefulness may often be wrongly assessed. Finally, sleep is rarely discussed between colleagues (27.4% regularly/always) and during rounds (7.5%-14.3% often/always).

IMPLICATIONS

Knowledge about sleep physiology should be increased through education among neonatal healthcare professionals. Furthermore, sleep should be considered more often during rounds and handovers.

Early qualitative and quantitative amplitude-integrated electroencephalogram and raw electroencephalogram for predicting long-term neurodevelopmental outcomes in extremely preterm infants in the Netherlands: a 10-year cohort study

BACKGROUND

Extremely preterm infants (<28 weeks of gestation) are at great risk of long-term neurodevelopmental impairments. Early amplitude-integrated electroencephalogram (aEEG) accompanied by raw EEG traces (aEEG-EEG) has potential for predicting subsequent outcomes in preterm infants. We aimed to determine whether and which qualitative and quantitative aEEG-EEG features obtained within the first postnatal days predict neurodevelopmental outcomes in extremely preterm infants.

METHODS

This study retrospectively analysed a cohort of extremely preterm infants (born before 28 weeks and 0 days of gestation) who underwent continuous two-channel aEEG-EEG monitoring during their first 3 postnatal days at Wilhelmina Children's Hospital, Utrecht, the Netherlands, between June 1, 2008, and Sept 30, 2018. Only infants who did not have genetic or metabolic diseases or major congenital malformations were eligible for inclusion. Features were extracted from preprocessed aEEG-EEG signals, comprising qualitative parameters grouped in three types (background pattern, sleep-wake cycling, and seizure activity) and quantitative metrics grouped in four categories (spectral content, amplitude, connectivity, and discontinuity). Machine learning-based regression and classification models were used to evaluate the predictive value of the extracted aEEG-EEG features for 13 outcomes, including cognitive, motor, and behavioural problem outcomes, at 2-3 years and 5-7 years. Potential confounders (gestational age at birth, maternal education, illness severity, morphine cumulative dose, the presence of severe brain injury, and the administration of antiseizure, sedative, or anaesthetic medications) were controlled for in all prediction analyses.

FINDINGS

369 infants were included and an extensive set of 339 aEEG-EEG features was extracted, comprising nine qualitative parameters and 330 quantitative metrics. The machine learning-based regression models showed significant but relatively weak predictive performance (ranging from r=0·13 to r=0·23) for nine of 13 outcomes. However, the machine learning-based classifiers exhibited acceptable performance in identifying infants with intellectual impairments from those with optimal outcomes at age 5-7 years, achieving balanced accuracies of 0·77 (95% CI 0·62-0·90; p=0·0020) for full-scale intelligence quotient score and 0·81 (0·65-0·96; p=0·0010) for verbal intelligence quotient score. Both classifiers maintained identical performance when solely using quantitative features, achieving balanced accuracies of 0·77 (95% CI 0·63-0·91; p=0·0030) for full-scale intelligence quotient score and 0·81 (0·65-0·96; p=0·0010) for verbal intelligence quotient score.

INTERPRETATION

These findings highlight the potential benefits of using early postnatal aEEG-EEG features to automatically recognise extremely preterm infants with poor outcomes, facilitating the development of an interpretable prognostic tool that aids in decision making and therapy planning.

FUNDING

European Commission Horizon 2020.

Combining Cardiorespiratory Signals and Video-Based Actigraphy for Classifying Preterm Infant Sleep States

The classification of sleep state in preterm infants, particularly in distinguishing between active sleep (AS) and quiet sleep (QS), has been investigated using cardiorespiratory information such as electrocardiography (ECG) and respiratory signals. However, accurately differentiating between AS and wake remains challenging; therefore, there is a pressing need to include additional information to further enhance the classification performance. To address the challenge, this study explores the effectiveness of incorporating video-based actigraphy analysis alongside cardiorespiratory signals for classifying the sleep states of preterm infants. The study enrolled eight preterm infants, and a total of 91 features were extracted from ECG, respiratory signals, and video-based actigraphy. By employing an extremely randomized trees (ET) algorithm and leave-one-subject-out cross-validation, a kappa score of 0.33 was achieved for the classification of AS, QS, and wake using cardiorespiratory features only. The kappa score significantly improved to 0.39 when incorporating eight video-based actigraphy features. Furthermore, the classification performance of AS and wake also improved, showing a kappa score increase of 0.21. These suggest that combining video-based actigraphy with cardiorespiratory signals can potentially enhance the performance of sleep-state classification in preterm infants. In addition, we highlighted the distinct strengths and limitations of video-based actigraphy and cardiorespiratory data in classifying specific sleep states.

Brain injury and long-term outcome after neonatal surgery for non-cardiac congenital anomalies

BACKGROUND

There is growing evidence that neonatal surgery for non-cardiac congenital anomalies (NCCAs) in the neonatal period adversely affects long-term neurodevelopmental outcome. However, less is known about acquired brain injury after surgery for NCCA and abnormal brain maturation leading to these impairments.

METHODS

A systematic search was performed in PubMed, Embase, and The Cochrane Library on May 6, 2022 on brain injury and maturation abnormalities seen on magnetic resonance imaging (MRI) and its associations with neurodevelopment in neonates undergoing NCCA surgery the first month postpartum. Rayyan was used for article screening and ROBINS-I for risk of bias assessment. Data on the studies, infants, surgery, MRI, and outcome were extracted.

RESULTS

Three eligible studies were included, reporting 197 infants. Brain injury was found in n = 120 (50%) patients after NCCA surgery. Sixty (30%) were diagnosed with white matter injury. Cortical folding was delayed in the majority of cases. Brain injury and delayed brain maturation was associated with a decrease in neurodevelopmental outcome at 2 years of age.

CONCLUSIONS

Surgery for NCCA was associated with high risk of brain injury and delay in maturation leading to delay in neurocognitive and motor development. However, more research is recommended for strong conclusions in this group of patients.

IMPACT

Brain injury was found in 50% of neonates who underwent NCCA surgery. NCCA surgery is associated with a delay in cortical folding. There is an important research gap regarding perioperative brain injury and NCCA surgery.

Ultra-Wideband Radar for Simultaneous and Unobtrusive Monitoring of Respiratory and Heart Rates in Early Childhood: A Deep Transfer Learning Approach

Unobtrusive monitoring of children's heart rate (HR) and respiratory rate (RR) can be valuable for promoting the early detection of potential health issues, improving communication with healthcare providers and reducing unnecessary hospital visits. A promising solution for wireless vital sign monitoring is radar technology. This paper presents a novel approach for the simultaneous estimation of children's RR and HR utilizing ultra-wideband (UWB) radar using a deep transfer learning algorithm in a cohort of 55 children. The HR and RR are calculated by processing radar signals via spectrogram from time epochs of 10 s (25 sample length of hamming window with 90% overlap) and then transforming the resultant representation into 2-dimensional images. These images were fed into a pre-trained Visual Geometry Group-16 (VGG-16) model (trained on ImageNet dataset), with weights of five added layers fine-tuned using the proposed data. The prediction on the test data achieved a mean absolute error (MAE) of 7.3 beats per minute (BPM < 6.5% of average HR) and 2.63 breaths per minute (BPM < 7% of average RR). We also achieved a significant Pearson's correlation of 77% and 81% between true and extracted for HR and RR, respectively. HR and RR samples are extracted every 10 s.

