Advantages of Cell Proliferation and Immune Regulation in CD146+NESTIN+ HUMSCs: Insights from Single-Cell RNA Sequencing.

The heterogeneity of stem cells is a significant factor inhibiting their clinical application, as different cell subpopulations may exhibit substantial differences in biological functions. We performed single-cell sequencing on HUMSCs from three donors of different gestational ages (22 + 5 weeks, 28 weeks, 39 weeks). We also compared the data with single-cell sequencing data from BMSCs from two public databases. The content of CD146+Nestin+ MSCs in preterm HUMSCs (22 + 5W: 30.2%, 28W: 25.8%) was higher than that in full-term HUMSCs (39W: 0.5%) and BMSCs (BMSC1: 0, BMSC2: 0.9%). Cell cycle analysis indicated a higher proportion of cells in the proliferative G2M phase in CD146+Nestin+ MSCs (40.8%) compared to CD146+Nestin- MSCs (20%) and CD146-Nestin- MSCs (12.5%). Degree of differentiation assessment suggested that CD146+Nestin+ MSCs exhibited lower differentiation than other cell subpopulations. Differential gene analysis revealed that CD146+Nestin+ MSCs overexpressed immune regulation-related factors. GO and KEGG enrichment analysis of modules identified by WGCNA suggested enrichment in pathways related to cellular immune regulation, antimicrobial activity, and proliferation. Immune-related gene analysis indicated that CD146+Nestin+ MSCs exhibited expression of multiple immune-related genes associated with "Antimicrobials," "Cytokines," and "Cytokine Receptors." Gene regulatory network analysis revealed high expression of immune-related regulators RELB, GAPB1, and EHF in CD146+Nestin+ MSCs.Our study provides a single-cell atlas of preterm HUMSCs, demonstrating the expression of CD146+Nestin+ MSCs across different tissues and confirming their advantages in cellular proliferation, antimicrobial activity, immune regulation, and low differentiation at the RNA level. This contributes valuable insights for the clinical application of HUMSCs.

Metabolic and Microbial Dysregulation in Preterm Infants with Neonatal Respiratory Distress Syndrome: An Early Developmental Perspective.

Neonatal respiratory distress syndrome (NRDS) is one of the most severe respiratory disorders in preterm infants (PTIs) due to immature lung development. To delineate the serum metabolic alterations and gut microbiota variations in NRDS and assess their implications on neonatal development, we enrolled 13 NRDS neonates and 12 PTIs and collected fecal and serum specimens after birth. Longitudinal fecal sampling was conducted weekly for a month in NRDS neonates. NRDS neonates were characterized by notably reduced gestational ages and birth weights and a higher rate of asphyxia at birth relative to PTIs. Early postnatal disturbances in tryptophan metabolism were evident in the NRDS group, concomitant with elevated relative abundance of Haemophilus, Fusicatenibacter, and Vibrio. Integrative multiomics analyses revealed an inverse relationship between tryptophan concentrations and Blautia abundance. At one-week old, NRDS neonates exhibited cortisol regulation anomalies and augmented hepatic catabolism. Sequential microbial profiling revealed distinct gut microbiota evolution in NRDS subjects, characterized by a general reduction in potentially pathogenic bacteria. The acute perinatal stress of NRDS leads to mitochondrial compromise, hormonal imbalance, and delayed gut microbiota evolution. Despite the short duration of NRDS, its impact on neonatal development is significant and requires extended attention.

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

Pain/Stress, Mitochondrial Dysfunction, and Neurodevelopment in Preterm Infants.

