The performance of the practices associated with the occurrence of severe intraventricular hemorrhage in the very premature infants: data analysis from the Chinese neonatal network.

BACKGROUND: The occurrence of severe intraventricular hemorrhage (sIVH) was high in the very preterm infants (VPIs) in China. The management strategies significantly contributed to the occurrence of sIVH in VPIs. However, the status of the perinatal strategies associated with sIVH for VPIs was rarely described across the multiple neonatal intensive care units (NICUs) in China. We aim to investigate the characteristics of the perinatal strategies associated with sIVH for VPIs across the multiple NICUs in China. METHODS: This was a retrospective analysis of data from a prospective cohort of Chinese Neonatal Network (CHNN) dataset, enrolling infants born at 24+0-31+6 from 2019 to 2021. Eleven perinatal practices performed within the first 3 days of life were investigated including antenatal corticosteroids use, antenatal magnesium sulphate therapy, intubation at birth, placental transfusion, need for advanced resuscitation, initial inhaled gas of 100% FiO2 in delivery room, initial invasive respiratory support, surfactant and caffeine administration, early enteral feeding, and inotropes use. The performances of these practices across the multiple NICUs were investigated using the standard deviations of differences between expected probabilities and observations. The occurrence of sIVH were compared among the NICUs. RESULTS: A total of 24,226 infants from 55 NICUs with a mean (SD) gestational age of 29.5 (1.76) and mean (SD) birthweight of 1.31(0.32) were included. sIVH was detected in 5.1% of VPIs. The rate of the antenatal corticosteroids, MgSO4 therapy, and caffeine was 80.0%, 56.4%, and 31.5%, respectively. We observed significant relationships between sIVH and intubation at birth (AOR 1.52, 95% CI 1.13 to 1.75) and initial invasive respiratory support (AOR 2.47, 95% CI 2.15 to 2.83). The lower occurrence of sIVH (4.8%) was observed corresponding with the highest utility of standard antenatal care, the lowest utility of invasive practices, and early enteral feeding administration. CONCLUSIONS: The current evidence-based practices were not performed in each VPI as expected among the studied Chinese NICUs. The higher utility of the invasive practices could be related to the occurrence of sIVH.

Neurosonography: Shaping the future of neuroprotection strategies in extremely preterm infants.

This review aims to explore the current application of Cranial Ultrasound Screening (CUS) in the diagnosis and treatment of brain diseases in extremely preterm infants. It also discusses the potential role of emerging ultrasound-derived technologies such as Super Microvascular Structure Imaging (SMI), Shear Wave Elastography (SWE), Ultrafast Doppler Ultrasound (UfD), and 3D ventricular volume assessment and automated segmentation techniques in clinical practice. A systematic search of medical databases was conducted using the keywords "(preterm OR extremely preterm OR extremely low birth weight) AND (ultrasound OR ultrasound imaging) AND (neurodevelopment OR brain development OR brain diseases OR brain injury OR neuro*)" to identify relevant literature. The titles, abstracts, and full texts of the identified articles were carefully reviewed to determine their relevance to the research topic. CUS offers unique advantages in early screening and monitoring of brain diseases in extremely preterm infants, as it can be performed at the bedside without the need for anesthesia or special monitoring. This technique facilitates early detection and intervention of conditions such as intraventricular hemorrhage, white matter injury, hydrocephalus, and hypoxic-ischemic injury in critically ill preterm infants. Continuous refinement of the screening and follow-up processes provides reliable clinical decision-making support for healthcare professionals and parents. Emerging ultrasound technologies, such as SWE, SMI, and UfD, are being explored to provide more accurate and in-depth understanding of brain diseases in extremely preterm infants. SWE has demonstrated its effectiveness in assessing the elasticity of neonatal brain tissue, aiding in the localization and quantification of potential brain injuries. SMI can successfully identify microvascular structures in the brain, offering a new perspective on neurologic diseases. UfD provides a high-sensitivity and quantitative imaging method for the prevention and treatment of neonatal brain diseases by detecting subtle changes in red blood cell movement and accurately assessing the status and progression of brain diseases. CUS and its emerging technologies have significant applications in the diagnosis and treatment of brain diseases in extremely preterm infants. Future research aims to address current technical challenges, optimize and enhance the clinical decision-making capabilities related to brain development, and improve the prevention and treatment outcomes of brain diseases in extremely preterm infants.