Effects of the neonatal intensive care environment on circadian health and development of preterm infants

The circadian system in mammals ensures adaptation to the light-dark cycle on Earth and imposes 24-h rhythmicity on metabolic, physiological and behavioral processes. The central circadian pacemaker is located in the brain and is entrained by environmental signals called Zeitgebers. From here, neural, humoral and systemic signals drive rhythms in peripheral clocks in nearly every mammalian tissue. During pregnancy, disruption of the complex interplay between the mother's rhythmic signals and the fetal developing circadian system can lead to long-term health consequences in the offspring. When an infant is born very preterm, it loses the temporal signals received from the mother prematurely and becomes totally dependent on 24/7 care in the Neonatal Intensive Care Unit (NICU), where day/night rhythmicity is usually blurred. In this literature review, we provide an overview of the fetal and neonatal development of the circadian system, and short-term consequences of disruption of this process as occurs in the NICU environment. Moreover, we provide a theoretical and molecular framework of how this disruption could lead to later-life disease. Finally, we discuss studies that aim to improve health outcomes after preterm birth by studying the effects of enhancing rhythmicity in light and noise exposure.

Characterizing light-dark cycles in the Neonatal Intensive Care Unit: a retrospective observational study

Objectives: To characterize bedside 24-h patterns in light exposure in the Neonatal Intensive Care Unit (NICU) and to explore the environmental and individual patient characteristics that influence these patterns in this clinical setting. Methods: We conducted a retrospective cohort study that included 79 very preterm infants who stayed in an incubator with a built-in light sensor. Bedside light exposure was measured continuously (one value per minute). Based on these data, various metrics (including relative amplitude, intradaily variability, and interdaily stability) were calculated to characterize the 24-h patterns of light exposure. Next, we determined the association between these metrics and various environmental and individual patient characteristics. Results: A 24-h light-dark cycle was apparent in the NICU with significant differences in light exposure between the three nurse shifts (p < 0.001), with the highest values in the morning and the lowest values at night. Light exposure was generally low, with illuminances rarely surpassing 75 lux, and highly variable between patients and across days within a single patient. Furthermore, the season of birth and phototherapy had a significant effect on 24-h light-dark cycles, whereas no effect of bed location and illness severity were observed. Conclusion: Even without an official lighting regime set, a 24-h light-dark cycle was observed in the NICU. Various rhythmicity metrics can be used to characterize 24-h light-dark cycles in a clinical setting and to study the relationship between light patterns and health outcomes.

Morphine exposure and neurodevelopmental outcome in infants born extremely preterm

AIM

To investigate the association between morphine exposure in the neonatal period and neurodevelopment at 2 and 5 years of age while controlling for potential confounders.

METHOD

We performed a retrospective, single-centre cohort study on 106 infants (60 males, 46 females; mean gestational age 26 weeks [SD 1]) born extremely preterm (gestational age < 28 weeks). Morphine administration was expressed as cumulative dose (mg/kg) until term-equivalent age. Neurodevelopmental outcome was assessed at 2 years with the Bayley Scales of Infant and Toddler Development, Third Edition, Dutch version and at 5 years with the Wechsler Preschool and Primary Scale of Intelligence, Third Edition, Dutch version. Multiple linear regression analysis was used to assess the association between morphine exposure and outcome.

RESULTS

Sixty-four out of 106 (60.4%) infants included in the study received morphine. Morphine exposure was not associated with poorer motor, cognitive, and language subscores of the Bayley Scales of Infant and Toddler Development, Third Edition, Dutch version at 2 years. Morphine exposure was associated with lower Full-Scale IQ scores (p = 0.008, B = -9.3, 95% confidence interval [CI] = -15.6 to -3.1) and Performance IQ scores (p = 0.005, B = -17.5, 95% CI = -27.9 to -7) at 5 years of age.

INTERPRETATION

Morphine exposure in infants born preterm is associated with poorer Full-Scale IQ and Performance IQ at 5 years. Individualized morphine administration is advised in infants born extremely preterm.

Additional Value of 3-Month Cranial Magnetic Resonance Imaging in Infants with Neonatal Encephalopathy following Perinatal Asphyxia

OBJECTIVE

To assess the evolution of neonatal brain injury noted on magnetic resonance imaging (MRI), develop a score to assess brain injury on 3-month MRI, and determine the association of 3-month MRI with neurodevelopmental outcome in neonatal encephalopathy (NE) following perinatal asphyxia.

METHODS

This was a retrospective, single-center study including 63 infants with perinatal asphyxia and NE (n = 28 cooled) with cranial MRI <2 weeks and 2-4 months after birth. Both scans were assessed using biometrics, a validated injury score for neonatal MRI, and a new score for 3-month MRI, with a white matter (WM), deep gray matter (DGM), and cerebellum subscore. The evolution of brain lesions was assessed, and both scans were related to 18- to 24-month composite outcome. Adverse outcome included cerebral palsy, neurodevelopmental delay, hearing/visual impairment, and epilepsy.

RESULTS

Neonatal DGM injury generally evolved into DGM atrophy and focal signal abnormalities, and WM/watershed injury evolved into WM and/or cortical atrophy. Although the neonatal total and DGM scores were associated with composite adverse outcomes, the 3-month DGM score (OR 1.5, 95% CI 1.2-2.0) and WM score (OR 1.1, 95% CI 1.0-1.3) also were associated with composite adverse outcomes (occurring in n = 23). The 3-month multivariable model (including the DGM and WM subscores) had higher positive (0.88 vs 0.83) but lower negative predictive value (0.83 vs 0.84) than neonatal MRI. Inter-rater agreement for the total, WM, and DGM 3-month score was 0.93, 0.86, and 0.59.

CONCLUSIONS

In particular, DGM abnormalities on 3-month MRI, preceded by DGM abnormalities on the neonatal MRI, were associated with 18- to 24-month outcome, indicating the utility of 3-month MRI for treatment evaluation in neuroprotective trials. However, the clinical usefulness of 3-month MRI seems limited compared with neonatal MRI.

Introduction of ultra-high-field MR brain imaging in infants: vital parameters, temperature and comfort

Background

Brain MRI in infants at ultra-high-field scanners might improve diagnostic quality, but safety should be evaluated first. In our previous study, we reported simulated specific absorption rates and acoustic noise data at 7 Tesla.

Methods

In this study, we included twenty infants between term-equivalent age and three months of age. The infants were scanned on a 7 Tesla MRI directly after their clinically indicated 3 Tesla brain MRI scan. Vital parameters, temperature, and comfort were monitored throughout the process. Brain temperature was estimated during the MRI scans using proton MR spectroscopy.

Results

We found no significant differences in vital parameters, temperature, and comfort during and after 7 Tesla MRI scans, compared to 3 Tesla MRI scans.

Conclusions

These data confirm our hypothesis that scanning infants at 7 Tesla MRI appears to be safe and we identified no additional risks from scanning at 3 Tesla MRI.