INTRODUCTION: Preterm infants experience tremendous early life pain/stress during their neonatal intensive care unit (NICU) hospitalization, which impacts their neurodevelopmental outcomes. Mitochondrial function/dysfunction may interface between perinatal stress events and neurodevelopment. Nevertheless, the specific proteins or pathways linking mitochondrial functions to pain-induced neurodevelopmental outcomes in infants remain unidentified. Our study aims to investigate the associations among pain/stress, proteins associated with mitochondrial function/dysfunction, and neurobehavioral responses in preterm infants. METHODS: We conducted a prospective cohort study, enrolling 33 preterm infants between September 2017 and July 2022 at two affiliated NICUs located in Hartford and Farmington, CT. NICU Network Neurobehavioral Scale (NNNS) datasets were evaluated to explore potential association with neurobehavioral outcomes. The daily pain/stress experienced by infant's during their NICU stay was documented. At 36-38 weeks post-menstrual age (PMA), neurobehavioral outcomes were evaluated using the NNNS and buccal swabs were collected for further analysis. Mass spectrometry-based proteomics was conducted on epithelial cells obtained from buccal swabs to evaluate protein expression level. Lasso statistical methods were conducted to study the association between protein abundance and infants' NNNS summary scores. Multiple linear regression and Gene Ontology (GO) enrichment analyses were performed to examine how clinical characteristics and neurodevelopmental outcomes may be associated with protein levels and underlying molecular pathways. RESULTS: During NICU hospitalization, preterm premature rupture of membrane (PPROM) was negatively associated with neurobehavioral outcomes. The protein functions including leptin receptor binding activity, glutathione disulfide oxidoreductase activity and response to oxidative stress, lipid metabolism, and phosphate and proton transmembrane transporter activity were negatively associated with neurobehavioral outcomes; in contrast, cytoskeletal regulation, epithelial barrier, and protection function were found to be associated with the optimal neurodevelopmental outcomes. In addition, mitochondrial function-associated proteins including SPRR2A, PAIP1, S100A3, MT-CO2, PiC, GLRX, PHB2, and BNIPL-2 demonstrated positive association with favorable neurodevelopmental outcomes, while proteins of ABLIM1, UNC45A, keratins, MUC1, and CYB5B showed positive association with adverse neurodevelopmental outcomes. CONCLUSION: Mitochondrial function-related proteins were observed to be associated with early life pain/stress and neurodevelopmental outcomes in infants. Large-scale studies with longitudinal datasets are warranted. Buccal proteins could be used to predict potential neurobehavioral outcomes.

Clinical Decision Support for Improved Neonatal Care: The Development of a Machine Learning Model for the Prediction of Late-onset Sepsis and Necrotizing Enterocolitis.

OBJECTIVE: To develop an artificial intelligence-based software system for predicting late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in infants admitted to the neonatal intensive care unit (NICU). STUDY DESIGN: Single-center, retrospective cohort study, conducted in the NICU of the Antwerp University Hospital. Continuous monitoring data of 865 preterm infants born at <32 weeks gestational age, admitted to the NICU in the first week of life, were used to train an XGBoost machine learning (ML) algorithm for LOS and NEC prediction in a cross-validated setup. Afterward, the model's performance was assessed on an independent test set of 148 patients (internal validation). RESULTS: The ML model delivered hourly risk predictions with an overall sensitivity of 69% (142/206) for all LOS/NEC episodes and 81% (67/83) for severe LOS/NEC episodes. The model showed a median time gain of ≤10 hours (IQR, 3.1-21.0 hours), compared with historical clinical diagnosis. On the complete retrospective dataset, the ML model made 721 069 predictions, of which 9805 (1.3%) depicted a LOS/NEC probability of ≥0.15, resulting in a total alarm rate of <1 patient alarm-day per week. The model reached a similar performance on the internal validation set. CONCLUSIONS: Artificial intelligence technology can assist clinicians in the early detection of LOS and NEC in the NICU, which potentially can result in clinical and socioeconomic benefits. Additional studies are required to quantify further the effect of combining artificial and human intelligence on patient outcomes in the NICU.

Hypertensive Disorders of Pregnancy and Risk of Early Brain Abnormalities on Magnetic Resonance Imaging at Term among Infants Born at ≤32 Weeks' Gestational Age.

