Reassessing acquired neonatal intestinal diseases using unsupervised machine learning.

BACKGROUND: Acquired neonatal intestinal diseases have an array of overlapping presentations and are often labeled under the dichotomous classification of necrotizing enterocolitis (which is poorly defined) or spontaneous intestinal perforation, hindering more precise diagnosis and research. The objective of this study was to take a fresh look at neonatal intestinal disease classification using unsupervised machine learning. METHODS: Patients admitted to the University of Florida Shands Neonatal Intensive Care Unit January 2013-September 2019 diagnosed with an intestinal injury, or had imaging findings of portal venous gas, pneumatosis, abdominal free air, or had an abdominal drain placed or exploratory laparotomy during admission were included. Congenital gastroschisis, omphalocele, intestinal atresia, malrotation were excluded. Data was collected via retrospective chart review with subsequent hierarchal, unsupervised clustering analysis. RESULTS: Five clusters of intestinal injury were identified: Cluster 1 deemed the "Low Mortality" cluster, Cluster 2 deemed the "Mature with Inflammation" cluster, Cluster 3 deemed the "Immature with High Mortality" cluster, Cluster 4 deemed the "Late Injury at Full Feeds" cluster, and Cluster 5 deemed the "Late Injury with High Rate of Intestinal Necrosis" cluster. CONCLUSION: Unsupervised machine learning can be used to cluster acquired neonatal intestinal injuries. Future study with larger multicenter datasets is needed to further refine and classify types of intestinal diseases. IMPACT: Unsupervised machine learning can be used to cluster types of acquired neonatal intestinal injury. Five major clusters of acquired neonatal intestinal injury are described, each with unique features. The clusters herein described deserve future, multicenter study to determine more specific early biomarkers and tailored therapeutic interventions to improve outcomes of often devastating neonatal acquired intestinal injuries.

COVID-19 booster enhances IgG mediated viral neutralization by human milk in vitro.

Background: Facilitated by the inability to vaccinate, and an immature immune system, COVID-19 remains a leading cause of death among children. Vaccinated lactating mothers produce specific SARS-CoV-2 antibodies in their milk, capable of neutralizing the virus in vitro. Our objective for this study is to assess the effect of COVID-19 booster dose on SARS-CoV-2 antibody concentration and viral neutralization in milk, plasma, and infant stool. Methods: Thirty-nine mothers and 25 infants were enrolled from December 2020 to May 2022. Milk, maternal plasma, and infants' stool were collected at various time-points up to 12 months following mRNA COVID-19 vaccination. A subgroup of 14 mothers received a booster dose. SARS-CoV-2 antibody levels and their neutralization capacities were assessed. Results: Booster vaccination led to significantly higher IgG levels within human milk and breastfed infants' stool. In vitro neutralization of VSV-gfp-SARS-CoV-2-S-gp, a laboratory safe SARS-CoV-2 like pseudovirus, improved following the booster, with a 90% increase in plasma neutralization and a 60% increase in milk neutralization. We found that post-booster neutralization by human milk was highly correlated to SARS-CoV-2 IgG level. In support of our correlation result, Protein G column depletion of IgG in milk yielded a significant reduction in viral neutralization (p = 0.04). Discussion: The substantial increase in neutralizing IgG levels in milk and breastfed infants' stool post-booster, coupled with the decrease in milk neutralization capabilities upon IgG depletion, underscores the efficacy of booster doses in augmenting the immune response against SARS-CoV-2 in human milk.

A Scoping Review of the Oral Microbiome in Preterm Infants.