The influence of nutrition on white matter development in preterm infants: a scoping review

White matter (WM) injury is the most common type of brain injury in preterm infants and is associated with impaired neurodevelopmental outcome (NDO). Currently, there are no treatments for WM injury, but optimal nutrition during early preterm life may support WM development. The main aim of this scoping review was to assess the influence of early postnatal nutrition on WM development in preterm infants. Searches were performed in PubMed, EMBASE, and COCHRANE on September 2022. Inclusion criteria were assessment of preterm infants, nutritional intake before 1 month corrected age, and WM outcome. Methods were congruent with the PRISMA-ScR checklist. Thirty-two articles were included. Negative associations were found between longer parenteral feeding duration and WM development, although likely confounded by illness. Positive associations between macronutrient, energy, and human milk intake and WM development were common, especially when fed enterally. Results on fatty acid and glutamine supplementation remained inconclusive. Significant associations were most often detected at the microstructural level using diffusion magnetic resonance imaging. Optimizing postnatal nutrition can positively influence WM development and subsequent NDO in preterm infants, but more controlled intervention studies using quantitative neuroimaging are needed. IMPACT: White matter brain injury is common in preterm infants and associated with impaired neurodevelopmental outcome. Optimizing postnatal nutrition can positively influence white matter development and subsequent neurodevelopmental outcome in preterm infants. More studies are needed, using quantitative neuroimaging techniques and interventional designs controlling for confounders, to define optimal nutritional intakes in preterm infants.

Respiratory Rate Extraction from Neonatal Near-Infrared Spectroscopy Signals

Background: Near-infrared spectroscopy (NIRS) relative concentration signals contain 'noise' from physiological processes such as respiration and heart rate. Simultaneous assessment of NIRS and respiratory rate (RR) using a single sensor would facilitate a perfectly time-synced assessment of (cerebral) physiology. Our aim was to extract respiratory rate from cerebral NIRS intensity signals in neonates admitted to a neonatal intensive care unit (NICU). Methods: A novel algorithm, NRR (NIRS RR), is developed for extracting RR from NIRS signals recorded from critically ill neonates. In total, 19 measurements were recorded from ten neonates admitted to the NICU with a gestational age and birth weight of 38 ± 5 weeks and 3092 ± 990 g, respectively. We synchronously recorded NIRS and reference RR signals sampled at 100 Hz and 0.5 Hz, respectively. The performance of the NRR algorithm is assessed in terms of the agreement and linear correlation between the reference and extracted RRs, and it is compared statistically with that of two existing methods. Results: The NRR algorithm showed a mean error of 1.1 breaths per minute (BPM), a root mean square error of 3.8 BPM, and Bland-Altman limits of agreement of 6.7 BPM averaged over all measurements. In addition, a linear correlation of 84.5% (p < 0.01) was achieved between the reference and extracted RRs. The statistical analyses confirmed the significant (p < 0.05) outperformance of the NRR algorithm with respect to the existing methods. Conclusions: We showed the possibility of extracting RR from neonatal NIRS in an intensive care environment, which showed high correspondence with the reference RR recorded. Adding the NRR algorithm to a NIRS system provides the opportunity to record synchronously different physiological sources of information about cerebral perfusion and respiration by a single monitoring system. This allows for a concurrent integrated analysis of the impact of breathing (including apnea) on cerebral hemodynamics.

Self-reported quantity and quality of sleep in children and adolescents with a chronic condition compared to healthy controls

To assess self-reported quantity and quality of sleep in Dutch children with a chronic condition compared to healthy controls and to the recommended hours of sleep for youth. Sleep quantity and quality were analyzed in children with a chronic condition (cystic fibrosis, chronic kidney disease, congenital heart disease, (auto-)immune disease, and medically unexplained symptoms (MUS); n = 291; 15 ± 3.1 years, 63% female. A subset of 171 children with a chronic condition were matched to healthy controls using Propensity Score matching, based on age and sex, ratio 1:4. Self-reported sleep quantity and quality were assessed with established questionnaires. Children with MUS were analyzed separately to distinguish between chronic conditions with and without an identified pathophysiological cause. Generally, children with a chronic condition met the recommended amount of sleep, however 22% reported poor sleep quality. No significant differences in sleep quantity and quality were found between the diagnosis groups. Children with a chronic condition and with MUS slept significantly more than healthy controls at ages 13, 15, and 16. Both at primary and secondary school, poor sleep quality was least frequent reported in children with a chronic condition and most often reported in children with MUS.  Conclusion: Overall, children with chronic conditions, including MUS, met the recommended hours of sleep for youth, and slept more than healthy controls. However, it is important to obtain a better understanding of why a substantial subset of children with chronic conditions, mostly children with MUS, still perceived their sleep quality as poor. What is Known: • According to the Consensus statement of the American Academy of Sleep medicine, typically developing children (6 to 12 years) should sleep 9 to 12 h per night, and adolescents (13 to 18 years) should sleep 8 to 10 h per night. • Literature on the optimal quantity and quality of sleep in children with a chronic condition is very limited. What is New: Our findings are important and provide novel insights: • In general, children with a chronic condition sleep according to the recommended hours of sleep. • A substantial subset of children with chronic conditions, perceived their sleep quality as poor. Although this was reported mostly by children with medically unexplained symptoms (MUS), the found poor sleep quality was independent of specific diagnosis.

A Scoping Review of Cerebral Doppler Arterial Waveforms in Infants

Cerebral Doppler ultrasound has been an important tool in pediatric diagnostics and prognostics for decades. Although the Doppler spectrum can provide detailed information on cerebral perfusion, the measured spectrum is often reduced to simple numerical parameters. To help pediatric clinicians recognize the visual characteristics of disease-associated Doppler spectra and identify possible areas for future research, a scoping review of primary studies on cerebral Doppler arterial waveforms in infants was performed. A systematic search in three online bibliographic databases yielded 4898 unique records. Among these, 179 studies included cerebral Doppler spectra for at least five infants below 1 y of age. The studies describe variations in the cerebral waveforms related to physiological changes (43%), pathology (62%) and medical interventions (40%). Characteristics were typically reported as resistance index (64%), peak systolic velocity (43%) or end-diastolic velocity (39%). Most studies focused on the anterior (59%) and middle (42%) cerebral arteries. Our review highlights the need for a more standardized terminology to describe cerebral velocity waveforms and for precise definitions of Doppler parameters. We provide a list of reporting variables that may facilitate unambiguous reports. Future studies may gain from combining multiple Doppler parameters to use more of the information encoded in the Doppler spectrum, investigating the full spectrum itself and using the possibilities for long-term monitoring with Doppler ultrasound.

Sleep and 24-hour rhythm characteristics in preschool children born very preterm and full term

STUDY OBJECTIVES

Sleep impacts the quality of life and is associated with cardiometabolic and neurocognitive outcomes. Little is known about the sleep of preterm-born children at preschool age. We, therefore, studied sleep and 24-hour rhythms of preschool children born very preterm compared with full-term children.

METHODS

This was a prospective cohort study comparing sleep quality and quantity of children born very preterm (gestational age [GA] < 30 weeks) with full-term children at the (corrected) age of 3 years, using (1) 2 parent-reported questionnaires (Brief Infant Sleep Questionnaire and The Munich Chronotype Questionnaire) and (2) at least 3 days of triaxial wrist actigraphy combined with sleep diary. We performed regression analyses with adjustment for sex (corrected), age, and birth weight standard deviation (SD) score.

RESULTS

Ninety-seven very-preterm-born (median GA 27+5; interquartile range 26 + 3;29 + 0 weeks) and 92 full-term children (GA 39 + 3; 38 + 4;40 + 4 weeks) were included. Sleep problems and other reported sleep parameters were not different between groups. As measured with actigraphy, sleep and 24-hour rhythm were similar between groups, except for very-preterm born children waking up 21 minutes (4;38) minutes later than full-term children (adjusted P = .001).

CONCLUSIONS

Based on parent reports and actigraphy, very-preterm-born children sleep quite similar to full-term controls at the corrected age of 3 years. Reported sleep problems were not different between groups. Actigraphy data suggest that preterm-born children may wake up later than children born full term. Further studies are needed to explore how sleep relates to cardiometabolic and neurodevelopmental outcomes after preterm birth and whether early interventions are useful to optimize 24-hour rhythm and sleep.

