Establishing Pose Based Features Using Histograms for the Detection of Abnormal Infant Movements

The pursuit of early diagnosis of cerebral palsy has been an active research area with some very promising results using tools such as the General Movements Assessment (GMA). In this paper, we conducted a pilot study on extracting important information from video sequences to classify the body movement into two categories, normal and abnormal, and compared the results provided by an independent expert reviewer based on GMA. We present two new pose-based features, Histograms of Joint Orientation 2D (HOJO2D) and Histograms of Joint Displacement 2D (HOJD2D), for the pose-based analysis and classification of infant body movement from video footage. We extract the 2D skeletal joint locations from 2D RGB images using Cao et al.’s method 1. Using the MINI-RGBD dataset 2, we further segment the body into local regions to extract part specific features. As a result, the pose and the degree of displacement are represented by histograms of normalised data. To demonstrate the effectiveness of the proposed features, we trained several classifiers using combinations of HOJO2D and HOJD2D features and conducted a series of experiments to classify the body movement into categories. The classification algorithms used included k-Nearest Neighbour (kNN, k=1 and k=3), Linear Discriminant Analysis (LDA) and the Ensemble classifier. Encouraging results were attained, with high accuracy (91.67{\%}) obtained using the Ensemble classifier

Nutrient-enriched formula versus standard formula for preterm infants

BACKGROUND: Preterm infants may accumulate nutrient deficits leading to extrauterine growth restriction. Feeding preterm infants with nutrient-enriched rather than standard formula might increase nutrient accretion and growth rates and might improve neurodevelopmental outcomes. OBJECTIVES: To compare the effects of feeding with nutrient-enriched formula versus standard formula on growth and development of preterm infants. SEARCH METHODS: We used the Cochrane Neonatal standard search strategy. This included electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL; 2018, Issue 11), MEDLINE, Embase, and the Cumulative Index to Nursing and Allied Health Literature (until November 2018), as well as conference proceedings, previous reviews, and clinical trials databases. SELECTION CRITERIA: Randomised and quasi-randomised controlled trials that compared feeding preterm infants with nutrient-enriched formula (protein and energy plus minerals, vitamins, or other nutrients) versus standard formula. DATA COLLECTION AND ANALYSIS: We extracted data using the Cochrane Neonatal standard methods. Two review authors separately evaluated trial quality and extracted and synthesised data using risk ratios (RRs), risk differences, and mean differences (MDs). We assessed certainty of evidence at the outcome level using Grading of Recommendations Assessment, Development and Evaluation (GRADE) methods. MAIN RESULTS: We identified seven trials in which a total of 590 preterm infants participated. Most participants were clinically stable preterm infants of birth weight less than 1850 g. Few participants were extremely preterm, extremely low birth weight, or growth restricted at birth. Trials were conducted more than 30 years ago, were formula industry funded, and were small with methodological weaknesses (including lack of masking) that might bias effect estimates. Meta-analyses of in-hospital growth parameters were limited by statistical heterogeneity. There is no evidence of an effect on time to regain birth weight (MD -1.48 days, 95% confidence interval (CI) -4.73 to 1.77) and low-certainty evidence suggests that feeding with nutrient-enriched formula increases in-hospital rates of weight gain (MD 2.43 g/kg/d, 95% CI 1.60 to 3.26) and head circumference growth (MD 1.04 mm/week, 95% CI 0.18 to 1.89). Meta-analysis did not show an effect on the average rate of length gain (MD 0.22 mm/week, 95% CI -0.70 to 1.13). Fewer data are available for growth and developmental outcomes assessed beyond infancy, and these do not show consistent effects of nutrient-enriched formula feeding. Data from two trials did not show an effect on Bayley Mental Development Index scores at 18 months post term (MD 2.87, 95% CI -1.38 to 7.12; moderate-certainty evidence). Infants who received nutrient-enriched formula had higher Bayley Psychomotor Development Index scores at 18 months post term (MD 6.56. 95% CI 2.87 to 10.26; low-certainty evidence), but no evidence suggested an effect on cerebral palsy (typical RR 0.79, 95% CI 0.30 to 2.07; 2 studies, 377 infants). Available data did not indicate any other benefits or harms and provided low-certainty evidence about the effect of nutrient-enriched formula feeding on the risk of necrotising enterocolitis in preterm infants (typical RR 0.72, 95% CI 0.41 to 1.25; 3 studies, 489 infants). AUTHORS' CONCLUSIONS: Available trial data show that feeding preterm infants nutrient-enriched (compared with standard) formulas has only modest effects on growth rates during their initial hospital admission. No evidence suggests effects on long-term growth or development. The GRADE assessment indicates that the certainty of this evidence is low, and that these findings should be interpreted and applied with caution. Further randomised trials would be needed to resolve this uncertainty