The purpose of this scoping review was to examine the oral microbiome composition in preterm infants, sampling and collection methods, as well as exposures associated with oral microbiome composition and health implications. We conducted a scoping review of the literature using the Arskey and O'Malley framework. We identified a total of 13 articles which met our inclusion criteria and purpose of this scoping review. Articles included in this review compared the oral microbiome in preterm infants to term infants, examined alterations to the oral microbiome over time, compared the oral microbiome to different body site microbiomes, and explored associations with clinically relevant covariates and outcomes. Exposures associated with the diversity and composition of the oral microbiome in preterm infants included delivery mode, oral feeding, oropharyngeal care, skin-to-skin care, and antibiotics. Day of life and birth weight were also associated with oral microbiome composition. The oral microbiome may be associated with the composition of the tracheal and gut microbiomes, likely due to their proximity. Alpha and beta diversity findings varied across studies as well as the relative abundance of taxa. This is likely due to the different sampling techniques and timing of collection, as well as the wide range of infant clinical characteristics. Multiple factors may influence the composition of the oral microbiome in preterm infants. However, given the heterogeneity of sampling techniques and results within this review, the evidence is not conclusive on the development as well as short- and long-term implications of the oral microbiome in preterm infants and needs to be explored in future research studies. KEY POINTS: · Day of life is a critical factor in oral microbiome development in preterm infants.. · The oral microbiome may be associated with tracheal and gut microbiome colonization.. · Future research should examine sampling methodology for examining the oral microbiome.. · Future research should explore associations with the oral microbiome and adverse health outcomes..

Monitoring and management of hypertriglyceridemia in extremely low birth weight neonates receiving intravenous lipid emulsions: A national survey.

AIM: To assess the practice variation of defining, monitoring and managing hypertriglyceridemia (HTG) in extremely low birth weight neonates receiving intravenous lipid emulsions (IVLE). METHODS: An 8-question survey created via the web survey site Qualtrics was distributed to neonatologists, neonatal nurse practitioners and fellows within the Section of Neonatal-Perinatal Medicine email directory list in the United States and Canada. Survey results were obtained between August and September 2022. RESULTS: There were 249 respondents from approximately 4000 members within the Section of Neonatal-Perinatal Medicine. Responses were documented as a frequency (percentage) with a margin of error of plus or minus 6.2 %. Most respondents were neonatologists, individuals practicing for >10 years and reported a unit-based policy for IVLE initiation and advancement. The definitions of HTG varied among respondents, with the majority (42.7 %) reporting a defining threshold of >200 mg/dL. Nineteen percent of respondents reported not routinely monitoring serum triglyceride concentrations with variable triglyceride monitoring intervals reported by other survey respondents. Regarding elevated triglyceride concentrations, 19.0 % reported decreasing the IVLE rate and checking triglyceride concentrations until normalization; 14.6 % reported IVLE discontinuation and monitoring triglyceride concentrations until normalization; 61.9 % reported using a combination of the above practices; and 4.4 % reported individualized practices for IVLE management with elevated triglyceride concentrations. CONCLUSION: This survey demonstrates a high variation in defining, monitoring and managing HTG in extremely low birth weight neonates and emphasizes the need for studies to better guide this practice.

Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal.

Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.

Progression of Enteral Feeding Volumes in Extremely Low Birth Weight Infants in the "Connection Trial".