OBJECTIVE: To evaluate the proximal effects of hypertensive disorders of pregnancy (HDP) on a validated measure of brain abnormalities in infants born at ≤32 weeks' gestational age (GA) using magnetic resonance imaging at term-equivalent age. STUDY DESIGN: In a multisite prospective cohort study, 395 infants born at ≤32 weeks' GA, underwent 3T magnetic resonance imaging scan between 39 and 44 weeks' postmenstrual age. A single neuroradiologist, blinded to clinical history, evaluated the standardized Kidokoro global brain abnormality score as the primary outcome. We classified infants as HDP-exposed by maternal diagnosis of chronic hypertension, gestational hypertension, pre-eclampsia, or eclampsia. Linear regression analysis identified the independent effects of HDP on infant brain abnormalities, adjusting for histologic chorioamnionitis, maternal smoking, antenatal steroids, magnesium sulfate, and infant sex. Mediation analyses quantified the indirect effect of HDP mediated via impaired intrauterine growth and prematurity and remaining direct effects on brain abnormalities. RESULTS: A total of 170/395 infants (43%) were HDP-exposed. Adjusted multivariable analyses revealed HDP-exposed infants had 27% (95% CI 5%-53%) higher brain abnormality scores than those without HDP exposure (P = .02), primarily driven by increased white matter injury/abnormality scores (P = .01). Mediation analyses showed HDP-induced impaired intrauterine growth significantly (P = .02) contributed to brain abnormality scores (22% of the total effect). CONCLUSIONS: Maternal hypertension independently increased the risk for early brain injury and/or maturational delays in infants born at ≤32 weeks' GA with an indirect effect of 22% resulting from impaired intrauterine growth. Enhanced prevention/treatment of maternal hypertension may mitigate the risk of infant brain abnormalities and potential neurodevelopmental impairments.

Predicting Extubation Readiness in Preterm Infants Utilizing Machine Learning: A Diagnostic Utility Study.

OBJECTIVE: The objective of this study was to predict extubation readiness in preterm infants using machine learning analysis of bedside pulse oximeter and ventilator data. STUDY DESIGN: This is an observational study with prospective recordings of oxygen saturation (SpO2) and ventilator data from infants <30 weeks of gestation age. Research pulse oximeters collected SpO2 (1 Hz sampling rate) to quantify intermittent hypoxemia (IH). Continuous ventilator metrics were collected (4-5-minute sampling) from bedside ventilators. Data modeling was completed using unbiased machine learning algorithms. Three model sets were created using the following data source combinations: (1) IH and ventilator (IH + SIMV), (2) IH, and (3) ventilator (SIMV). Infants were also analyzed separated by postnatal age (infants <2 or ≥2 weeks of age). Models were compared by area under the receiver operating characteristic curve (AUC). RESULTS: A total of 110 extubation events from 110 preterm infants were analyzed. Infants had a median gestation age and birth weight of 26 weeks and 825 g, respectively. Of the 3 models presented, the IH + SIMV model achieved the highest AUC of 0.77 for all infants. Separating infants by postnatal age increased accuracy further achieving AUC of 0.94 for <2 weeks of age group and AUC of 0.83 for ≥2 weeks group. CONCLUSIONS: Machine learning analysis has the potential to enhance prediction accuracy of extubation readiness in preterm infants while utilizing readily available data streams from bedside pulse oximeters and ventilators.

Gut microbial network signatures of early colonizers in preterm neonates with extrauterine growth restriction.

BACKGROUND: Extrauterine growth restriction (EUGR) represents a prevalent condition observed in preterm neonates, which poses potential adverse implications for both neonatal development and long-term health outcomes. The manifestation of EUGR has been intricately associated with perturbations in microbial and metabolic profiles. This study aimed to investigate the characteristics of the gut microbial network in early colonizers among preterm neonates with EUGR. METHODS: Twenty-nine preterm infants participated in this study, comprising 14 subjects in the EUGR group and 15 in the normal growth (AGA) group. Meconium (D1) and fecal samples were collected at postnatal day 28 (D28) and 1 month after discharge (M1). Subsequently, total bacterial DNA was extracted and sequenced using the Illumina MiSeq system, targeting the V3-V4 hyper-variable regions of the 16S rRNA gene. RESULTS: The outcomes of principal coordinates analysis (PCoA) and examination of the microbial network structure revealed distinctive developmental trajectories in the gut microbiome during the initial three months of life among preterm neonates with and without EUGR. Significant differences in microbial community were observed at the D1 (P = 0.039) and M1 phases (P = 0.036) between the EUGR and AGA groups, while a comparable microbial community was noted at the D28 phase (P = 0.414). Moreover, relative to the AGA group, the EUGR group exhibited significantly lower relative abundances of bacteria associated with secretion of short-chain fatty acids, including Lactobacillus (P = 0.041) and Parabacteroides (P = 0.033) at the D1 phase, Bifidobacterium at the D28 phase, and genera Dysgonomonas (P = 0.042), Dialister (P = 0.02), Dorea (P = 0.042), and Fusobacterium (P = 0.017) at the M1 phase. CONCLUSION: Overall, the present findings offer crucial important insights into the distinctive gut microbial signatures exhibited by earlier colonizers in preterm neonates with EUGR. Further mechanistic studies are needed to establish whether these differences are the cause or a consequence of EUGR.