Early Antibiotic Exposure and Bronchopulmonary Dysplasia in Very Preterm Infants at Low Risk of Early-Onset Sepsis.

Importance: The overutilization of antibiotics in very preterm infants (VPIs) at low risk of early-onset sepsis (EOS) is associated with increased mortality and morbidities. Nevertheless, the association of early antibiotic exposure with bronchopulmonary dysplasia (BPD) remains equivocal. Objective: To evaluate the association of varying durations and types of early antibiotic exposure with the incidence of BPD in VPIs at low risk of EOS. Design, Setting, and Participants: This national multicenter cohort study utilized data from the Chinese Neonatal Network (CHNN) which prospectively collected data from January 1, 2019, to December 31, 2021. VPIs less than 32 weeks' gestational age or with birth weight less than 1500 g at low risk of EOS, defined as those born via cesarean delivery, without labor or rupture of membranes, and no clinical evidence of chorioamnionitis, were included. Data analysis was conducted from October 2022 to December 2023. Exposure: Early antibiotic exposure was defined as the total number of calendar days antibiotics were administered within the first week of life, which were further categorized as no exposure, 1 to 4 days of exposure, and 5 to 7 days of exposure. Main Outcomes and Measures: The primary outcome was the composite of moderate to severe BPD or mortality at 36 weeks' post menstrual age (PMA). Logistic regression was employed to assess factors associated with BPD or mortality using 2 different models. Results: Of the 27 176 VPIs included in the CHNN during the study period (14 874 male [54.7%] and 12 302 female [45.3%]), 6510 (23.9%; 3373 male [51.8%] and 3137 female [48.2.%]) were categorized as low risk for EOS. Among them, 1324 (20.3%) had no antibiotic exposure, 1134 (17.4%) received 1 to 4 days of antibiotics treatment, and 4052 (62.2%) received 5 to 7 days of antibiotics treatment. Of the 5186 VPIs who received antibiotics, 4098 (79.0%) received broad-spectrum antibiotics, 888 (17.1%) received narrow-spectrum antibiotics, and 200 (3.9%) received antifungals or other antibiotics. Prolonged exposure (5-7 days) was associated with increased likelihood of moderate to severe BPD or death (adjusted odds ratio [aOR], 1.23; 95% CI, 1.01-1.50). The use of broad-spectrum antibiotics (1-7 days) was also associated with a higher risk of moderate to severe BPD or death (aOR, 1.27; 95% CI, 1.04-1.55). Conclusions and Relevance: In this cohort study of VPIs at low risk for EOS, exposure to prolonged or broad-spectrum antibiotics was associated with increased risk of developing moderate to severe BPD or mortality. These findings suggest that VPIs exposed to prolonged or broad-spectrum antibiotics early in life should be monitored for adverse outcomes.

Seizure Detection Based on Lightweight Inverted Residual Attention Network.