A Pose-based Feature Fusion and Classification Framework for the Early Prediction of Cerebral Palsy in Infants

The early diagnosis of cerebral palsy is an area which has recently seen significant multi-disciplinary research. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. However, the prospect of automating these processes may improve accessibility of the assessment and also enhance the understanding of movement development of infants. Previous works have established the viability of using pose-based features extracted from RGB video sequences to undertake classification of infant body movements based upon the GMA. In this paper, we propose a series of new and improved features, and a feature fusion pipeline for this classification task. We also introduce the RVI-38 dataset, a series of videos captured as part of routine clinical care. By utilising this challenging dataset we establish the robustness of several motion features for classification, subsequently informing the design of our proposed feature fusion framework based upon the GMA. We evaluate our proposed framework’s classification performance using both the RVI-38 dataset and the publicly available MINI-RGBD dataset. We also implement several other methods from the literature for direct comparison using these two independent datasets. Our experimental results and feature analysis show that our proposed pose-based method performs well across both datasets. The proposed features afford us the opportunity to include finer detail than previous methods, and further model GMA specific body movements. These new features also allow us to take advantage of additional body-part specific information as a means of improving the overall classification performance, whilst retaining GMA relevant, interpretable, and shareable features

Bone Mineral Density and Osteoporosis after Preterm Birth: The Role of Early Life Factors and Nutrition

The effects of preterm birth and perinatal events on bone health in later life remain largely unknown. Bone mineral density (BMD) and osteoporosis risk may be programmed by early life factors. We summarise the existing literature relating to the effects of prematurity on adult BMD and the Developmental Origins of Health and Disease hypothesis and programming of bone growth. Metabolic bone disease of prematurity and the influence of epigenetics on bone metabolism are discussed and current evidence regarding the effects of breastfeeding and aluminium exposure on bone metabolism is summarised. This review highlights the need for further research into modifiable early life factors and their effect on long-term bone health after preterm birth

Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework

Providing early diagnosis of cerebral palsy (CP) is key to enhancing the developmental outcomes for those affected. Diagnostic tools such as the General Movements Assessment (GMA), have produced promising results in early diagnosis, however these manual methods can be laborious. In this paper, we propose a new framework for the automated classification of infant body movements, based upon the GMA, which unlike previous methods, also incorporates a visualization framework to aid with interpretability. Our proposed framework segments extracted features to detect the presence of Fidgety Movements (FMs) associated with the GMA spatiotemporally. These features are then used to identify the body-parts with the greatest contribution towards a classification decision and highlight the related body-part segment providing visual feedback to the user. We quantitatively compare the proposed framework's classification performance with several other methods from the literature and qualitatively evaluate the visualization's veracity. Our experimental results show that the proposed method performs more robustly than comparable techniques in this setting whilst simultaneously providing relevant visual interpretability

Probiotics for preterm infants and the recent FDA alert in the USA

The US Food and Drug Administration (FDA) recently issued a warning regarding probiotic use in preterm infants1 leading to the withdrawal of at least two products in the USA. Product withdrawal may extend to Europe, if companies become unwilling to risk legal challenges for products that may not generate significant profits. The FDA alert highlighted the risk of € invasive, potentially fatal' sepsis with probiotics, and the unregulated nature of the market. Product marketing may have implied probiotics reduce necrotising enterocolitis (NEC), when such a claim can only be made with high-quality randomised controlled trial (RCT) evidence. Despite a plethora of RCTs and meta-analyses (MAs), no RCT with NEC as a primary outcome has shown benefit, nor has any RCT been powered with NEC as the primary outcome. This is disappointing as NEC is responsible for more than 1:20 child deaths before age 10 years.2 Nevertheless, most neonatal medicine practice is based on MAs, observational studies and clinician experience rather than definitive RCTs

Optimisation and application of a novel method to identify bacteriophage in maternal milk and infant stool identifies host-phage communities within preterm infant gut