Reinitiating lung development: a novel approach in the management of bronchopulmonary dysplasia.

Bronchopulmonary dysplasia (BPD) is the predominant chronic lung disease in preterm infants, linked with various adverse long-term outcomes. Multiple prenatal and postnatal risk factors can impede lung development, leading to BPD. Current management of BPD relies heavily on pharmacotherapies and alterations in ventilatory strategies. However, these interventions only mitigate BPD symptoms without addressing underlying alveolar, vascular, structural, and functional deficiencies. Given the retarded lung development in infants with BPD and the limitations of existing modalities, new therapeutic approaches are imperative. The induced differentiation of stem/progenitor cells and the spatiotemporal expression patterns of growth factors associated with lung developmental processes are critical for lung development reactivation in BPD, which focuses on stimulating pulmonary vasculogenesis and alveolarization. This review summarizes the process of lung development and offers a comprehensive overview of advancements in therapies designed to reinitiate lung development in BPD. Furthermore, we assessed the potential of these therapies for maintaining lung homeostasis and effectively restoring pulmonary structure and function through stem/progenitor cells and growth factors, which have been widely researched.

Preterm Birth Alters the Regional Development and Structural Covariance of Cerebellum at Term-Equivalent Age.

Preterm birth is associated with increased risk for a spectrum of neurodevelopmental disabilities. The cerebellum is implicated in a wide range of cognitive functions extending beyond sensorimotor control and plays an increasingly recognized role in brain development. Morphometric studies based on volume analyses have revealed impaired cerebellar development in preterm infants. However, the structural covariance between the cerebellum and cerebral cortex has not been studied during the neonatal period, and the extent to which structural covariance is affected by preterm birth remains unknown. In this study, using the structural MR images of 52 preterm infants scanned at term-equivalent age and 312 full-term controls from the Developing Human Connectome Project, we compared volumetric growth, local cerebellum shape development and cerebello-cerebral structural covariance between the two groups. We found that although there was no significant difference in the overall volume measurements between preterm and full-term infants, the shape measurements were different. Compared with the control infants, preterm infants had significantly larger thickness in the vermis and lower thickness in the lateral portions of the bilateral cerebral hemispheres. The structural covariance between the cerebellum and frontal and parietal lobes was significantly greater in preterm infants than in full-term controls. The findings in this study suggested that cerebellar development and cerebello-cerebral structural covariance may be affected by premature birth.

One-year anthropometric follow-up of South African preterm infants in kangaroo mother care: Which early-life factors predict malnutrition?

BACKGROUND: Preterm infants often have poor short- and long-term growth. Kangaroo mother care supports short-term growth, but longer-term outcomes are unclear. METHODS: This study analysed longitudinally collected routine clinical data from a South African cohort of preterm infants (born <37 weeks gestation) attending the outpatient follow-up clinic of a tertiary-level hospital (Tshwane District, South Africa) for 1 year between 2012 and 2019. At 1 year, small-for-gestational age (SGA) and appropriate-for-gestational age (AGA) infants were compared with regard to age-corrected anthropometric z-scores (weight-for-age [WAZ], length-for-age [LAZ], weight-for-length [WLZ] and BMI-for-age [BMIZ]) and rates of underweight (WAZ < -2), stunting (LAZ < -2), wasting (WLZ < -2) and overweight (BMIZ> + 2). Multiple regression analysis was used to investigate associations between maternal/infant characteristics and rates of underweight, stunting, wasting and overweight. RESULTS: At 1 year, compared with AGA infants (n = 210), SGA infants (n = 111) had lower WAZ (-1.26 ± 1.32 vs. -0.22 ± 1.24, p < 0.001), LAZ (-1.50 ± 1.11 vs. -0.60 ± 1.06, p < 0.001), WLZ (-0.66 ± 1.31 vs. 0.11 ± 1.24, p < 0.001) and BMIZ (-0.55 ± 1.31 vs. 1.06 ± 1.23, p < 0.001), despite larger WAZ gains from birth (+0.70 ± 1.30 vs. +0.05 ± 1.30, p < 0.001). SGA infants had significantly more stunting (34.2% vs. 9.1%; p < 0.001), underweight (31.2% vs. 7.2%; p < 0.001) and wasting (12.6% vs. 4.3%, p = 0.012), with no difference in overweight (4.5% vs. 7.7%, p = 0.397). In multiple regression analysis, birth weight-for-GA z-score more consistently predicted 1-year malnutrition than SGA. CONCLUSION: Preterm-born SGA infants remain more underweight, stunted and wasted than their preterm-born AGA peers at 1 year, despite greater WAZ gains. Interventions for appropriate catch-up growth especially for SGA preterm infants are needed.

