7 research outputs found

    Maternal risk factors associated with term low birth weight in India: A review

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    Low birth weight is one of the leading factors for infant morbidity and mortality. To a large extent affect, various maternal risk factors are associated with pregnancy outcomes by increasing odds of delivering an infant with low birth weight. Despite this association, understanding the maternal risk factors affecting term low birth weight has been a challenging task. To date, limited studies have been conducted in India that exert independent magnitude of these effects on term low birth weight. The aim of this review is to examine the current knowledge of maternal risk factors that contribute to term low birth weight in the Indian population. In order to identify the potentially relevant articles, an extensive literature search was conducted using PubMed, Goggle Scholar and IndMed databases (1993 – Dec 2020). Our results indicate that maternal age, educational status, socio-economic status, ethnicity, parity, pre-pregnancy weight, maternal stature, maternal body mass index, obstetric history, maternal anaemia, gestational weight gain, short pregnancy outcome, hypertension during pregnancy, infection, antepartum haemorrhage, tobacco consumption, maternal occupation, maternal psychological stress, alcohol consumption, antenatal care and mid-upper arm circumference have all independent effects on term low birth weight in the Indian population. Further, we argue that exploration for various other dimensions of maternal factors and underlying pathways can be useful for a better understanding of how it exerts independent association on term low birth weight in the Indian sub-continent

    Early Prediction of Hemodynamic Shock in Pediatric Intensive Care Units With Deep Learning on Thermal Videos

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    Shock is one of the major killers in intensive care units, and early interventions can potentially reverse it. In this study, we advance a noncontact thermal imaging modality for continuous monitoring of hemodynamic shock working on 1,03,936 frames from 406 videos recorded longitudinally upon 22 pediatric patients. Deep learning was used to preprocess and extract the Center-to-Peripheral Difference (CPD) in temperature values from the videos. This time-series data along with the heart rate was finally analyzed using Long-Short Term Memory models to predict the shock status up to the next 6 h. Our models achieved the best area under the receiver operating characteristic curve of 0.81 ± 0.06 and area under the precision-recall curve of 0.78 ± 0.05 at 5 h, providing sufficient time to stabilize the patient. Our approach, thus, provides a reliable shock prediction using an automated decision pipeline that can provide better care and save lives

    A step toward healthy newborn: An assessment of 2 years' admission pattern and treatment outcomes of neonates admitted in special newborn care units of Gujarat

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    Context: Facility Based Newborn Care (FBNC) is a key strategy to improve child survival, especially in newborn care where neonatal mortality rate (NMR) is stagnant in declining. Gujarat has achieved considerable amount of reduction in child deaths, but neonatal health requires attention. The study was aimed to assess the admission pattern of Special Newborn Care Units (SNCUs) which supports decision-making. Settings and Design: A cross-sectional descriptive analysis was done from secondary data of the SNCU reports on the aspects of admission patterns, morbidity, and mortality pattern. The reports had been analyzed on various critical variables. Results: In 2015–2016, Gujarat has operationalized forty SNCUs by saturating each district with at least one SNCU. The study found near proportions of (53%) inborn – (47%) outborn admission and 44% admission of female. Out of 69,662 admissions, 67% were discharged, 16% died, 10% leaving against medical advice, and 7% referred to higher centers. Major reasons for admission were respiratory distress syndrome (RDS) (22%) and infection (21%). Similar pattern in mortality found as final diagnosis of deaths was RDS (23%) and infection (21%). The proportion of neonatal deaths in outborn was high compared to inborn. Conclusion: Strengthening of FBNC is essential to address neonatal mortality. NMR is of prime focus because the health interventions needed to tackle NMR differ from those needed for infant mortality rate and under-five mortality rate. This accentuates the need for focused attention on facility- and community-based child health interventions along with quality maternal health services and robust referral mechanisms to all delivery points

    Persistently Elevated Level of IL-8 in Chlamydia trachomatis Infected HeLa 229 Cells is Dependent on Intracellular Available Iron

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    Chlamydia trachomatis is a leading cause of sexually transmitted infection worldwide and responsible for myriad of immunopathological changes associated with reproductive health. Delayed secretion of proinflammatory chemokine interleukin (IL)-8 is a hallmark of chlamydial infection and is dependent on chlamydial growth. We examined the effect of iron chelators on IL-8 production in HeLa 229 (cervix epitheloid cell, CCL2) cells infected with C. trachomatis. IL-8 production was induced by Iron chelator DFO and Mimosine, however, synergy with chlamydial infection was obtained with DFO only. Temporal expression of proinflammatory secreted cytokines IL-1beta, TNF-alpha, and IL-8 did not show synchrony in Chlamydia trachomatis infected cells. Secretion of IL-8 from Hela cells infected with C. trachomatis was not dependent on IL-1 beta and TNF-alpha induction. These results indicate towards involvement of iron in chlamydia induced IL-8 production

    Persistently Elevated Level of IL-8 in Chlamydia trachomatis Infected HeLa 229 Cells is Dependent on Intracellular Available Iron

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    Chlamydia trachomatis is a leading cause of sexually transmitted infection worldwide and responsible for myriad of immunopathological changes associated with reproductive health. Delayed secretion of proinflammatory chemokine interleukin (IL)-8 is a hallmark of chlamydial infection and is dependent on chlamydial growth. We examined the effect of iron chelators on IL-8 production in HeLa 229 (cervix epitheloid cell, CCL2) cells infected with C. trachomatis. IL-8 production was induced by Iron chelator DFO and Mimosine, however, synergy with chlamydial infection was obtained with DFO only. Temporal expression of proinflammatory secreted cytokines IL-1beta, TNF-alpha, and IL-8 did not show synchrony in Chlamydia trachomatis infected cells. Secretion of IL-8 from Hela cells infected with C. trachomatis was not dependent on IL-1 beta and TNF- alpha induction. These results indicate towards involvement of iron in chlamydia induced IL-8 production

    SymPy: symbolic computing in Python

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    Článek pojednává o architektuře SymPy, popisuje vlastnosti tohoto softwaru a vybrané pod-moduly.SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy
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