OBJECTIVE: Investigate daily feeding volumes and their association with clinical variables in the early postnatal care of premature infants of the "Connection Trial." STUDY DESIGN: A total of 641 infants of 510 to 1,000-g birth weight (BW, mean: 847 g) and mean 27 weeks' gestational age at birth (GA) were analyzed for total daily enteral (TDE) feeding volumes of 10, 20, 40, 80, and 120 mL/kg/d and their association with 24 clinical variables. Uni- and multivariable Cox regression models were used to calculate hazard ratios (HR) with 95% confidence intervals as a measure of the chance of reaching each of the TDE volumes. RESULTS: Daily feeding volumes were highly variable and the median advancement from 10 to 120 mL/kg/d was 11 mL/kg/d. Univariable analyses showed the lowest chance (HR, 0.22-0.81) of reaching the TDE volumes for gastrointestinal (GI) serious adverse events (SAEs), GI perforation, GI obstruction, and necrotizing enterocolitis, as well as respiratory SAEs, persistent ductus arteriosus, and hypotension. Each GA week, 100-g BW, and point in 5-minute Apgar score at birth associated with 8 to 20% increased chance of reaching the TDE volumes. Multivariable analyses showed independent effects for BW, GA, Apgar score, GI SAEs, abdominal symptoms/signs, respiratory SAEs, days on antibiotics, and hypotension. CONCLUSION: This observational analysis demonstrates the variable and cautious progression of enteral feedings in contemporary extremely low BW infants and the extent to which clinical variables associate with this progression. KEY POINTS: · Total feedings of 10 and 120 mL/kg/d were reached at median 4 and 14 day of age, respectively, and at a daily increase of 11 mL/kg.. · Each incremental GA week, 100-g BW, and point in 5-minute Apgar score associated with 8 to 20% increased chance of reaching enteral feedings of 10 to 120 mL/kg/d.. · Progression of enteral feeding associated with several clinical events and was slower than advocated in common feeding protocols..

Multiomic Investigations into Lung Health and Disease.

Diseases of the lung account for more than 5 million deaths worldwide and are a healthcare burden. Improving clinical outcomes, including mortality and quality of life, involves a holistic understanding of the disease, which can be provided by the integration of lung multi-omics data. An enhanced understanding of comprehensive multiomic datasets provides opportunities to leverage those datasets to inform the treatment and prevention of lung diseases by classifying severity, prognostication, and discovery of biomarkers. The main objective of this review is to summarize the use of multiomics investigations in lung disease, including multiomics integration and the use of machine learning computational methods. This review also discusses lung disease models, including animal models, organoids, and single-cell lines, to study multiomics in lung health and disease. We provide examples of lung diseases where multi-omics investigations have provided deeper insight into etiopathogenesis and have resulted in improved preventative and therapeutic interventions.

Oral Care in Critically Ill Infants and the Potential Effect on Infant Health: An Integrative Review.

BACKGROUND: Critically ill infants admitted to the neonatal intensive care unit are at risk for ventilator-associated pneumonia and abnormal oral colonization. Adherence to evidence-based guidelines for oral care in critically ill adults is associated with improved short- and long-term health outcomes. However, oral care guidelines for critically ill infants admitted to the neonatal intensive care unit have not been established, possibly increasing their risk of ventilator-associated pneumonia and other health complications. OBJECTIVE: To describe and summarize the evidence regarding oral care for critically ill infants admitted to the neonatal intensive care unit and to identify gaps needing further investigation. METHODS: The MEDLINE (through PubMed) and CINAHL databases were searched for observational studies and randomized controlled trials investigating the effect of oral care on oral colonization, ventilator-associated pneumonia, and health outcomes of infants in the neonatal intensive care unit. RESULTS: This review of 5 studies yielded evidence that oral care may promote a more commensal oral and endotracheal tube aspirate microbiome. It may also reduce the risk of ventilator-associated pneumonia and length of stay in the neonatal intensive care unit. However, the paucity of research regarding oral care in this population and differences in oral care procedures, elements used, and timing greatly limit any possible conclusions. CONCLUSIONS: Oral care in critically ill infants may be especially important because of their suppressed immunity and physiological immaturity. Further appropriately powered studies that control for potential covariates, monitor for adverse events, and use recommended definitions of ventilator-associated pneumonia are needed to make clinical recommendations.

Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the screening burden on ophthalmologists and neonatologists and improve the detection of treatment-requiring ROP. Neural networks such as convolutional neural networks and deep learning (DL) systems are used to calculate a vascular severity score (VSS), an important component of various risk models. These DL systems have been validated in various studies, which are reviewed here. Most importantly, we discuss a promising study that validated a DL system that could predict the development of ROP despite a lack of clinical evidence of disease on the first retinal examination. Additionally, there is promise in utilizing these systems through telemedicine in more rural and resource-limited areas. This review highlights the value of these DL systems in early ROP diagnosis.