Short apneas and periodic breathing in preterm infants in the neonatal intensive care unit-Effects of sleep position, sleep state, and age.

This observational study investigated the effects of sleep position and sleep state on short apneas and periodic breathing in hospitalized preterm infants longitudinally, in relation to postmenstrual age. Preterm infants (25-31 weeks gestation, n = 29) were studied fortnightly after birth until discharge, in prone and supine positions, and in quiet sleep and active sleep. The percentage of time spent in each sleep state (percentage of time in quiet sleep and percentage of time in active sleep), percentage of total sleep time spent in short apneas and periodic breathing, respectively, the percentage of falls from baseline in heart rate, arterial oxygen saturation and cerebral tissue oxygenation index during short apneas and periodic breathing, and the associated percentage of total sleep time with systemic (arterial oxygen saturation < 90%) and cerebral hypoxia (cerebral tissue oxygenation index < 55%) were analysed using a linear mixed model. Results showed that the prone position decreased (improved) the percentage of falls from baseline in arterial oxygen saturation during both short apneas and periodic breathing, decreased the proportion of infants with periodic breathing and the periodic breathing-associated percentage of total sleep time with cerebral hypoxia. The percentage of time in quiet sleep was higher in the prone position. Quiet sleep decreased the percentage of total sleep time spent in short apneas, the short apneas-associated percentage of falls from baseline in heart rate, arterial oxygen saturation, and proportion of infants with systemic hypoxia. Quiet sleep also decreased the proportion of infants with periodic breathing and percentage of total sleep time with cerebral hypoxia. The effects of sleep position and sleep state were not related to postmenstrual age. In summary, when sleep state is controlled for, the prone sleeping position has some benefits during both short apneas and periodic breathing. Quiet sleep improves cardiorespiratory stability and is increased in the prone position at the expense of active sleep, which is critical for brain maturation. This evidence should be considered in positioning preterm infants.

Lipid analysis of breast milk and formula for preterm infants and the application and prospects of novel structural lipids - a comprehensive review.

Preterm infants, often characterized by lower birth weights and underdeveloped physiologies, necessitate specialized nutritional care. While breast milk stands as the ideal nutritional source, offering substantial energy through its fatty acid content to support the infants' growth and developmental needs, its usage might not always be feasible. Fatty acids in breast milk are critical for the development of these infants. In scenarios where breast milk is not an option, formula feeding becomes a necessary alternative. Thus, a comprehensive understanding of the fatty acid profiles in both breast milk and formulas is crucial for addressing the distinct nutritional requirements of preterm infants. This paper aims to summarize the effects of lipid composition, structure, and positioning in breast milk and formula on the growth and development of preterm infants. Furthermore, it explores recent advancements in the use of novel structural lipids in formulas, laying the groundwork for future innovations in formula design specifically catered to the needs of preterm infants.

Characteristics of red blood cell transfusion among very preterm infants in China.

