Clinical Predictors and Outcome of Metabolic Acidosis in Under-Five Children Admitted to an Urban Hospital in Bangladesh with Diarrhea and Pneumonia

BACKGROUND: Clinical features of metabolic acidosis and pneumonia frequently overlap in young diarrheal children, resulting in differentiation from each other very difficult. However, there is no published data on the predictors of metabolic acidosis in diarrheal children also having pneumonia. Our objective was to evaluate clinical predictors of metabolic acidosis in under-five diarrheal children with radiological pneumonia, and their outcome. METHODS: We prospectively enrolled all under-five children (n = 164) admitted to the Special Care Ward (SCW) of the Dhaka Hospital of icddr, b between September and December 2007 with diarrhea and radiological pneumonia who also had their total serum carbon-dioxide estimated. We compared the clinical features and outcome of children with radiological pneumonia and diarrhea with (n = 98) and without metabolic acidosis (n = 66). RESULTS: Children with metabolic acidosis more often had higher case-fatality (16% vs. 5%, p = 0.039) compared to those without metabolic acidosis on admission. In logistic regression analysis, after adjusting for potential confounders such as age of the patient, fever on admission, and severe wasting, the independent predictors of metabolic acidosis in under-five diarrheal children having pneumonia were clinical dehydration (OR 3.57, 95% CI 1.62-7.89, p = 0.002), and low systolic blood pressure even after full rehydration (OR 1.02, 95% CI 1.01-1.04, p = 0.005). Proportions of children with cough, respiratory rate/minute, lower chest wall indrawing, nasal flaring, head nodding, grunting respiration, and cyanosis were comparable (p>0.05) among the groups. CONCLUSION AND SIGNIFICANCE: Under-five diarrheal children with radiological pneumonia having metabolic acidosis had frequent fatal outcome than those without acidosis. Clinical dehydration and persistent systolic hypotension even after adequate rehydration were independent clinical predictors of metabolic acidosis among the children. However, metabolic acidosis in young diarrheal children had no impact on the diagnostic clinical features of radiological pneumonia which underscores the importance of early initiation of appropriate antibiotics to combat morbidity and deaths in such population

Impact of Lack of Breast Feeding during Neonatal Age on the Development of Clinical Signs of Pneumonia and Hypoxemia in Young Infants with Diarrhea

Hypoxemia is a grave sequel of pneumonia, and an important predictor of a fatal outcome. Pneumonia in the neonatal period is often associated with lack of breast feeding. However, there is no published report on the impact of the cessation of breast feeding in the neonatal period on the development of pneumonia and hypoxemia. The purpose of our study was to assess the impact of non-breast feeding or stopping breast feeding during the neonatal period (henceforth to be referred to as non-breast fed) on clinical features of pneumonia and hypoxemia in 0-6-month-old infants with diarrhea admitted to an urban hospital in Bangladesh.We prospectively enrolled all infants (n = 107) aged 0 to 6 months who were admitted to the Special Care Ward (SCW) of the Dhaka Hospital of the International Centre for Diarrhoeal Disease Research Bangladesh (ICDDR,B) with diarrhea and pneumonia from September 2007 through December 2007.We compared the clinical features of pneumonia and hypoxemia of breast fed infants (n = 34) with those who were non-breast fed (n = 73).The median (inter-quartile range) duration of hypoxemia (hours) in non-breast-feds was longer than breast-fed infants [0.0 (0.0, 12.0) vs. 12.0 (0.0, 21.75); p = 0.021]. After adjusting for potential confounders such as inability to drink, fever, head nodding, cyanosis, grunting respiration, and lower chest wall in drawing, the non-breast-fed infants with pneumonia along with diarrhea had a higher probability of cough (OR 9.09; CI 1.34-61.71; p = 0.024), hypoxemia (OR 3.32; CI 1.23-8.93; p = 0.017), and severe undernutrition (OR 3.42; CI 1.29-9.12; p = 0.014).Non-breast feeding or cessation of breast feeding during the neonatal period may substantially increase the incidence of severe malnutrition, incidence of cough, and both the incidence and duration of hypoxemia in young infants presenting with pneumonia and diarrhea. The findings emphasize the paramount importance of the continuation of breast feeding in the neonatal period and early infancy

Clinical characteristics, etiology and antimicrobial susceptibility among overweight and obese individuals with diarrhea: observed at a large diarrheal disease hospital, Bangladesh