CITATION

Bijlsma A, Beunders VAA, Dorrepaal DJ, et al. Sleep and 24-hour rhythm characteristics in preschool children born very preterm and full term. J Clin Sleep Med. 2023;19(4):685-693.

Susceptibility weighted imaging can be a sensitive sequence to detect brain damage in neonates with kernicterus: a case report

BACKGROUND

Kernicterus in the acute phase is difficult to diagnose. It depends on a high signal on T1 at the globus pallidum and subthalamic nucleus level. Unfortunately, these areas also show a relatively high signal on T1 in neonates as an expression of early myelination. Therefore, a less myelin-dependent sequence, like SWI, may be more sensitive to detecting damage in the globus pallidum area.

CASE PRESENTATION

A term baby developed jaundice on day three following an uncomplicated pregnancy and delivery. Total bilirubin peaked at 542 μmol/L on day four. Phototherapy was started, and an exchange transfusion was performed. ABR showed absent responses on day 10. MRI on day eight demonstrated abnormal high signal globus pallidus on T1w, isointense on T2w, without diffusion restriction, and high signal on SWI at globus pallidal and subthalamus level and phase image at globus pallidal level. These findings were consistent with the challenging diagnosis of kernicterus. On follow-up, the infant presented with sensorineural hearing loss and had a work-up for cochlear implant surgery. At 3 months of age, the follow-up MR shows normalization of the T1 and SWI signals and a high signal on T2.

CONCLUSIONS

SWI seems more sensitive to injury than the T1w and lacks the disadvantage of the T1w sequence, where early myelin confers a high signal.

Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG

OBJECTIVE

To investigate the feasibility of automated sleep staging based on quantitative analysis of dual-channel electroencephalography (EEG) for extremely and very preterm infants during their first postnatal days.

METHODS

We enrolled 17 preterm neonates born between 25 and 30 weeks of gestational age. Three-hour behavioral sleep observations and simultaneous dual-channel EEG monitoring were conducted for each infant within their first 72 hours after birth. Four kinds of representative and complementary quantitative EEG (qEEG) metrics (i.e., bursting, synchrony, spectral power, and complexity) were calculated and compared between active sleep, quiet sleep, and wakefulness. All analyses were performed in offline mode.

RESULTS

In separate comparison analyses, significant differences between sleep-wake states were found for bursting, spectral power and complexity features. The automated sleep-wake state classifier based on the combination of all qEEG features achieved a macro-averaged area under the curve of receiver operating characteristic of 74.8%. The complexity features contributed the most to sleep-wake state classification.

CONCLUSIONS

It is feasible to distinguish between sleep-wake states within the first 72 postnatal hours for extremely and very preterm infants using qEEG metrics.

SIGNIFICANCE

Our findings offer the possibility of starting personalized care dependent on preterm infants' sleep-wake states directly after birth, potentially yielding long-run benefits for their developmental outcomes.

Device-based and subjective measurements of sleep in children with cerebral palsy: a comparison of sleep diary, actigraphy, and bed sensor data

STUDY OBJECTIVES

To investigate how subjective assessments and device-based measurements of sleep relate to each other in children with cerebral palsy (CP).

METHODS

Sleep of children with CP, classified at Gross Motor Function Classification System levels I-III, was measured during 7 consecutive nights using 1 subjective (ie, sleep diary) and 2 device-based (ie, actigraphy and bed sensor) instruments. The agreement between the instruments was assessed for all nights and separately for school- and weekend nights, using intraclass correlation coefficients (ICC) and Bland-Altman plots.

RESULTS

A total of 227 nights from 38 children with CP (53% male; median age [range] 6 [2-12] years), were included in the analyses. Sleep parameters showed poor agreement between the 3 instruments, except for total time in bed, which showed satisfactory agreement between (1) actigraphy and sleep diary (ICC > 0.86), (2) actigraphy and bed sensor (ICC > 0.84), and (3) sleep diary and bed sensor (ICC > 0.83). Furthermore, agreement between sleep diary and bed sensor was also satisfactory for total sleep time (ICC > 0.70) and wakefulness after sleep onset (ICC = 0.55; only during weekend nights).

CONCLUSIONS

Researchers and clinicians need to be aware of the discrepancies between instruments for sleep monitoring in children with CP. We recommend combining both subjective and device-based measures to provide information on the perception as well as an unbiased estimate of sleep. Further research needs to be conducted on the use of a bed sensor for sleep monitoring in children with CP.

CITATION

van Rijssen IM, Hulst RY, Gorter JW, et al. Device-based and subjective measurements of sleep in children with cerebral palsy: a comparison of sleep diary, actigraphy, and bed sensor data. J Clin Sleep Med. 2023;19(1):35-43.

Estimation of Respiratory Rate from Functional Near-Infrared Spectroscopy (fNIRS): A New Perspective on Respiratory Interference

OBJECTIVE

Respiration is recognized as a systematic physiological interference in functional near-infrared spectroscopy (fNIRS). However, it remains unanswered as to whether it is possible to estimate the respiratory rate (RR) from such interference. Undoubtedly, RR estimation from fNIRS can provide complementary information that can be used alongside the cerebral activity analysis, e.g., sport studies. Thus, the objective of this paper is to propose a method for RR estimation from fNIRS. Our primary presumption is that changes in the baseline wander of oxygenated hemoglobin concentration (O2Hb) signal are related to RR.

METHODS

fNIRS and respiratory signals were concurrently collected from subjects during controlled breathing tasks at a constant rate from 0.1 Hz to 0.4 Hz. Firstly, the signal quality index algorithm is employed to select the best O2Hb signal, and then a band-pass filter with cut-off frequencies from 0.05 to 2 Hz is used to remove very low- and high-frequency artifacts. Secondly, troughs of the filtered O2Hb signal are localized for synthesizing the baseline wander (S1) using cubic spline interpolation. Finally, the fast Fourier transform of the S1 signal is computed, and its dominant frequency is considered as RR. In this paper, two different datasets were employed, where the first one was used for the parameter adjustment of the proposed method, and the second one was solely used for testing.

RESULTS

The low mean absolute error between the reference and estimated RRs for the first and second datasets (2.6 and 1.3 breaths per minute, respectively) indicates the feasibility of the proposed method for RR estimation from fNIRS.

SIGNIFICANCE

This paper provides a novel view on the respiration interference as a source of complementary information in fNIRS.

The relationship between interhemispheric synchrony, morphine and microstructural development of the corpus callosum in extremely preterm infants

The primary aim of this study is to examine whether bursting interhemispheric synchrony (bIHS) in the first week of life of infants born extremely preterm, is associated with microstructural development of the corpus callosum (CC) on term equivalent age magnetic resonance imaging scans. The secondary aim is to address the effects of analgesics such as morphine, on bIHS in extremely preterm infants. A total of 25 extremely preterm infants (gestational age [GA] < 28 weeks) were monitored with the continuous two-channel EEG during the first 72 h and after 1 week from birth. bIHS was analyzed using the activation synchrony index (ASI) algorithm. Microstructural development of the CC was assessed at ~ 30 and ~ 40 weeks of postmenstrual age (PMA) using fractional anisotropy (FA) measurements. Multivariable regression analyses were used to assess the primary and secondary aim. Analyses were adjusted for important clinical confounders: morphine, birth weight z-score, and white matter injury score. Due to the reduced sample size, only the most relevant variables, according to literature, were included. ASI was not significantly associated with FA of the CC at 30 weeks PMA and at 40 weeks PMA (p > .5). ASI was positively associated with the administration of morphine (p < .05). Early cortical synchrony may be affected by morphine and is not associated with the microstructural development of the CC. More studies are needed to evaluate the long-term effects of neonatal morphine treatment to optimize sedation in this high-risk population.