BACKGROUND AND OBJECTIVES: National-level data on the incidence of red blood cell (RBC) transfusions and outcomes among very preterm infants (VPIs) are lacking in China. This study aims to describe the use and variation of RBC transfusion among VPIs in China. MATERIALS AND METHODS: This cohort study was conducted among 70 tertiary hospitals participating in the Chinese Neonatal Network (CHNN) from 2019 to 2020 across China. All VPIs admitted to the CHNN neonatal intensive care units (NICUs) were included. RESULTS: A total of 13,447 VPIs were enrolled, of whom 7026 (52.2%) received ≥1 RBC transfusions. The mean number of transfusions per infant was 2 (interquartile range [IQR] 1-4 times) and the median age at first transfusion was 15 days (IQR 3-27 days). The transfusion rate was higher in critically ill infants compared with non-critically ill infants (70.5% vs. 39.3%). The transfusion rate varied widely (13.5%-95.0%) between different NICUs. The prevalence of death, severe intra-ventricular haemorrhage, necrotizing enterocolitis (NEC) or spontaneous intestinal perforation (SIP), sepsis, bronchopulmonary dysplasia (BPD), severe retinopathy of prematurity (ROP) and cystic periventricular leukomalacia (cPVL) was significantly higher in the transfused group. Among non-critically ill infants, RBC transfusion was independently associated with BPD, severe ROP and cPVL. CONCLUSION: Our study, providing the first baseline data on RBC transfusions among VPIs in China, shows an alarmingly high RBC transfusion rate with significant site variations. There is an urgent need for national guidelines on RBC transfusions for VPIs in China.

Can deep learning classify cerebral ultrasound images for the detection of brain injury in very preterm infants?

OBJECTIVES: Cerebral ultrasound (CUS) is the main imaging screening tool in preterm infants. The aim of this work is to develop deep learning (DL) models that classify normal vs abnormal CUS to serve as a computer-aided detection tool providing timely interpretation of the scans. METHODS: A population-based cohort of very preterm infants (220-306 weeks) born between 2004 and 2016 in Nova Scotia, Canada. A set of nine sequential CUS images per infant was retrieved at three specific coronal landmarks at three pre-identified times (first, sixth weeks, and term age). A radiologist manually labeled each image as normal or abnormal. The dataset was split into training/development/test subsets (80:10:10). Different convolutional neural networks were tested, with filtering of the most uncertain prediction. The model's performance was assessed using precision/recall and the receiver operating area under the curve. RESULTS: Sequential CUS retrieved for 538/665 babies (81% of the cohort). Four thousand one hundred eighty images were used to develop and test the model. The model performance was only discrete at the beginning but, through different machine learning strategies was boosted to good levels averaging 0.86 ROC AUC (95% CI: 0.82, 0.90) and 0.87 PR AUC (95% CI: 0.84, 0.90) (model uncertainty estimation filters using normalized entropy threshold = 0.5). CONCLUSION: This study offers proof of the feasibility of applying DL to CUS. This basic diagnostic model showed good discriminative ability to classify normal versus abnormal CUS. This serves as a CAD and a framework for constructing a prognostic model. CLINICAL RELEVANCE STATEMENT: This DL model can serve as a computer-aided detection tool to classify CUS of very preterm babies as either normal or abnormal. This model will also be used as a framework to develop a prognostic model. KEY POINTS: Binary computer-aided detection models of CUS are applicable for classifying ultrasound images in very preterm babies. This model acts as a step towards developing a model for predicting neurodevelopmental outcomes in very preterm babies. This model serves as a tool for interpretation of CUS in this patient population with a heightened risk of brain injury.

Incidence of brain injuries in a large cohort of very preterm and extremely preterm infants at term-equivalent age: results of a single tertiary neonatal care center over 10 years.