Background:The present study aimed to determine the clinical characteristics and etiology of overweight and obese (OO) individuals with diarrhea attending an urban Dhaka Hospital, International Centre for Diarrheal Disease Research (icddr,b), Bangladesh.Methods:Total of 508 under-5 children, 96 individuals of 5-19 years and 1331 of >19 years were identified as OO from the Diarrheal Disease Surveillance System (DDSS) between 1993-2011. Two comparison groups such as well-nourished and malnourished individuals from respective age stratums were selected.Results:Isolation rate of rotavirus was higher among OO under-5 children compared to malnourished group (46% vs. 28%). Rotavirus infection among OO individuals aged 5-19 years (9% vs. 3%) (9% vs. 3%) and >19 years (6% vs. 4%) (6% vs. 3%) was higher compared to well-nourished and malnourished children. Conversely, Vibrio cholerae was lower among all OO age groups compared to well-nourished and malnourished ones. Shigella (4% vs. 6%) (4% vs. 8%), and Campylobacter (3% vs. 5%) (3% vs. 5%) were lower only among OO in >19 years individuals compared to their counterparts of the same age stratum. Salmonella was similarly isolated in all age strata and nutritional groups. In multinomial logistic regression among under-5 children, significant association was observed only with use of antimicrobials at home [OR-1.97] and duration of hospital stay [OR-0.68]. For individuals aged 5-19 years, use of antimicrobials at home (OR-1.83), some or severe dehydration (OR-3.12), having received intravenous saline (OR-0.46) and rotavirus diarrhea (OR-2.96) were found to be associated with OO respectively. Moreover, significant associations were also found for duration of diarrhea before coming to hospital (>24 hours) (OR-1.24), Shigella (OR-0.46), and Campylobacter (OR-0.58) among >19 years OO individuals along with other associated co-variates in 5-19 years group (all

Maximum Photosynthetic Yield of Green Microalgae in Photobioreactors

The biomass yield on light energy of Dunaliella tertiolecta and Chlorella sorokiniana was investigated in a 1.25- and 2.15-cm light path panel photobioreactor at constant ingoing photon flux density (930 µmol photons m−2 s−1). At the optimal combination of biomass density and dilution rate, equal biomass yields on light energy were observed for both light paths for both microalgae. The observed biomass yield on light energy appeared to be based on a constant intrinsic biomass yield and a constant maintenance energy requirement per gram biomass. Using the model of Pirt (New Phytol 102:3–37, 1986), a biomass yield on light energy of 0.78 and 0.75 g mol photons−1 and a maintenance requirement of 0.0133 and 0.0068 mol photons g−1 h−1 were found for D. tertiolecta and C. sorokiniana, respectively. The observed yield decreases steeply at low light supply rates, and according to this model, this is related to the increase of the amount of useable light energy diverted to biomass maintenance. With this study, we demonstrated that the observed biomass yield on light in short light path bioreactors at high biomass densities decreases because maintenance requirements are relatively high at these conditions. All our experimental data for the two strains tested could be described by the physiological models of Pirt (New Phytol 102:3–37, 1986). Consequently, for the design of a photobioreactor, we should maintain a relatively high specific light supply rate. A process with high biomass densities and high yields at high light intensities can only be obtained in short light path photobioreactors

Self organising maps for visualising and modelling

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring

Pneumonia and poverty: a prospective population-based study among children in Brazil

<p>Abstract</p> <p>Background</p> <p>Children in developing country suffer the highest burden of pneumonia. However, few studies have evaluated associations between poverty and pneumonia.</p> <p>Methods</p> <p>A prospective population-based study on pneumonia was carried out as part of the Latin America Epidemiological Assessment of Pneumococcus (LEAP study). Chest x-rays were obtained for children one to 35 months old with suspected pneumonia presenting to emergency care centers and hospital emergency rooms in Goiania, Brazil. Chest radiographs were evaluated according to WHO guidelines. Clustering of radiologically-confirmed pneumonia were evaluated using a Poisson-based spatial scan statistic. Associations between census socioeconomic indicators and pneumonia incidence rates were analyzed using generalized linear models.</p> <p>Results</p> <p>From May, 2007 to May, 2009, chest radiographs were obtained from 11 521 children with clinical pneumonia; 3955 episodes were classified as radiologically-confirmed. Incidence rates were significantly higher in very low income areas (4825.2 per 10⁵) compared to high income areas (1637.3 per 10⁵). Spatial analysis identified clustering of confirmed pneumonia in Western (RR 1.78; p = 0.001) and Southeast (RR 1.46; p = 0.001) regions of the city, and clustering of hospitalized pneumonia in the Western region (RR 1.69; p = 0.001). Lower income households and illiteracy were associated with pneumonia incidence.</p> <p>Conclusions</p> <p>In infants the risk of developing pneumonia is inversely associated with the head of household income and with the woman educational level. Areas with deprived socioeconomic conditions had higher incidence of pneumonia and should be targeted for high vaccination coverage.</p

The Childhood Acute Illness and Nutrition (CHAIN) network nested case-cohort study protocol: a multi-omics approach to understanding mortality among children in sub-Saharan Africa and South Asia

