Morbidity and trends in length of hospitalisation of very and extremely preterm infants born between 2008 and 2021 in the Netherlands:a cohort study

OBJECTIVES: This study investigated changes in the length of stay (LoS) at a level III/IV neonatal intensive care unit (NICU) and level II neonatology departments until discharge home for very preterm infants and identified factors influencing these trends. DESIGN: Retrospective cohort study based on data recorded in the Netherlands Perinatal Registry between 2008 and 2021. SETTING: A single level III/IV NICU and multiple level II neonatology departments in the Netherlands. PARTICIPANTS: NICU-admitted infants (n=2646) with a gestational age (GA) &lt;32 weeks. MAIN OUTCOME MEASURES: LoS at the NICU and overall LoS until discharge home. RESULTS: The results showed an increase of 5.1 days (95% CI 2.2 to 8, p&lt;0.001) in overall LoS in period 3 after accounting for confounding variables. This increase was primarily driven by extended LoS at level II hospitals, while LoS at the NICU remained stable. The study also indicated a strong association between severe complications of preterm birth and LoS. Treatment of infants with a lower GA and more (severe) complications (such as severe retinopathy of prematurity) during the more recent periods may have increased LoS. CONCLUSION: The findings of this study highlight the increasing overall LoS for very preterm infants. LoS of very preterm infants is presumably influenced by the occurrence of complications of preterm birth, which are more frequent in infants at a lower gestational age.</p

Morbidity and trends in length of hospitalisation of very and extremely preterm infants born between 2008 and 2021 in the Netherlands:a cohort study

OBJECTIVES: This study investigated changes in the length of stay (LoS) at a level III/IV neonatal intensive care unit (NICU) and level II neonatology departments until discharge home for very preterm infants and identified factors influencing these trends. DESIGN: Retrospective cohort study based on data recorded in the Netherlands Perinatal Registry between 2008 and 2021. SETTING: A single level III/IV NICU and multiple level II neonatology departments in the Netherlands. PARTICIPANTS: NICU-admitted infants (n=2646) with a gestational age (GA) &lt;32 weeks. MAIN OUTCOME MEASURES: LoS at the NICU and overall LoS until discharge home. RESULTS: The results showed an increase of 5.1 days (95% CI 2.2 to 8, p&lt;0.001) in overall LoS in period 3 after accounting for confounding variables. This increase was primarily driven by extended LoS at level II hospitals, while LoS at the NICU remained stable. The study also indicated a strong association between severe complications of preterm birth and LoS. Treatment of infants with a lower GA and more (severe) complications (such as severe retinopathy of prematurity) during the more recent periods may have increased LoS. CONCLUSION: The findings of this study highlight the increasing overall LoS for very preterm infants. LoS of very preterm infants is presumably influenced by the occurrence of complications of preterm birth, which are more frequent in infants at a lower gestational age.</p

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

Morbidity and trends in length of hospitalisation of very and extremely preterm infants born between 2008 and 2021 in the Netherlands: A cohort study

Objectives This study investigated changes in the length of stay (LoS) at a level III/IV neonatal intensive care unit (NICU) and level II neonatology departments until discharge home for very preterm infants and identified factors influencing these trends. Design Retrospective cohort study based on data recorded in the Netherlands Perinatal Registry between 2008 and 2021. Setting A single level III/IV NICU and multiple level II neonatology departments in the Netherlands. Participants NICU-admitted infants (n=2646) with a gestational age (GA) <32 weeks. Main outcome measures LoS at the NICU and overall LoS until discharge home. Results The results showed an increase of 5.1 days (95% CI 2.2 to 8, p<0.001) in overall LoS in period 3 after accounting for confounding variables. This increase was primarily driven by extended LoS at level II hospitals, while LoS at the NICU remained stable. The study also indicated a strong association between severe complications of preterm birth and LoS. Treatment of infants with a lower GA and more (severe) complications (such as severe retinopathy of prematurity) during the more recent periods may have increased LoS. Conclusion The findings of this study highlight the increasing overall LoS for very preterm infants. LoS of very preterm infants is presumably influenced by the occurrence of complications of preterm birth, which are more frequent in infants at a lower gestational age

Nurses’ experiences and perspectives on aEEG monitoring in neonatal care: A qualitative study