A Perspective on a Quality Management System for AI/ML-Based Clinical Decision Support in Hospital Care

Although many artificial intelligence (AI) and machine learning (ML) based algorithms are being developed by researchers, only a small fraction has been implemented in clinical-decision support (CDS) systems for clinical care. Healthcare organizations experience significant barriers implementing AI/ML models for diagnostic, prognostic, and monitoring purposes. In this perspective, we delve into the numerous and diverse quality control measures and responsibilities that emerge when moving from AI/ML-model development in a research environment to deployment in clinical care. The Sleep-Well Baby project, a ML-based monitoring system, currently being tested at the neonatal intensive care unit of the University Medical Center Utrecht, serves as a use-case illustrating our personal learning journey in this field. We argue that, in addition to quality assurance measures taken by the manufacturer, user responsibilities should be embedded in a quality management system (QMS) that is focused on life-cycle management of AI/ML-CDS models in a medical routine care environment. Furthermore, we highlight the strong similarities between AI/ML-CDS models and in vitro diagnostic devices and propose to use ISO15189, the quality guideline for medical laboratories, as inspiration when building a QMS for AI/ML-CDS usage in the clinic. We finally envision a future in which healthcare institutions run or have access to a medical AI-lab that provides the necessary expertise and quality assurance for AI/ML-CDS implementation and applies a QMS that mimics the ISO15189 used in medical laboratories.

Post-hemorrhagic ventricular dilatation affects white matter maturation in extremely preterm infants

BACKGROUND

Data on microstructural white matter integrity in preterm infants with post-hemorrhagic ventricular dilatation (PHVD) using diffusion tensor imaging (DTI) are limited. Also, to date, no study has focused on the DTI changes in extremely preterm (EP) infants with PHVD.

METHODS

A case-control study of EP infants <28 weeks' gestation with PHVD was conducted. Diffusivity and fractional anisotropy (FA) values of corticospinal tracts (CST) and corpus callosum (CC) were measured using DTI at term-equivalent age. Outcomes were assessed at 2-years-corrected age.

RESULTS

Twenty-one infants with PHVD and 21 matched-controls were assessed. FA values in the CC were lower in infants with PHVD compared with controls (mean difference, 0.05 [95% confidence interval (CI), 0.02-0.08], p < 0.001). In infants with periventricular hemorrhagic infarction, FA values in the CC were lower than in controls (mean difference, 0.05 [95% CI, 0.02-0.09], p = 0.005). The composite cognitive and motor scores were associated with the FA value of the CC (coefficient 114, p = 0.01 and coefficient 147, p = 0.004; respectively).

CONCLUSIONS

Extremely preterm infants with PHVD showed lower FA values in CC. A positive correlation was also shown between the composite cognitive and motor scores and FA value of the CC at 2-years-corrected age.

IMPACT

Extremely preterm infants with post-hemorrhagic ventricular dilatation showed lower fractional anisotropy values in their corpus callosum compared with controls reflecting the impaired microstructure of these commissural nerve fibers that are adjacent to the dilated ventricles. Impaired microstructure of the corpus callosum was shown to be associated with cognitive and motor scores at 2-years-corrected age.

The Sleep Well Baby project: an automated real-time sleep–wake state prediction algorithm in preterm infants

Study Objectives

Sleep is an important driver of early brain development. However, sleep is often disturbed in preterm infants admitted to the neonatal intensive care unit (NICU). We aimed to develop an automated algorithm based on routinely measured vital parameters to classify sleep–wake states of preterm infants in real-time at the bedside.

Methods

In this study, sleep–wake state observations were obtained in 1-minute epochs using a behavioral scale developed in-house while vital signs were recorded simultaneously. Three types of vital parameter data, namely, heart rate, respiratory rate, and oxygen saturation, were collected at a low-frequency sampling rate of 0.4 Hz. A supervised machine learning workflow was used to train a classifier to predict sleep–wake states. Independent training (n = 37) and validation datasets were validation n = 9) datasets were used. Finally, a setup was designed for real-time implementation at the bedside.

Results

The macro-averaged area-under-the-receiver-operator-characteristic (AUROC) of the automated sleep staging algorithm ranged between 0.69 and 0.82 for the training data, and 0.61 and 0.78 for the validation data. The algorithm provided the most accurate prediction for wake states (AUROC = 0.80). These findings were well validated on an independent sample (AUROC = 0.77).

Conclusions

With this study, to the best of our knowledge, a reliable, nonobtrusive, and real-time sleep staging algorithm was developed for the first time for preterm infants. Deploying this algorithm in the NICU environment may assist and adapt bedside clinical work based on infants’ sleep–wake states, potentially promoting the early brain development and well-being of preterm infants.

Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants

The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.

Language lateralization in very preterm children: associating dichotic listening to interhemispheric connectivity and language performance

BACKGROUND

Language difficulties of very preterm (VPT) children might be related to weaker cerebral hemispheric lateralization of language. Language lateralization refers to the development of an expert region for language processing in the left hemisphere during the first years of life. Children born VPT might not develop such a dominant left hemisphere for language processing. A dichotic listening task may be a functional task to show the dominance of the left hemisphere during language processing. During this task, different acoustic events are simultaneously presented to both ears. Due to crossing fibers in the brain, right ear stimuli are transferred directly to the left hemisphere, and left ear stimuli are transferred first to the right hemisphere and then, through the corpus callosum (CC), to the left hemisphere. Dichotic listening typically shows a right ear advantage, assuming to reflect left hemispherical language dominance. The CC, in particular the splenium, is associated with auditory processing and is considered important for language lateralization. The objective of this work was to explore whether dichotic listening performance in school-aged VPT children are associated with language performance and interhemispheric connectivity.

METHODS

This is a cross-sectional study of 58 VPT children and 30 full term controls at age 10 years. Language performance and dichotic digit test (DDT) were assessed. In 44 VPT children, additionally diffusion weighted imaging (DWI) was performed using a 3 T MRI scanner. Fractional anisotropy (FA) and mean diffusivity (MD) values of the splenium of the CC were extracted.

RESULTS

Poorer right ear DDT scores were associated with poorer language performance in VPT children only (p = 0.015). Association between right ear DDT scores and MD of the splenium approached the level of significance (p = 0.051).

CONCLUSIONS

These results support the hypothesis that poor language performance in VPT children may be a consequence of weaker lateralized language organization, due to a poorly developed splenium of the CC. Dichotic listening may reflect the level of language lateralization in VPT children.

IMPACT

Poor language performance in VPT children may be a consequence of weaker lateralized language organization, due to a poorly developed splenium of the CC. Dichotic listening performance may reflect the level of language lateralization in VPT children and right ear scores of a dichotic listening task are associated with both the splenium of the corpus callosum and language performance. If our results could be validated in future research, it suggests that poor CC development may indicate VPT children at risk for long-term language problems.