Timely and accurately seizure detection is of great importance for the diagnosis and treatment of epilepsy patients. Existing seizure detection models are often complex and time-consuming, highlighting the urgent need for lightweight seizure detection. Additionally, existing methods often neglect the key characteristic channels and spatial regions of electroencephalography (EEG) signals. To solve these issues, we propose a lightweight EEG-based seizure detection model named lightweight inverted residual attention network (LRAN). Specifically, we employ a four-stage inverted residual mobile block (iRMB) to effectively extract the hierarchical features from EEG. The convolutional block attention module (CBAM) is introduced to make the model focus on important feature channels and spatial information, thereby enhancing the discrimination of the learned features. Finally, convolution operations are used to capture local information and spatial relationships between features. We conduct intra-subject and inter-subject experiments on a publicly available dataset. Intra-subject experiments obtain 99.25% accuracy in segment-based detection and 0.36/h false detection rate (FDR) in event-based detection, respectively. Inter-subject experiments obtain 84.32% accuracy. Both sets of experiments maintain high classification accuracy with a low number of parameters, where the multiply accumulate operations (MACs) are 25.86[Formula: see text]M and the number of parameters is 0.57[Formula: see text]M.

Adsorption and activation of small molecules on boron nitride catalysts.

Hexagonal boron nitride possesses a unique layered structure, high specific surface area and similar electronic properties as graphene, which makes it not only a promising catalyst support, but also a highly effective metal-free catalyst in the booming field of green chemistry. Reactions involving small molecules (e.g., oxygen, low carbon alkanes, nitrogen and carbon dioxide) have always been a hot topic in catalytic research, especially associated with the adsorption and activation regime of different forms of small molecules on catalysts. In this review, we have investigated the adsorption of different small molecules and the relevant activation mechanisms of four typical chemical bonds (OO, C-H, NN, CO) on hexagonal boron nitride. Recent progress on approaches adopted to enhance the activation capacity such as doping, defect engineering and heterostructuring are summarized, highlighting the potential applications of nonmetallic hexagonal boron nitride catalysts in various reactions. This comprehensive investigation offers a reference point for the enhanced mechanistic understanding and future design of effective and sustainable catalytic systems based on boron nitride.

Brain development in newborns and infants after ECMO.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) not only significantly improves survival rates in severely ill neonates but also is associated with long-term neurodevelopmental issues. To systematically review the available literature on the neurodevelopmental outcomes of neonates and infants who have undergone ECMO treatment, with a focus on motor deficits, cognitive impairments, sensory impairments, and developmental delays. This review aims to understand the incidence, prevalence, and risk factors for these problems and to explore current nursing care and management strategies. DATA SOURCES: A comprehensive literature search was performed across PubMed, EMBASE, and Web of Science using a wide array of keywords and phrases pertaining to ECMO, neonates, infants, and various facets of neurodevelopment. The initial screening involved reviewing titles and abstracts to exclude irrelevant articles, followed by a full-text assessment of potentially relevant literature. The quality of each study was evaluated based on its research methodology and statistical analysis. Moreover, citation searches were conducted to identify potentially overlooked studies. Although the focus was primarily on neonatal ECMO, studies involving children and adults were also included due to the limited availability of neonate-specific literature. RESULTS: About 50% of neonates post-ECMO treatment exhibit varying degrees of brain injury, particularly in the frontal and temporoparietal white matter regions, often accompanied by neurological complications. Seizures occur in 18%-23% of neonates within the first 24 hours, and bleeding events occur in 27%-60% of ECMO procedures, with up to 33% potentially experiencing ischemic strokes. Although some studies suggest that ECMO may negatively impact hearing and visual development, other studies have found no significant differences; hence, the influence of ECMO remains unclear. In terms of cognitive, language, and intellectual development, ECMO treatment may be associated with potential developmental delays, including lower composite scores in cognitive and motor functions, as well as potential language and learning difficulties. These studies emphasize the importance of early detection and intervention of potential developmental issues in ECMO survivors, possibly necessitating the implementation of a multidisciplinary follow-up plan that includes regular neuromotor and psychological evaluations. Overall, further multicenter, large-sample, long-term follow-up studies are needed to determine the impact of ECMO on these developmental aspects. CONCLUSIONS: The impact of ECMO on an infant's nervous system still requires further investigation with larger sample sizes for validation. Fine-tuned management, comprehensive nursing care, appropriate patient selection, proactive monitoring, nutritional support, and early rehabilitation may potentially contribute to improving the long-term outcomes for these infants.