Human milk oligosaccharides, proteins such as lactoferrin, and bacteria represent just some of the bioactive components of mothers’ breast milk (BM). Bacteriophages (viruses that infect bacteria) are an often-overlooked component of BM that can cause major changes in microbial composition and metabolism. BM bacteriophage composition has been explored in term and healthy infants, suggesting vertical transmission of bacteriophages occurs between mothers and their infants. Several important differences between term and very preterm infants (< 30 weeks gestational age) may limit this phenomenon in the latter. To better understand the link between BM bacteriophages and gut microbiomes of very preterm infants in health and disease, standardised protocols are required for isolation and characterisation from BM. In this study we use isolated nucleic acid content, bacteriophage richness and Shannon diversity to validate several parameters applicable during bacteriophage isolation from precious BM samples. Parameters validated include sample volume required; centrifugal sedimentation of microbes; hydrolysis of milk samples with digestive enzymes; induction of temperate bacteriophages and concentration / purification of isolated bacteriophage particles in donor milk (DM). Our optimised method enables characterisation of bacteriophages from as little as 0.1 mL BM. We identify viral families that were exclusively identified with inclusion of induction of temperate bacteriophages (Inoviridae) and hydrolysis of milk lipid processes (Iridoviridae and Baculoviridae). Once applied to a small clinical cohort we demonstrate vertical transmission of bacteriophages from mothers BM to the gut of very preterm infants at the species level. This optimised method will enable future research characterising the bacteriophage composition of BM in very preterm infants to determine their clinical relevance in the development of a healthy preterm infant gut microbiome

Caffeine for the care of preterm infants in sub-Saharan Africa: a missed opportunity?

In 2019, 2.4 million neonates (infants <28 days of age) died globally. Of these, over 80% were preterm infants (<37 weeks gestation), with the majority born in low-income and middle-income countries.1 Complications of preterm birth, largely from respiratory distress syndrome due to surfactant deficiency, pneumonia or apnoea of prematurity (AOP), are now the leading cause of under 5 mortality globally.1 These conditions are frequently fatal in the absence of effective ventilatory support which is commonplace in neonatal units across sub-Saharan Africa. Although the global neonatal mortality rate (NMR) has halved over the past three decades, significant regional disparities remain. These correlate with World Bank and International Monetary Fund estimates of the proportion of the population living on less than US$1.90 a day, with the majority of poorer countries being in sub-Saharan Africa.1 2 As the region with the highest NMR of 27 per 1000 live births, it is estimated that a baby born in in sub-Saharan Africa is 10 times more likely to die than one born in a high income country.1 Countries in sub-Saharan Africa are unlikely to meet the global target of no more than 12 newborn deaths per 1000 live births by 2030.3 In 2017, 75 countries (almost half from sub-Saharan Africa) signed up to the ‘Every Newborn Action Plan’ that has strategic global and national actions and milestones to address gaps in maternal and newborn care.4 This ambitious commitment requires evidence-based interventions5 and innovative strategies to improve neonatal survival and longer-term outcomes

Development of the preterm gut microbiome in twins at risk of necrotising enterocolitis and sepsis

The preterm gut microbiome is a complex dynamic community influenced by genetic and environmental factors and is implicated in the pathogenesis of necrotising enterocolitis (NEC) and sepsis. We aimed to explore the longitudinal development of the gut microbiome in preterm twins to determine how shared environmental and genetic factors may influence temporal changes and compared this to the expressed breast milk (EBM) microbiome. Stool samples (n = 173) from 27 infants (12 twin pairs and 1 triplet set) and EBM (n = 18) from 4 mothers were collected longitudinally. All samples underwent PCR-DGGE (denaturing gradient gel electrophoresis) analysis and a selected subset underwent 454 pyrosequencing. Stool and EBM shared a core microbiome dominated by Enterobacteriaceae, Enterococcaceae, and Staphylococcaceae. The gut microbiome showed greater similarity between siblings compared to unrelated individuals. Pyrosequencing revealed a reduction in diversity and increasing dominance of Escherichia sp. preceding NEC that was not observed in the healthy twin. Antibiotic treatment had a substantial effect on the gut microbiome, reducing Escherichia sp. and increasing other Enterobacteriaceae. This study demonstrates related preterm twins share similar gut microbiome development, even within the complex environment of neonatal intensive care. This is likely a result of shared genetic and immunomodulatory factors as well as exposure to the same maternal microbiome during birth, skin contact and exposure to EBM. Environmental factors including antibiotic exposure and feeding are additional significant determinants of community structure, regardless of host genetics