Early Speech Sound Production and Its Trajectories in Very Preterm Children From 2 to 4 Years of Age

PURPOSE

Very preterm (VPT) children are at risk for speech and language problems throughout school age. However, little is known about early speech sound production in these children. This study aims to present a detailed description of early speech sound production and its trajectories in VPT children from 2 to 4 years of age. In addition, this study aimed to determine if early speech sound production is associated with speech production and expressive language function at 4 years of age.

METHOD

In 63 VPT children (< 32 weeks of gestation, 41 boys, mean gestational age = 28.8 weeks, mean birth weight = 1,135 g), speech sound production was assessed by naturalistic speech analysis at 2 years of corrected age and speech and language function by standardized tests at 4 years of age.

RESULTS

Speech sound production was found to be abnormal in 49% of the VPT children at 2 years of age and in 19% at 4 years of age. Four different speech production trajectories from 2 to 4 years of age could be identified: a normal trajectory, an abnormal trajectory, a catch-up trajectory, and a growing-into-deficit trajectory. Early speech production, defined by the number of acquired consonants at 2 years of age, significantly predicted the word production score at 4 years of age and the sentence production score at 4 years of age.

CONCLUSIONS

Compared to the general population, an alarmingly high proportion of VPT children showed speech production problems at 2 years of age. About half of these children showed persistent speech problems at 4 years of age. Moreover, these problems were associated with expressive language problems at the age of 4 years.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.19310822.

Neonatal quantitative electroencephalography and long-term outcomes: a systematic review

AIM

To evaluate quantitative electroencephalogram (EEG) measures as predictors of long-term neurodevelopmental outcome in infants with a postconceptional age below 46 weeks, including typically developing infants born at term, infants with heterogeneous underlying pathologies, and infants born preterm.

METHOD

A comprehensive search was performed using PubMed, Embase, and Web of Science from study inception up to 8th January 2021. Studies that examined associations between neonatal quantitative EEG measures, based on conventional and amplitude-integrated EEG, and standardized neurodevelopmental outcomes at 2 years of age or older were reviewed. Significant associations between neonatal quantitative EEG and long-term outcome measures were grouped into one or more of the following categories: cognitive outcome; motor outcome; composite scores; and other standardized outcome assessments.

RESULTS

Twenty-four out of 1740 studies were included. Multiple studies showed that conventional EEG-based absolute power in the delta, theta, alpha, and beta frequency bands and conventional and amplitude-integrated EEG-related amplitudes were positively associated with favourable long-term outcome across several domains, including cognition and motor performance. Furthermore, a lower presence of discontinuous background pattern was also associated with favourable outcomes. However, interpretation of the results is limited by heterogeneity in study design and populations.

INTERPRETATION

Neonatal quantitative EEG measures may be used as prognostic biomarkers to identify those infants who will develop long-term difficulties and who might benefit from early interventions.

Early Ultrasonic Monitoring of Brain Growth and Later Neurodevelopmental Outcome in Very Preterm Infants

BACKGROUND AND PURPOSE

In infants born very preterm, monitoring of early brain growth could contribute to prediction of later neurodevelopment. Therefore, our aim was to investigate associations between 2 early cranial ultrasound markers (corpus callosum-fastigium and corpus callosum length) and neurodevelopmental outcome and the added value of both markers in the prediction of neurodevelopmental outcome based on neonatal risk factors and head circumference in very preterm infants.

MATERIALS AND METHODS

This prospective observational study included 225 infants born at <30 weeks' gestational age, of whom 153 were without any brain injury on cranial ultrasound. Corpus callosum-fastigium and corpus callosum length and head circumference were measured at birth, 29 weeks' gestational age, transfer from the neonatal intensive care unit to a level II hospital, and 2 months' corrected age. We analyzed associations of brain markers and their growth with cognitive, motor, language, and behavioral outcome at 2 years' corrected age.

RESULTS

In infants without brain injury, greater corpus callosum-fastigium length at 2 months was associated with better cognitive outcome. Corpus callosum length at 2 months was positively associated with cognitive, motor, and language outcome. Faster growth of the corpus callosum length between birth and 2 months was associated with better cognitive and motor function. Prediction of neurodevelopmental outcome based on neonatal risk factors with or without head circumference was significantly improved by adding corpus callosum length.

CONCLUSIONS

Both corpus callosum-fastigium and corpus callosum length on cranial ultrasound are associated with neurodevelopmental outcome of very preterm infants without brain injury at 2 years, but only corpus callosum length shows the added clinical utility in predicting neurodevelopmental outcome.

Are multidisciplinary neurodevelopmental profiles of children born very preterm at age 2 relevant to their long-term development? A preliminary study

To identify distinctive multidisciplinary neurodevelopmental profiles of relatively healthy children born very preterm (VPT) and describe the longitudinal course of these profiles up to age 10. At 2 years of corrected age, 84 children born VPT underwent standardized testing for cognitive, language, speech, motor, behavioral, and auditory nerve function. These data were submitted to factor and cluster analysis. Sixty-one of these children underwent cognitive, language, and behavioral assessment again at age 10. Descriptive statistics were used to analyze longitudinal trajectories for each profile. Four neurodevelopmental profiles were identified at age 2. Profile 1 children (n = 22/26%) had excellent cognitive-language-motor function, normal behavioral and auditory nerve function, but showed an unexpected severe decline up to age 10. Profile 2 children (n = 16/19%) had very low behavioral function, low cognitive-language-motor function, and accelerated auditory nerve function. Their scores remained low up until age 10. Profile 3 children (n = 17/20%) had delayed auditory nerve function, low behavioral function, and slightly lower cognitive-language-motor function. They showed the most increasing trajectory. Profile 4 children (n = 29/35%) had very low cognitive-language-motor function, normal behavioral and auditory nerve function, but showed wide variation in their trajectory. Our preliminary study showed that a multidisciplinary profile-oriented approach may be important in children born VPT to improve counseling and provide targeted treatment for at risk children. High performers at age 2 may not be expected to maintain their favorable development. Behavioral problems might negatively impact language development. Delayed auditory nerve function might represent a slow start and catch-up development.

Precision Medicine in Neonates: A Tailored Approach to Neonatal Brain Injury

Despite advances in neonatal care to prevent neonatal brain injury and neurodevelopmental impairment, predicting long-term outcome in neonates at risk for brain injury remains difficult. Early prognosis is currently based on cranial ultrasound (CUS), MRI, EEG, NIRS, and/or general movements assessed at specific ages, and predicting outcome in an individual (precision medicine) is not yet possible. New algorithms based on large databases and machine learning applied to clinical, neuromonitoring, and neuroimaging data and genetic analysis and assays measuring multiple biomarkers (omics) can fulfill the needs of modern neonatology. A synergy of all these techniques and the use of automatic quantitative analysis might give clinicians the possibility to provide patient-targeted decision-making for individualized diagnosis, therapy, and outcome prediction. This review will first focus on common neonatal neurological diseases, associated risk factors, and most common treatments. After that, we will discuss how precision medicine and machine learning (ML) approaches could change the future of prediction and prognosis in this field.

A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video

Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake pattern, which functions as an essential indicator of neurophysiological organization in the neonatal period, has profound meaning in the prediction of cognitive diseases and brain maturity. In recent years, unobtrusive sleep monitoring and automatic sleep staging have been intensively studied for adults, but much less for neonates. This work aims to investigate a novel video-based unobtrusive method for neonatal sleep-wake classification by analyzing the behavioral changes in the neonatal facial region. A hybrid model is proposed to monitor the sleep-wake patterns of human neonates. The model combines two algorithms: deep convolutional neural network (DCNN) and support vector machine (SVM), where DCNN works as a trainable feature extractor and SVM as a classifier. Data was collected from nineteen Chinese neonates at the Children's Hospital of Fudan University, Shanghai, China. The classification results are compared with the gold standard of video-electroencephalography scored by pediatric neurologists. Validations indicate that the proposed hybrid DCNN-SVM model achieved reliable performances in classifying neonatal sleep and wake states in RGB video frames (with the face region detected), with an accuracy of 93.8 ± 2.2% and an F1-score 0.93 ± 0.3.