Synergistic effects of achieving perinatal interventions on bronchopulmonary dysplasia in preterm infants.

To investigate the effect of perinatal interventions on the risk of severe BPD (sBPD) and death in extremely preterm infants (EPIs) and their synergistic effects. This was a secondary analysis of the prospective cohort Chinese Neonatal Network (CHNN). Infants with a birth weight of 500 to 1250 g or 24-28 weeks completed gestational age were recruited. The impacts and the synergistic effects of six evidence-based perinatal interventions on the primary outcomes of sBPD and death were assessed by univariate and multivariable logistic regression modeling. Totally, 6568 EPIs were finally enrolled. Antenatal corticosteroid (adjusted OR, aOR, 0.74; 95%CI, 0.65-083), birth in centers with tertiary NICU (aOR, 0.64; 95%CI, 0.57-0.72), preventing intubation in the delivery room (aOR, 0.65; 95%CI, 0.58-0.73), early caffeine therapy (aOR, 0.59; 95%CI, 0.52-0.66), and early extubating (aOR, 0.42; 95%CI 0.37-0.47), were strongly associated with a lower risk of sBPD and death while early surfactant administration was associated with a lower risk of death (aOR, 0.84; 95%CI, 0.72, 0.98). Compared with achieving 0/1 perinatal interventions, achieving more than one intervention was associated with decreased rates (46.6% in 0/1 groups while 38.5%, 29.6%, 22.2%, 16.2%, and 11.7% in 2/3/4/5/6-intervention groups respectively) and reduced risks of sBPD/death with aORs of 0.76(0.60, 0.96), 0.55(0.43, 0.69), 0.38(0.30, 0.48), 0.28(0.22, 0.36), and 0.20(0.15, 0.27) in 2, 3, 4, 5, and 6 intervention groups respectively. Subgroup analyses showed consistent results. CONCLUSION: Six perinatal interventions can effectively reduce the risk of sBPD and death in a synergistic form. WHAT IS KNOWN: • Bronchopulmonary dysplasia (BPD) is a multifactorial chronic lung disease associated with prematurity. The effective management of BPD requires a comprehensive set of interventions. However, the extent to which these interventions can mitigate the risk of severe outcomes, such as severe BPD or mortality, or if they possess synergistic effects remains unknown. WHAT IS NEW: • The implementation of various perinatal interventions, such as prenatal steroids, birth in centers with tertiary NICU, early non-Invasive respiratory support, surfactant administration within 2 hours after birth, early caffeine initiation within 3 days, and early extubation within 7 days after birth has shown promising results in the prevention of severe bronchopulmonary dysplasia (BPD) or mortality in extremely preterm infants. Moreover, these interventions have demonstrated synergistic effects when implemented in combination.

Acetamide Electrosynthesis from CO2 and Nitrite in Water.

Renewable electricity driven electrocatalytic CO2 reduction reaction (CO2 RR) is a promising solution to carbon neutralization, which mainly generate simple carbon products. It is of great importance to produce more valuable C-N chemicals from CO2 and nitrogen species. However, it is challenging to co-reduce CO2 and NO3 - /NO2 - to generate aldoxime an important intermediate in the electrocatalytic C-N coupling process. Herein, we report the successful electrochemical conversion of CO2 and NO2 - to acetamide for the first time over copper catalysts under alkaline condition through a gas diffusion electrode. Operando spectroelectrochemical characterizations and DFT calculations, suggest acetaldehyde and hydroxylamine identified as key intermediates undergo a nucleophilic addition reaction to produce acetaldoxime, which is then dehydrated to acetonitrile and followed by hydrolysis to give acetamide under highly local alkaline environment and electric field. Moreover, the above mechanism was successfully extended to the formation of phenylacetamide. This study provides a new strategy to synthesize highly valued amides from CO2 and wastewater.