Introduction: Many acutely ill children in low- and middle-income settings have a high risk of mortality both during and after hospitalisation despite guideline-based care. Understanding the biological mechanisms underpinning mortality may suggest optimal pathways to target for interventions to further reduce mortality. The Childhood Acute Illness and Nutrition (CHAIN) Network ( www.chainnnetwork.org) Nested Case-Cohort Study (CNCC) aims to investigate biological mechanisms leading to inpatient and post-discharge mortality through an integrated multi-omic approach. Methods and analysis; The CNCC comprises a subset of participants from the CHAIN cohort (1278/3101 hospitalised participants, including 350 children who died and 658 survivors, and 270/1140 well community children of similar age and household location) from nine sites in six countries across sub-Saharan Africa and South Asia. Systemic proteome, metabolome, lipidome, lipopolysaccharides, haemoglobin variants, toxins, pathogens, intestinal microbiome and biomarkers of enteropathy will be determined. Computational systems biology analysis will include machine learning and multivariate predictive modelling with stacked generalization approaches accounting for the different characteristics of each biological modality. This systems approach is anticipated to yield mechanistic insights, show interactions and behaviours of the components of biological entities, and help develop interventions to reduce mortality among acutely ill children. Ethics and dissemination. The CHAIN Network cohort and CNCC was approved by institutional review boards of all partner sites. Results will be published in open access, peer reviewed scientific journals and presented to academic and policy stakeholders. Data will be made publicly available, including uploading to recognised omics databases. Trial registration NCT03208725

Characterising paediatric mortality during and after acute illness in Sub-Saharan Africa and South Asia: a secondary analysis of the CHAIN cohort using a machine learning approach

Background A better understanding of which children are likely to die during acute illness will help clinicians and policy makers target resources at the most vulnerable children. We used machine learning to characterise mortality in the 30-days following admission and the 180-days after discharge from nine hospitals in low and middle-income countries (LMIC). Methods A cohort of 3101 children aged 2–24 months were recruited at admission to hospital for any acute illness in Bangladesh (Dhaka and Matlab Hospitals), Pakistan (Civil Hospital Karachi), Kenya (Kilifi, Mbagathi, and Migori Hospitals), Uganda (Mulago Hospital), Malawi (Queen Elizabeth Central Hospital), and Burkina Faso (Banfora Hospital) from November 2016 to January 2019. To record mortality, children were observed during their hospitalisation and for 180 days post-discharge. Extreme gradient boosted models of death within 30 days of admission and mortality in the 180 days following discharge were built. Clusters of mortality sharing similar characteristics were identified from the models using Shapley additive values with spectral clustering. Findings Anthropometric and laboratory parameters were the most influential predictors of both 30-day and post-discharge mortality. No WHO/IMCI syndromes were among the 25 most influential mortality predictors of mortality. For 30-day mortality, two lower-risk clusters (N = 1915, 61%) included children with higher-than-average anthropometry (1% died, 95% CI: 0–2), and children without signs of severe illness (3% died, 95% CI: 2–4%). The two highest risk 30-day mortality clusters (N = 118, 4%) were characterised by high urea and creatinine (70% died, 95% CI: 62–82%); and nutritional oedema with low platelets and reduced consciousness (97% died, 95% CI: 92–100%). For post-discharge mortality risk, two low-risk clusters (N = 1753, 61%) were defined by higher-than-average anthropometry (0% died, 95% CI: 0–1%), and gastroenteritis with lower-than-average anthropometry and without major laboratory abnormalities (0% died, 95% CI: 0–1%). Two highest risk post-discharge clusters (N = 267, 9%) included children leaving against medical advice (30% died, 95% CI: 25–37%), and severely-low anthropometry with signs of illness at discharge (46% died, 95% CI: 34–62%). Interpretation WHO clinical syndromes are not sufficient at predicting risk. Integrating basic laboratory features such as urea, creatinine, red blood cell, lymphocyte and platelet counts into guidelines may strengthen efforts to identify high-risk children during paediatric hospitalisations. Funding Bill & Melinda Gates Foundation OPP1131320

Isolation of a euryhaline microalgal strain, Tetraselmis sp CTP4, as a robust feedstock for biodiesel production

Bioprospecting for novel microalgal strains is key to improving the feasibility of microalgae-derived biodiesel production. Tetraselmis sp. CTP4 (Chlorophyta, Chlorodendrophyceae) was isolated using fluorescence activated cell sorting (FACS) in order to screen novel lipid-rich microalgae. CTP4 is a robust, euryhaline strain able to grow in seawater growth medium as well as in non-sterile urban wastewater. Because of its large cell size (9-22 mu m), CTP4 settles down after a six-hour sedimentation step. This leads to a medium removal efficiency of 80%, allowing a significant decrease of biomass dewatering costs. Using a two-stage system, a 3-fold increase in lipid content (up to 33% of DW) and a 2-fold enhancement in lipid productivity (up to 52.1 mg L-1 d(-1)) were observed upon exposure to nutrient depletion for 7 days. The biodiesel synthesized from the lipids of CTP4 contained high levels of oleic acid (25.67% of total fatty acids content) and minor amounts of polyunsaturated fatty acids with >= 4 double bonds (< 1%). As a result, this biofuel complies with most of the European (EN14214) and American (ASTM D6751) specifications, which commonly used microalgal feedstocks are usually unable to meet. In conclusion, Tetraselmis sp. CTP4 displays promising features as feedstock with lower downstream processing costs for biomass dewatering and biodiesel refining