Cerebellar injury in term neonates with hypoxic-ischemic encephalopathy is underestimated

BACKGROUND

Postmortem examinations frequently show cerebellar injury in infants with severe hypoxic-ischemic encephalopathy (HIE), while it is less well visible on MRI. The primary aim was to investigate the correlation between cerebellar apparent diffusion coefficient (ADC) values and histopathology in infants with HIE. The secondary aim was to compare ADC values in the cerebellum of infants with HIE and infants without brain injury.

METHODS

ADC values in the cerebellar vermis, hemispheres and dentate nucleus (DN) of (near-)term infants with HIE (n = 33) within the first week after birth were compared with neonates with congenital non-cardiac anomalies, normal postoperative MRIs and normal outcome (n = 22). Microglia/macrophage activation was assessed using CD68 and/or HLA-DR staining and Purkinje cell (PC) injury using H&E-stained slices. The correlation between ADC values and the histopathological measures was analyzed.

RESULTS

ADC values in the vermis (p = 0.021) and DN (p < 0.001) were significantly lower in infants with HIE compared to controls. ADC values in the cerebellar hemispheres were comparable. ADC values in the vermis were correlated with the number and percentage of normal PCs; otherwise ADC values and histology were not correlated.

CONCLUSION

Histopathological injury in the cerebellum is common in infants with HIE. ADC values underestimate histopathological injury.

IMPACT

ADC values might underestimate cerebellar injury in neonates with HIE. ADC values in the vermis and dentate nucleus of infants with HIE are lower compared to controls, but not in the cerebellar hemispheres. Abnormal ADC values are only found when cytotoxic edema is very severe. ADC values in the vermis are correlated with Purkinje cell injury in the vermis; furthermore, there were no correlations between ADC values and histopathological measures.

Radar-based sleep stage classification in children undergoing polysomnography: a pilot-study

STUDY OBJECTIVES

Unobtrusive monitoring of sleep and sleep disorders in children presents challenges. We investigated the possibility of using Ultra-Wide band (UWB) radar to measure sleep in children.

METHODS

Thirty-two children scheduled to undergo a clinical polysomnography participated; their ages ranged from 2 months to 14 years. During the polysomnography, the children's body movements and breathing rate were measured by an UWB-radar. A total of 38 features were calculated from the motion signals and breathing rate obtained from the raw radar signals. Adaptive boosting was used as machine learning classifier to estimate sleep stages, with polysomnography as gold standard method for comparison.

RESULTS

Data of all participants combined, this study achieved a Cohen's Kappa coefficient of 0.67 and an overall accuracy of 89.8% for wake and sleep classification, a Kappa of 0.47 and an accuracy of 72.9% for wake, rapid-eye-movement (REM) sleep, and non-REM sleep classification, and a Kappa of 0.43 and an accuracy of 58.0% for wake, REM sleep, light sleep and deep sleep classification.

CONCLUSION

Although the current performance is not sufficient for clinical use yet, UWB radar is a promising method for non-contact sleep analysis in children.

Beginning to See the Light: Lessons Learned From the Development of the Circadian System for Optimizing Light Conditions in the Neonatal Intensive Care Unit

The circadian timing system optimizes health by temporally coordinating behavior and physiology. During mammalian gestation, fetal circadian rhythms are synchronized by the daily fluctuations in maternal body temperature, hormones and nutrients. Circadian disruption during pregnancy is associated with negative effects on developmental outcomes in the offspring, highlighting the importance of regular and robust 24-h rhythms over gestation. In the case of preterm birth (before 37 weeks of gestation), maternal cues no longer synchronize the neonate's circadian system, which may adversely affect the neonate. There is increasing evidence that introducing robust light-dark cycles in the Neonatal Intensive Care Unit has beneficial effects on clinical outcomes in preterm infants, such as weight gain and hospitalization time, compared to infants exposed to constant light or constant near-darkness. However, the biological basis for these effects and the relationship with the functional and anatomical development of the circadian system is not fully understood. In this review, we provide a concise overview of the effects of light-dark cycles on clinical outcomes of preterm neonates in the NICU and its alignment with the development of the circadian system.

NutriBrain: protocol for a randomised, double-blind, controlled trial to evaluate the effects of a nutritional product on brain integrity in preterm infants

Background

The gut microbiota and the brain are connected through different mechanisms. Bacterial colonisation of the gut plays a substantial role in normal brain development, providing opportunities for nutritional neuroprotective interventions that target the gut microbiome. Preterm infants are at risk for brain injury, especially white matter injury, mediated by inflammation and infection. Probiotics, prebiotics and L-glutamine are nutritional components that have individually already demonstrated beneficial effects in preterm infants, mostly by reducing infections or modulating the inflammatory response. The NutriBrain study aims to evaluate the benefits of a combination of probiotics, prebiotics and L-glutamine on white matter microstructure integrity (i.e., development of white matter tracts) at term equivalent age in very and extremely preterm born infants.

Methods

This study is a double-blind, randomised, controlled, parallel-group, single-center study. Eighty-eight infants born between 24 + 0 and < 30 + 0 weeks gestational age and less than 72 h old will be randomised after parental informed consent to receive either active study product or placebo. Active study product consists of a combination of Bifidobacterium breve M-16V, short-chain galacto-oligosaccharides, long-chain fructo-oligosaccharides and L-glutamine and will be given enterally in addition to regular infant feeding from 48 to 72 h after birth until 36 weeks postmenstrual age. The primary study outcome of white matter microstructure integrity will be measured as fractional anisotropy, assessed using magnetic resonance diffusion tensor imaging at term equivalent age and analysed using Tract-Based Spatial Statistics. Secondary outcomes are white matter injury, brain tissue volumes and cortical morphology, serious neonatal infections, serum inflammatory markers and neurodevelopmental outcome.

Discussion

This study will be the first to evaluate the effect of a combination of probiotics, prebiotics and L-glutamine on brain development in preterm infants. It may give new insights in the development and function of the gut microbiota and immune system in relation to brain development and provide a new, safe treatment possibility to improve brain development in the care for preterm infants.

Trial registration

ISRCTN, ISRCTN96620855. Date assigned: 10/10/2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12887-021-02570-x.

Mammillary body atrophy and other MRI correlates of school-age outcome following neonatal hypoxic-ischemic encephalopathy

The mammillary bodies (MB) and hippocampi are important for memory function and are often affected following neonatal hypoxic ischemic encephalopathy (HIE). The aim of this study was to assess neurodevelopmental outcome in 10-year-old children with HIE with and without therapeutic hypothermia. Additional aims were to assess the associations between MB atrophy, brain volumes (including the hippocampi), white matter microstructure and neurodevelopmental outcome at school-age. Ten-year-old children with HIE were included, who were treated with therapeutic hypothermia (n = 22) or would have qualified but were born before this became standard of care (n = 28). Children completed a neuropsychological and motor assessment and MRI. Mammillary bodies were scored as normal or atrophic at 10 years. Brain volumes were segmented on childhood MRI and DTI scans were analysed using tract-based spatial statistics. Children with HIE suffered from neurocognitive and memory problems at school-age, irrespective of hypothermia. Hippocampal volumes and MB atrophy were associated with total and performance IQ, processing speed and episodic memory in both groups. Normal MB and larger hippocampi were positively associated with global fractional anisotropy. In conclusion, injury to the MB and hippocampi was associated with neurocognition and memory at school-age in HIE and might be an early biomarker for neurocognitive and memory problems.