Neurodevelopmental Outcomes Prediction in Newborns with Seizures Caused by KCNQ2 Gene Defects.

INTRODUCTION: Pathogenic variant in the KCNQ2 gene is a common genetic etiology of neonatal convulsion. However, it remains a question in KCNQ2-related disorders that who will develop into atypical developmental outcomes. METHODS: We established a prediction model for the neurodevelopmental outcomes of newborns with seizures caused by KCNQ2 gene defects based on the Gradient Boosting Machine (GBM) model with a training set obtained from the Human Gene Mutation Database (HGMD, public training dataset). The features used in the prediction model were, respectively, based on clinical features only and optimized features. The validation set was obtained from the China Neonatal Genomes Project (CNGP, internal validation dataset). RESULTS: With the HGMD training set, the prediction results showed that the area under the receiver-operating characteristic curve (AUC) for predicting atypical developmental outcomes was 0.723 when using clinical features only and was improved to 0.986 when using optimized features, respectively. In feature importance ranking, both variants pathogenicity and protein functional/structural features played an important role in the prediction model. For the CNGP validation set, the AUC was 0.596 when using clinical features only and was improved to 0.736 when using optimized features. CONCLUSION: In our study, functional/structural features and variant pathogenicity have higher feature importance compared with clinical information. This prediction model for the neurodevelopmental outcomes of newborns with seizures caused by KCNQ2 gene defects is a promising alternative that could prove to be valuable in clinical practice.

Bottom-Up Construction of Ni(II)-Incorporated Covalent Organic Framework for Metallaphotoredox Catalysis.

The construction of an all-in-one catalyst, in which the photosensitizer and the transition metal site are close to each other, is important for improving the efficiency of metallaphotoredox catalysis. However, the development of convenient synthetic strategies for the precise construction of an all-in-one catalyst remains a challenging task due to the requirement of precise installation of the catalytic sites. Herein, we have successfully established a facile bottom-up strategy for the direct synthesis of Ni(II)-incorporated covalent organic framework (COF), named LZU-713@Ni, as a versatile all-in-one metallaphotoredox catalyst. LZU-713@Ni showed excellent activity and recyclability in the photoredox/nickel-catalyzed C-O, C-S, and C-P cross-coupling reactions. Notably, this catalyst displayed a better catalytic activity than its homogeneous analogues, physically mixed dual catalyst system, and, especially, LZU-713/Ni which was prepared through post-synthetic modification. The improved catalytic efficiency of LZU-713@Ni should be attributed to the implementation of bottom-up strategy, which incorporated the fixed, ordered, and abundant catalytic sites into its framework. This work sheds new light on the exploration of concise and effective strategies for the construction of multifunctional COF-based photocatalysts.

Adherence to exercise therapy among children and adolescents with Juvenile idiopathic arthritis: a scoping review.

PURPOSE: To identify parameters and measurement methods of exercise therapy adherence, as well as barriers and facilitators affecting adherence among children and adolescents with juvenile idiopathic arthritis (JIA). METHODS: Studies were eligible for inclusion if patients were 0-18 years of age, had JIA, and the focus of the research was on exercise therapy patterns, measurement/parameters of exercise adherence, and barriers/facilitators for exercise adherence. Two reviewers independently identified and categorized the barriers and facilitators to exercise therapy adherence using the International Classification of Functioning, Disability, and Health (ICF). RESULTS: Twenty articles were included in this review. Among patients with JIA, 29%-99% adhered to exercise therapy. The most commonly measured parameters of adherence were session completion and behavior component, with a self-report log serving as the most common means of assessment. Time pressure, symptoms related to JIA, lack of enjoyment, and insufficient motivation were the main barriers. Facilitators were commonly identified as adequate motivation, effective symptoms management, and social support. CONCLUSIONS: Future interventions should consider the identified factors to promote exercise engagement in children and adolescents with JIA. Strategies for promoting exercise adherence in children and adolescents with JIA is needed.