Antibiotics Use and Its Effects on the Establishment of Feeding Tolerance in Preterm Neonates.

OBJECTIVE: Antibiotics are one of the most widely used medications in today's neonatal intensive care units. Indiscriminate antibiotic usage persists in preterm newborns who are symptomatic due to factors linked to prematurity rather than being septic. Previous studies in older infants suggest that prior antibiotic administration is associated with possible dysmotility and microbial dysbiosis in the intestinal tract. We hypothesize that early antibiotic administration impacts high-risk preterm infants' tolerance to enteral feeding advancement. STUDY DESIGN: As part of the Routine Early Antibiotic Use in SymptOmatic Preterm Neonates study, symptomatic preterm newborns without maternal infection risk factors were randomized to receive or not receive antibiotics, with C1 receiving antibiotics and C2 not. Of the 55 newborns that underwent pragmatic randomization, 28 preterm neonates in group C1 received antibiotics. RESULTS: The premature neonates in the randomized groups who received antibiotics and those who did not showed no differences in sustained feeding tolerance. CONCLUSION: Our investigation of the risk of feeding issues in babies who get antibiotics early in life revealed no differences between neonates who received antibiotics and those who did not when the randomized controlled trial data alone was reviewed. Given the sample sizes, it is uncertain if the preceding analysis is powerful enough to detect differences (a significant percentage of neonates who were randomly assigned to NOT get antibiotics subsequently received early treatment due to changing clinical conditions). This affirms the requirement for a meticulously designed prospective randomized study. KEY POINTS: · Defining feeding tolerance for the first time in neonates.. · Patients from the REASON trial were evaluated.. · Preterm neonates were the focus of this study..

Association between early life antibiotic exposure and development of early childhood atopic dermatitis.

Background: Atopic dermatitis (AD) is a chronic, inflammatory skin disease commonly onset during infancy. Objective: We examine the association between pre-and postnatal antibiotic exposure and the development of AD. Methods: A retrospective, observational study analyzed 4106 infants at the University of Florida from June 2011 to April 2017. Results: Antibiotic exposure during the first year of life was associated with a lower risk of AD. The association was strongest for exposure during the first month of life. There were no significant differences in the rates of AD in infants with or without exposure to antibiotics in months 2 through 12, when examined by month. Antibiotic exposure during week 2 of life was associated with lower risk of AD, with weeks 1, 3, and 4 demonstrating a similar trend. Limitations: Retrospective data collection from a single center, use of electronic medical record, patient compliance with prescribed medication, and variable follow-up. Conclusions: Early life exposures, such as antibiotics, may lead to long-term changes in immunity. Murine models of atopic dermatitis demonstrate a "critical window" for the development of immune tolerance to cutaneous microbes. Our findings suggest that there may also be a "critical window" for immune tolerance in human infants, influenced by antibiotic exposure.

Detection of SARS-CoV-2 IgA and IgG in human milk and breastfeeding infant stool 6 months after maternal COVID-19 vaccination.

OBJECTIVE: Assess presence, durability, and neutralization capacity of SARS-CoV-2-specific antibodies in breastfeeding infants' stool, mother's plasma and milk following maternal vaccination. DESIGN: Thirty-seven mothers and 25 infants were enrolled between December 2020 and November 2021 for this prospective observational study. All mothers were vaccinated during lactation except three, which were vaccinated during pregnancy. Milk, maternal plasma, and infants' stool was collected pre-vaccination and at periods up to 6 months following COVID-19 vaccine series initiation/completion. SARS-CoV-2 antibody levels and their neutralization capacities were assessed. RESULTS: SARS-CoV-2-specific IgA and IgG levels were higher in infant stool post-maternal vaccination amongst milk-fed compared to controls. Maternal SARS-CoV-2-specific IgA and IgG concentrations decreased over 6 months post-vaccination but remained higher than pre-vaccination levels. We observed improved neutralization capacity in milk and plasma after COVID-19 vaccination. CONCLUSIONS: The presence of SARS-CoV-2-specific antibodies in infant stool following maternal vaccination offers further evidence of the lasting transfer of these antibodies through breastfeeding.