OBJECTIVES: Cerebral magnetic resonance imaging (cMRI) at term-equivalent age (TEA) can detect brain injury (BI) associated with adverse neurological outcomes in preterm infants. This study aimed to assess BI incidences in a large, consecutive cohort of preterm infants born < 32 weeks of gestation, the comparison between very (VPT, ≥ 28 + 0 to < 32 + 0 weeks of gestation) and extremely preterm infants (EPT, < 28 + 0 weeks of gestation) and across weeks of gestation. METHODS: We retrospectively analyzed cMRIs at TEA of VPT and EPT infants born at a large tertiary center (2009-2018). We recorded and compared the incidences of BI, severe BI, intraventricular hemorrhage (IVH), periventricular hemorrhagic infarction (PVHI), cerebellar hemorrhage (CBH), cystic periventricular leukomalacia (cPVL), and punctate white matter lesions (PWML) between VPTs, EPTs, and across weeks of gestation. RESULTS: We included 507 preterm infants (VPT, 335/507 (66.1%); EPT, 172/507 (33.9%); mean gestational age (GA), 28 + 2 weeks (SD 2 + 2 weeks); male, 52.1%). BIs were found in 48.3% of the preterm infants (severe BI, 12.0%) and increased with decreasing GA. IVH, PVHI, CBH, cPVL, and PWML were seen in 16.8%, 0.8%, 10.5%, 3.4%, and 18.1%, respectively. EPT vs. VPT infants suffered more frequently from BI (59.3% vs. 42.7%, p < 0.001), severe BI (18.6% vs. 8.7%, p = 0.001), IVH (31.9% vs. 9.0%, p < 0.001), and CBH (18.0% vs. 6.6%, p < 0.001). CONCLUSION: Brain injuries are common cMRI findings among preterm infants with a higher incidence of EPT compared to VPT infants. These results may serve as reference values for clinical management and research. CLINICAL RELEVANCE STATEMENT: Our results with regard to gestational age might provide valuable clinical insights, serving as a key reference for parental advice, structured follow-up planning, and enhancing research and management within the Neonatal Intensive Care Unit. KEY POINTS: • Brain injury is a common cMRI finding in preterm infants seen in 48.3% individuals. • Extremely preterm compared to very preterm infants have higher brain injury incidences driven by brain injuries such as intraventricular and cerebellar hemorrhage. • Reference incidence values are crucial for parental advice and structured follow-up planning.

Growth Trajectory at 24 Months of Preterm Infants after Discharge: A Longitudinal Study in Indonesia.

Maintaining optimal growth of preterm infants after hospital discharge remains a challenge. There has been no data on the long-term growth trajectory of preterm infants in Indonesia. We aimed to describe the growth trajectory of preterm infants up to 24 months of corrected age and its variation among gestational age groups. A longitudinal study was conducted in Cipto Mangunkusumo Hospital, Jakarta from 2018 to 2020. All preterm infants who were discharged during the study period were included. Growth trajectory analysis used weight-for-age (WAZ), length-for-age (LAZ), and weight-for-length (WFL) z-score of 3-month time intervals across gestational age groups using repeated measure ANOVA and generalized estimating equation regression. Length trajectory was specifically reported as a stunted proportion. Among 306 preterm infants included, most were moderate preterm (49.67%) and low birth weight (69.93%). Overall WAZ at 0 month were in the median of the curve, then decreased at 3 months, but consistently increased slowly until 24 months. The WAZ trends were unique across gestational age groups, but statistically similar (p = 0.263). The proportion of stunted gradually decreases to 13.40% at 24 months, mostly among the moderate preterm group in the first 6 months (p<0.001) but then becomes similar at 24 months. All subjects were in the normal range for WFL but had variations in trends across gestational age groups (p<0.001). Growth trajectory differed between weight, length, and weight-for-length in the first 24 months and varied among gestational age groups. Close follow-up is crucial to ensure optimal growth after NICU discharge.

Immunization status and factors influencing hepatitis B vaccination of preterm infants in three provinces of China, 2019 to 2021.

BACKGROUND: Premature infants have less physiologic reserve and often delayed vaccination compared to full-term infants. The birth dose of hepatitis B vaccine (HepB-BD) is an essential measure to achieve the goal of "zero infections" of hepatitis B virus in all newborns. However, there are few investigations of hepatitis B vaccination of preterm infants, leading to uncertainty of coverage and insufficient knowledge of factors influencing timely vaccination of this important population. METHODS: We obtained hepatitis B vaccine (HepB) vaccination histories of premature infants born during 2019-2021 in three provinces from the respective provincial immunization information systems. Extracted data included date of birth, sex, region, and dates of HepB administration. We conducted descriptive analyses that included basic characteristics of the study subjects, HepB-BD administration, and full-series HepB vaccination. Factors potentially influencing HepB-BD and full series vaccination were analyzed by logistic regression. RESULTS: There were 1623 premature infants included in the analytic data set. Overall HepB-BD coverage was 71.41%; coverage among premature infants born to mothers with unknown hepatitis B surface antigen (HBsAg) status was 69.57%; coverage was higher at county-level-and-above hospitals (72.02%) than hospitals below county level (61.11%). Full-series HepB coverage was 94.15%; full-series coverage among preterm infants weighing less than 2000 g at birth was 76.92%. Logistic regression showed that the HepB-BD vaccination rate was positively associated with being born to an HBsAg-positive mother and being preterm with high birth weight. Regression analysis for factors influencing full-series HepB coverage showed that being born prematurely was positively associated with full-series coverage and being premature with a very low birth weight was negatively associated with full-series coverage. CONCLUSIONS: HepB-BD coverage levels in three provinces of China were less than the target of 90%, especially among premature infants born to mothers with unknown HBsAg status and at hospitals below the county level. Screening of pregnant women should be a universal normal standard. Hepatitis B vaccination training should be strengthened in hospitals to improve the HepB-BD vaccination rate of premature infants and to effectively prevent mother-to-child transmission of hepatitis B virus.