Despite its potential as an effective means of improving health and function in patients with juvenile idiopathic arthritis (JIA), the level of exercise participation in this population is not ideal.Future interventions should focus on improving personal factors associated with exercise therapy adherence, such as motivation.To facilitate the participation in the exercise of children and adolescents with JIA, supportive exercise environments should be provided.

Treatment of patent ductus arteriosus and short-term outcomes among extremely preterm infants: a multicentre cohort study.

Background: The optimal treatment strategy for patent ductus arteriosus (PDA) in extremely preterm infants is currently highly controversial. This study aimed to evaluate the association between PDA treatment and short-term outcomes among extremely preterm infants. Methods: This cohort study included all extremely preterm infants (≤27 and 6/7 weeks) who were admitted to hospitals participating in the Chinese Neonatal Network from January 2019 to December 2021, and were diagnosed to have PDA by echocardiogram. PDA treatment was defined as medical treatment and/or surgical ligation of PDA during hospitalization. Short-term outcomes included death, bronchopulmonary dysplasia (BPD), death/BPD, retinopathy of prematurity, necrotizing enterocolitis, and severe brain injury. Multivariate logistic regression was used to evaluate the association between PDA treatment and outcomes. Subgroup analysis were performed among infants with different respiratory support on 3 and 7 days of life. Findings: A total of 2494 extremely preterm infants with the diagnosis of PDA were enrolled, of which 1299 (52.1%) received PDA treatment. PDA treatment was significantly associated with lower risk of death (adjusted odds ratio, 0.48; 95% confidence interval, 0.38-0.60). The decreased risk of death was accompanied by increased risk of BPD and death/BPD. In subgroup analysis according to respiratory support, PDA treatment was associated with lower risk of death among infants who required invasive ventilation. However, the beneficial effect on death was not significant among infants who did not require invasive ventilation. Interpretation: PDA treatment was associated with reduced mortality in extremely preterm infants, but this beneficial effect was mainly present among infants who required invasive ventilation. Funding: This study was funded by the Shanghai Science and Technology Commission's Scientific and Technological Innovation Action Plan (21Y21900800) and the Canadian Institutes of Health Research (CTP87518).

Hybrid Network for Patient-Specific Seizure Prediction from EEG Data.

Seizure prediction can improve the quality of life for patients with drug-resistant epilepsy. With the rapid development of deep learning, lots of seizure prediction methods have been proposed. However, seizure prediction based on single convolution models is limited by the inherent defects of convolution itself. Convolution pays attention to the local features while underestimates the global features. The long-term dependence of the electroencephalogram (EEG) data cannot be captured. In view of these defects, a hybrid model called STCNN based on Swin transformer (ST) and 2D convolutional neural network (2DCNN) is proposed. Time-frequency features extracted by short-term Fourier transform (STFT) are taken as the input of STCNN. ST blocks are used in STCNN to capture the global information and long-term dependencies of EEGs. Meanwhile, the 2DCNN blocks are adopted to capture the local information and short-term dependent features. The combination of the two blocks can fully exploit the seizure-related information thus improve the prediction performance. Comprehensive experiments are performed on the CHB-MIT scalp EEG dataset. The average seizure prediction sensitivity, the area under the ROC curve (AUC) and the false positive rate (FPR) are 92.94%, 95.56% and 0.073, respectively.

Lightweight Seizure Detection Based on Multi-Scale Channel Attention.