The relationship between preterm birth and sleep in children at school age: A systematic review

Premature birth (before 37 weeks of gestation) has been linked to a variety of adverse neurological outcomes. Sleep problems are associated with decreased neurocognitive functioning, which is especially common in children born preterm. The exact relationship between prematurity and sleep at school age is unknown. A systematic review is performed with the aim to assess the relationship between prematurity and sleep at school age (5th to 18th year of life), in comparison to sleep of their peers born full-term. Of 347 possibly eligible studies, nine were included. The overall conclusion is that prematurity is associated with earlier bedtimes and a lower sleep quality, in particular more nocturnal awakenings and more non-rapid eye movement stage 2 sleep. Interpretations and limitations of the review are discussed. Moreover, suggestions for future research are brought forward, including the need for a systematic approach with consistent outcome measures in this field of research. A better understanding of the mechanisms that influence sleep in the vulnerable group of children born preterm could help optimize these children's behavioral and intellectual development.

Pathophysiology of Cerebral Hyperperfusion in Term Neonates With Hypoxic-Ischemic Encephalopathy: A Systematic Review for Future Research

Worldwide neonatal hypoxic-ischemic encephalopathy (HIE) is a common cause of mortality and neurologic disability, despite the implementation of therapeutic hypothermia treatment. Advances toward new neuroprotective interventions have been limited by incomplete knowledge about secondary injurious processes such as cerebral hyperperfusion commonly observed during the first 1-5 days after asphyxia. Cerebral hyperperfusion is correlated with adverse neurodevelopmental outcome and it is a process that remains poorly understood. In order to provide an overview of the existing knowledge on the pathophysiology and highlight the gaps in current understanding of cerebral hyperperfusion in term animals and neonates with HIE, we performed a systematic research. We included papers scoping for study design, population, number of participants, study technique and relevant findings. Methodological quality was assessed using the checklist for cohort studies from The Joanna Briggs Institute. Out of 2,690 results, 34 studies were included in the final review-all prospective cohort studies. There were 14 studies of high, 17 moderate and 3 of low methodological quality. Data from the literature were analyzed in two main subjects: (1) Hemodynamic Changes subdivided into macro- and microscopic hemodynamic changes, and (2) Endogenous Pathways which was subdivided into N-methyl-D-aspartate/Mitogen activated protein kinase (NDMA/MAPK), Nitric Oxide (NO), prostanoids and other endogenous studies. Cerebral hyperperfusion in term neonates with HIE was found to be present 10-30 min after the hypoxic-ischemic event and was still present around day 10 and up to 1 month after birth. Cerebral hyperperfusion was also characterized by angiogenesis and cerebral vasodilation. Additionally, cerebral vasodilation was mediated by endogenous pathways such as MAPK through urokinase Plasminogen Activator (uPA), by neuronal NO synthase following NMDA and by prostanoid synthesis. Future research should elucidate the precise role of NMDA, MAPK and prostanoids in cerebral hyperperfusion. Moreover, research should focus on possible interventions and the effect of hypothermia on hyperperfusion. These findings should be taken into account simultaneously with brain imagining techniques, becoming a valuable asset in assessing the impact in neurodevelopmental outcome.

24-hour activity for children with cerebral palsy: a clinical practice guide

The association between physical activity and health has been clearly established, and the promotion of physical activity should be viewed as a cost-effective approach that is universally prescribed as a first-line treatment for nearly every chronic disease. Health care providers involved in the care for individuals with cerebral palsy (CP) are encouraged to take an active role in promoting their health and well-being. Balancing activity behaviours across the whole day, with improved physical activity, reduced sedentary time, and healthy sleep behaviours, can set up infants, preschool-, and school-aged children with CP for a healthy trajectory across their lifetime. However, most clinicians do not apply a systematic surveillance, assessment, and management approach to detect problems with physical activity or sleep in children with CP. Consequently, many children with CP miss out on an important first line of treatment. This article presents an evidence-informed clinical practice guide with practical pointers to help practitioners in detecting 24-hour activity problems as a critical step towards adoption of healthy lifestyle behaviours for children with CP that provide long-term health benefits.

Current ideas about the roles of rapid eye movement and non-rapid eye movement sleep in brain development

Understanding the links between sleep and brain development is important, as rapid eye movement (REM) sleep and non-REM (NREM) sleep seem to contribute to different aspects of brain maturation. If children have sleep problems, REM sleep and NREM sleep are likely to have different consequences for their developing brain, depending on their age. We highlight important discoveries from human and animal research on the role sleep plays in brain development. A hypothetical model is presented to explain the dynamic relationship of REM sleep and NREM sleep with different processes of brain maturation, with implications for current neonatal care and future research.

Synthetic MRI demonstrates prolonged regional relaxation times in the brain of preterm born neonates with severe postnatal morbidity

BACKGROUND

To identify preterm infants at risk for neurodevelopment impairment that might benefit from early neurorehabilitation, early prognostic biomarkers of future outcomes are needed.

OBJECTIVE

To determine whether synthetic MRI is sensitive to age-related changes in regional tissue relaxation times in the brain of preterm born neonates when scanned at term equivalent age (TEA, 37-42 weeks), and to investigate whether severe postnatal morbidity results in prolonged regional tissue relaxation times.

MATERIALS AND METHODS

This retrospective study included 70 very preterm born infants scanned with conventional and synthetic MRI between January 2017 and June 2019 at TEA. Infants with severe postnatal morbidity were allocated to a high-risk group (n = 22). All other neonates were allocated to a low-risk group (n = 48). Linear regression analysis was performed to determine the relationship between relaxation times and postmenstrual age (PMA) at scan. Analysis of covariance was used to evaluate the impact of severe postnatal morbidity in the high-risk group on T1 and T2 relaxation times. Receiver operating characteristic (ROC) curves were plotted and analysed with area under the ROC curve (AUC) to evaluate the accuracy of classifying high-risk patients based on regional relaxation times.

RESULTS

A linear age-related decrease of T1 and T2 relaxation times correlating with PMA at scan (between 37 and 42 weeks) was found in the deep gray matter, the cerebellum, the cortex, and the posterior limb of the internal capsule (PLIC) (p < .005 each), but not in the global, frontal, parietal, or central white matter. Analysis of covariance for both risk groups, adjusted for PMA, revealed significantly prolonged regional tissue relaxation times in neonates with severe postnatal morbidity, which was best illustrated in the central white matter of the centrum semiovale (T1 Δ = 11.5%, T2 Δ = 13.4%, p < .001) and in the PLIC (T1 Δ = 9.2%, T2 Δ = 6.9%, p < .001). The relaxation times in the PLIC and the central white matter predicted high-risk status with excellent accuracy (AUC range 0.82-0.86).

CONCLUSION

Synthetic MRI-based relaxometry in the brain of preterm born neonates is sensitive to age-related maturational changes close to TEA. Severe postnatal morbidity correlated with a significant delay in tissue relaxation. Synthetic MRI may provide early prognostic biomarkers for neurodevelopment impairment.