Skin microbiome sampling in the preterm neonate.

Despite advances in our understanding of the human microbiome, there exist significant knowledge gaps in our understanding of the skin microbiome of the preterm neonate. Herein, we describe skin microbiome sampling of six preterm neonates at multiple timepoints, and compare the skin microbiome samples to environmental (crib/isolette swabs) and negative controls. Samples of the same type (skin, crib, control) were more similar than when compared by week or by patient.

Multiomics, artificial intelligence, and precision medicine in perinatology.

Technological advances in omics evaluation, bioinformatics, and artificial intelligence have made us rethink ways to improve patient outcomes. Collective quantification and characterization of biological data including genomics, epigenomics, metabolomics, and proteomics is now feasible at low cost with rapid turnover. Significant advances in the integration methods of these multiomics data sets by machine learning promise us a holistic view of disease pathogenesis and yield biomarkers for disease diagnosis and prognosis. Using machine learning tools and algorithms, it is possible to integrate multiomics data with clinical information to develop predictive models that identify risk before the condition is clinically apparent, thus facilitating early interventions to improve the health trajectories of the patients. In this review, we intend to update the readers on the recent developments related to the use of artificial intelligence in integrating multiomic and clinical data sets in the field of perinatology, focusing on neonatal intensive care and the opportunities for precision medicine. We intend to briefly discuss the potential negative societal and ethical consequences of using artificial intelligence in healthcare. We are poised for a new era in medicine where computational analysis of biological and clinical data sets will make precision medicine a reality. IMPACT: Biotechnological advances have made multiomic evaluations feasible and integration of multiomics data may provide a holistic view of disease pathophysiology. Artificial Intelligence and machine learning tools are being increasingly used in healthcare for diagnosis, prognostication, and outcome predictions. Leveraging artificial intelligence and machine learning tools for integration of multiomics and clinical data will pave the way for precision medicine in perinatology.

Tachygastria in Preterm Infants: A Longitudinal Cohort Study.

OBJECTIVES: Tachygastria is a gastric dysrhythmia (>4 to ≤9 cycles per minute, cpm) associated with gastric hypomotility and gastrointestinal disorders. Healthy preterm infants spend more time in tachygastria than adults; however, normative values are not defined. We sought to determine the percent of time preterm infants spend in tachygastria. METHODS: We conducted a longitudinal, prospective cohort study with weekly electrogastrography (EGG) recordings in 51 preterm <34 weeks' gestation and 5 term (reference) infants. We calculated percentage recording time in tachygastria (% tachygastria) and determined the mean ± standard deviation (SD) across EGG sessions. Mixed effects model was performed to test weekly variance in % tachygastria and gestational age effect. Successive pre- and post-prandial measurements were obtained to assess reproducibility of % tachygastria. We compared time to achieve full feeds between subjects with % tachygastria within 1 SD from the mean versus % tachygastria >1 SD from mean. RESULTS: Three hundred seventy-six EGG sessions were completed (N = 56). Mean % tachygastria was 40% with SD ±5%. We demonstrated no change in % tachygastria across 9 postnatal weeks (P = 0.70) and no gestational age effect. No difference was demonstrated between successive pre- (P = 0.91) and post-prandial (P = 0.96) % tachygastria. Infants with 35%-45% tachygastria (within 1 SD from mean) had higher gestational age and less time to achieve full feeds than infants with <35% or >45% tachygastria. CONCLUSIONS: EGG is a reproducible tool to assess % tachygastria in preterm infants. Clinical significance of increased or decreased % tachygastria needs further investigation to validate if 35%-45% tachygastria is safe for feeding.