Epilepsy is one kind of neurological disease characterized by recurring seizures. Recurrent seizures can cause ongoing negative mental and cognitive damage to the patient. Therefore, timely diagnosis and treatment of epilepsy are crucial for patients. Manual electroencephalography (EEG) signals analysis is time and energy consuming, making automatic detection using EEG signals particularly important. Many deep learning algorithms have thus been proposed to detect seizures. These methods rely on expensive and bulky hardware, which makes them unsuitable for deployment on devices with limited resources due to their high demands on computer resources. In this paper, we propose a novel lightweight neural network for seizure detection using pure convolutions, which is composed of inverted residual structure and multi-scale channel attention mechanism. Compared with other methods, our approach significantly reduces the computational complexity, making it possible to deploy on low-cost portable devices for seizures detection. We conduct experiments on the CHB-MIT dataset and achieves 98.7% accuracy, 98.3% sensitivity and 99.1% specificity with 2.68[Formula: see text]M multiply-accumulate operations (MACs) and only 88[Formula: see text]K parameters.

Down-regulation of long noncoding RNA HULC inhibits the inflammatory response in ankylosing spondylitis by reducing miR-556-5p-mediated YAP1 expression.

OBJECTIVE: Ankylosing spondylitis (AS) is a progressive systemic disease characterized by a chronic inflammatory response in the sacroiliac joints and spine. Long noncoding RNAs suggest significant actions in the progression of AS. Therefore, a specific lncRNA, highly upregulated in liver cancer (HULC), was studied here regarding its functions and related mechanisms in AS. METHODS: Measurements of miR-556-5p, HULC, and YAP1 expression were performed on AS cartilage tissues and chondrocytes. The interaction between miR-556-5p and HULC or YAP1 was verified. CCK-8, flow cytometry and enzyme-linked immunosorbent assay were used to evaluate the effects of HULC, miR-556-5p, and YAP1 on the proliferation, apoptosis, and inflammatory response of AS chondrocytes. Furthermore, the action of HULC/miR-556-5p/YAP1 was experimentally observed in AS mice. RESULTS: HULC and YAP1 levels were augmented, while miR-556-5p levels were suppressed in AS cartilage tissues and chondrocytes. Downregulating HULC or upregulating miR-556-5p stimulated chondrocyte proliferation and inhibited apoptosis and inflammation in AS. miR-556-5p was a downstream factor of HULC, and YAP1 was a potential target of miR-556-5p. The improvement effect of downregulated HULC on AS chondrocytes was saved when YAP1 expression was forced. In addition, silence of HULC improved the pathological injury of spinal cartilage in AS mice by enhancing miR-556-5p-related regulation of YAP1. CONCLUSION: HULC inhibition relieves the inflammatory response in AS by reducing miR-556-5p-mediated YAP1 expression.

A study protocol for investigating the sonographic characteristics of neonates with critical illness: an observational cohort study.

BACKGROUND: Haemodynamic instability and hypoxaemia are common and serious threats to the survival of neonates. A growing body of literature indicates that critical care ultrasound has become the optimal evaluation tool for sick neonates. However, few studies have described sonographic characteristics of haemodynamics systematically in the neonates with critical illness. This protocol describes a prospective observational cohort study aimed at (1) characterising the sonographic characteristics of the neonates with critical diseases; and (2) assessing the mortality, significant morbidity, utility of vasoactive medications, fluid resuscitation, duration of ventilation, etc. METHODS AND ANALYSIS: This is a single-centre, prospective and observational study conducted in Chengdu Women's and Children's Central Hospital from 1 December 2022 to 31 December 2027. Neonates admitted to the neonatal intensive care unit will be recruited. After inclusion, the neonates will undergo the neonatal critical care ultrasound. The data collected via case report forms include clinical variables and sonographic measures. The primary outcome is to identify the sonographic characteristics of sick neonates with different diseases, and the secondary outcome is to describe the mortality, significant morbidity, utility of vasoactive medications, fluid resuscitation and duration of ventilation. DISCUSSION: Our study provided an organised neonatal critical care ultrasound workflow, which can be applied in practice. Accordingly, this study will first set up large data on the sonographic description of the neonates with critical illness, which can help to understand the pathophysiology of the critical illness, potentially titrating the treatment. TRIAL REGISTRATION NUMBER: Chinese Clinical Trial Registry (ChiCTR2200065581; https://www.chictr.org.cn/com/25/showproj.aspx?proj=184095).