Healthcare resource utilisation and costs in infants with confirmed respiratory syncytial virus infections: a national population cohort study.

BACKGROUND: Respiratory syncytial virus (RSV) is the leading cause of severe respiratory infections in infants worldwide, significantly affecting their health and contributing to the global healthcare burden. We aimed to examine healthcare resource utilisation patterns and costs for infants under one year old with confirmed RSV infection across subgroups of different gestational ages and health conditions and the cost implications of RSV infections over time, thereby demonstrating the economic burden of the disease. METHODS: This retrospective cohort study utilised nationwide claims data from the Korea Health Insurance Review and Assessment Service for infants under one year of age with confirmed RSV infection in the first year of life from January 2017 to April 2022. The infants were stratified into three subgroups based on their gestational age and health status: unhealthy preterm, healthy preterm, and full-term infants. A descriptive analysis was conducted to estimate healthcare utilization by type of resource and costs related to the treatment of RSV. RESULTS: Out of 93,585 RSV infections identified, 31,206 patients met the inclusion criteria; these included 963 unhealthy preterm, 1,768 healthy preterm and 28,475 full-term infants. In our study, 76.3% of the infants with confirmed RSV infection required intensive care, including hospitalisation and more critical interventions such as intensive care unit (ICU) or mechanical ventilation (MV). The total average cost of RSV management was notably higher for unhealthy preterm infants ($ 6,325; 95% confidence interval (CI): $ 5,484-7,165) than for healthy preterm ($ 1,134; 95% CI: $ 1,006 - 1,261) and full-term infants ($ 606; 95% CI: 583-630). Our findings confirmed a significant epidemiological and economic burden, with infants at greater risk-shorter gestational age and poorer health conditions. Furthermore, we observed a marked increase in the total average cost of RSV management during COVID-19, reflecting the complex interplay between RSV and pandemic-related healthcare dynamics. CONCLUSION: Our findings provide evidence for the significant economic burden of RSV infection among infants, with considerable disparities based on gestational age and health status subgroups. However, RSV prevention policies should also recognise that healthy preterm or full-term infants who receive intensive care face a significant disease burden.

From "wet" matrices to "dry" blood spot sampling strategy: a versatile LC-MS/MS assay for simultaneous monitoring caffeine and its three primary metabolites in preterm infants.

OBJECTIVES: To update traditional "wet" matrices to dried blood spot (DBS) sampling, based on the liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) technique, and develop a method for simultaneous analyzing caffeine and its three primary metabolites (theobromine, paraxanthine, and theophylline), supporting routine therapeutic drug monitoring (TDM) for preterm infants. METHODS: DBS samples were prepared by a two-step quantitative sampling method, i.e., volumetric sampling of a quantitative 10 µL volume of peripheral blood and an 8 mm diameter whole punch extraction by a methanol/water (80/20, v/v) mixture containing 125 mM formic acid. Four paired stable isotope labeled internal standards and a collision energy defect strategy were applied for the method optimization. The method was fully validated following international guidelines and industrial recommendations on DBS analysis. Cross validation with previously developed plasma method was also proceeded. The validated method was then implemented on the TDM for preterm infants. RESULTS: The two-step quantitative sampling strategy and a high recovery extraction method were developed and optimized. The method validation results were all within the acceptable criteria. Satisfactory parallelism, concordance, and correlation were observed between DBS and plasma concentrations of the four analytes. The method was applied to provide routine TDM services to 20 preterm infants. CONCLUSIONS: A versatile LC-MS/MS platform for simultaneous monitoring caffeine and its three primary metabolites was developed, fully validated, and successfully applied into the routine clinical TDM practices. Sampling method switching from "wet" matrices to "dry" DBS will facilitate and support the precision dosing of caffeine for preterm infants.