Purpose: This study aimed to gather nurses’ experiences and perspectives regarding the amplitude-integrated electroencephalogram (aEEG) monitoring system in neonatal intensive care units (NICUs) and to explore potential avenues for future improvements. Design and Methods: This study employed a descriptive qualitative design. Semi-structured interviews were conducted with 20 nurses from the level-III NICU of a Dutch medical center. The collected interview data were analyzed using thematic analysis. Results: Seven main themes emerged: training in aEEG monitoring, proficiency in aEEG electrode placement and pattern interpretation, usual practices of using aEEG, neonatologist-nurse cooperation on aEEG, the performance of the automated seizure detection software, the usefulness of aEEG monitoring in the NICU, and feedback about the current aEEG monitoring system. Conclusions: Nurses confirmed that aEEG is a valuable tool for cerebral function monitoring in the NICU; however, improvements are necessary. For better utilization of aEEG in the NICU, it is recommended to enhance nurses’ aEEG knowledge and skills and apply state-of-art techniques to improve the monitoring system. Practice implications: To enhance the aEEG knowledge of NICU nurses, we suggest introducing structured training programs, conducting routine case-centered discussions, and creating readily available reference resources. To optimize the aEEG monitoring system, it is essential to incorporate innovative electrodes, provide remote accessibility, integrate advanced algorithms, and develop an intuitive graphical user interface

Unobtrusive cot side sleep stage classification in preterm infants using ultra-wideband radar

Background: Sleep is an important driver of development in infants born preterm. However, continuous unobtrusive sleep monitoring of infants in the neonatal intensive care unit (NICU) is challenging.Objective: To assess the feasibility of ultra-wideband (UWB) radar for sleep stage classification in preterm infants admitted to the NICU.Methods: Active and quiet sleep were visually assessed using video recordings in 10 preterm infants (recorded between 29 and 34 weeks of postmenstrual age) admitted to the NICU. UWB radar recorded all infant's motions during the video recordings. From the baseband data measured with the UWB radar, a total of 48 features were calculated. All features were related to body and breathing movements. Six machine learning classifiers were compared regarding their ability to reliably classify active and quiet sleep using these raw signals.Results: The adaptive boosting (AdaBoost) classifier achieved the highest balanced accuracy (81%) over a 10-fold cross-validation, with an area under the curve of receiver operating characteristics (AUC-ROC) of 0.82.Conclusions: The UWB radar data, using the AdaBoost classifier, is a promising method for non-obtrusive sleep stage assessment in very preterm infants admitted to the NICU

The impact of trophic and immunomodulatory factors on oligodendrocyte maturation: Potential treatments for encephalopathy of prematurity

Encephalopathy of prematurity (EoP) is a major cause of morbidity in preterm neonates, causing neurodevelopmental adversities that can lead to lifelong impairments. Preterm birth-related insults, such as cerebral oxygen fluctuations and perinatal inflammation, are believed to negatively impact brain development, leading to a range of brain abnormalities. Diffuse white matter injury is a major hallmark of EoP and characterized by widespread hypomyelination, the result of disturbances in oligodendrocyte lineage development. At present, there are no treatment options available, despite the enormous burden of EoP on patients, their families, and society. Over the years, research in the field of neonatal brain injury and other white matter pathologies has led to the identification of several promising trophic factors and cytokines that contribute to the survival and maturation of oligodendrocytes, and/or dampening neuroinflammation. In this review, we discuss the current literature on selected factors and their therapeutic potential to combat EoP, covering a wide range of in vitro, preclinical and clinical studies. Furthermore, we offer a future perspective on the translatability of these factors into clinical practice

Detecting Asymmetry of Upper Limb Activity with Accelerometry in Infants at Risk for Unilateral Spastic Cerebral Palsy

Aims: To examine whether accelerometry can quantitate asymmetry of upper limb activity in infants aged 3–12 months at risk for developing unilateral spastic cerebral palsy (USCP). Method: A prospective study was performed in 50 infants with unilateral perinatal brain injury at high risk of developing USCP. Triaxial accelerometers were worn on the ipsilateral and contralesional upper limb during the Hand Assessment for Infants (HAI). Infants were grouped in three age intervals (3–5 months, 5–7.5 months and 7.5 until 12 months). Each age interval group was divided in a group with and without asymmetrical hand function based on HAI cutoff values suggestive of USCP. Results: In a total of 82 assessments, the asymmetry index for mean upper limb activity was higher in infants with asymmetrical hand function compared to infants with symmetrical hand function in all three age groups (ranging from 41 to 51% versus − 2–6%, p < 0.01), while the total activity of both upper limbs did not differ. Conclusions: Upper limb accelerometry can identify asymmetrical hand function in the upper limbs in infants with unilateral perinatal brain injury from 3 months onwards and is complementary to the Hand Assessment for Infants

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)

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