Risk stratification of hemodynamically significant patent ductus arteriosus by clinical and genetic factors.

BACKGROUND: Hemodynamically significant patent ductus arteriosus (hsPDA) is associated with increased comorbidities in neonates. Early evaluation of hsPDA risk is critical to implement individualized intervention. The aim of the study was to provide a powerful reference for the early identification of high-risk hsPDA population and early treatment decisions. METHODS: We enrolled infants who were diagnosed with PDA and performed exome sequencing. The collapsing analyses were used to find the risk gene set (RGS) of hsPDA for model construction. The credibility of RGS was proven by RNA sequencing. Multivariate logistic regression was performed to establish models combining clinical and genetic features. The models were evaluated by area under the receiver operating curve (AUC) and decision curve analysis (DCA). RESULTS: In this retrospective cohort study of 2199 PDA patients, 549 (25.0%) infants were diagnosed with hsPDA. The model [all clinical characteristics selected by least absolute shrinkage and selection operator regression (all CCs)] based on six clinical variables was acquired within three days of life, including gestational age (GA), respiratory distress syndrome (RDS), the lowest platelet count, invasive mechanical ventilation, and positive inotropic and vasoactive drugs. It has an AUC of 0.790 [95% confidence interval (CI) = 0.749-0.832], while the simplified model (basic clinical characteristic model) including GA and RDS has an AUC of 0.753 (95% CI = 0.706-0.799). There was a certain consistency between RGS and differentially expressed genes of the ductus arteriosus in mice. The AUC of the models was improved by RGS, and the improvement was significant (all CCs vs. all CCs + RGS: 0.790 vs. 0.817, P < 0.001). DCA demonstrated that all models were clinically useful. CONCLUSIONS: Models based on clinical factors were developed to accurately stratify the risk of hsPDA in the first three days of life. Genetic features might further improve the model performance. Video Abstract (MP4 86834 kb).

High-Resolution and Multidimensional Phenotypes Can Complement Genomics Data to Diagnose Diseases in the Neonatal Population.

Advances in genomic medicine have greatly improved our understanding of human diseases. However, phenome is not well understood. High-resolution and multidimensional phenotypes have shed light on the mechanisms underlying neonatal diseases in greater details and have the potential to optimize clinical strategies. In this review, we first highlight the value of analyzing traditional phenotypes using a data science approach in the neonatal population. We then discuss recent research on high-resolution, multidimensional, and structured phenotypes in neonatal critical diseases. Finally, we briefly introduce current technologies available for the analysis of multidimensional data and the value that can be provided by integrating these data into clinical practice. In summary, a time series of multidimensional phenome can improve our understanding of disease mechanisms and diagnostic decision-making, stratify patients, and provide clinicians with optimized strategies for therapeutic intervention; however, the available technologies for collecting multidimensional data and the best platform for connecting multiple modalities should be considered.

Hybrid Attention Network for Epileptic EEG Classification.

Automatic seizure detection from electroencephalography (EEG) based on deep learning has been significantly improved. However, existing works have not adequately excavate the spatial-temporal information between EEG channels. Besides, most works mainly focus on patient-specific scenarios while cross-patient seizure detection is more challenging and meaningful. Regarding the above problems, we propose a hybrid attention network (HAN) for automatic seizure detection. Specifically, the graph attention network (GAT) extracts spatial features at the front end, and Transformer gets time features as the back end. HAN leverages the attention mechanism and fully extracts the spatial-temporal correlation of EEG signals. The focal loss function is introduced to HAN to deal with the imbalance of the dataset accompanied by seizure detection based on EEG. Both patient-specific and patient-independent experiments are carried out on the public CHB-MIT database. Experimental results demonstrate the efficacy of HAN in both experimental settings.