Browsing by Subject "newborns"

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    FETAL AND NEONATAL FACTORS INFLUENCING FREE CARNITINE
    (Office of the Vice Chancellor for Research, 2012-04-13) Winchester, Paul D.; Proctor, Cathy; Pandya, Janit; Ying, Jun
    Background: Free Carnitine (FC) is now measured routinely in new-borns in Indiana. Studies with small numbers have suggested that FC may be dependent on fetal and neonatal factors. Objective: Our objective was to compare FC levels with various fetal and neonatal factors. Our goal was to establish normative data by gestation in a very large cohort (Indiana State) and to use these carnitine values to develop hypotheses about FC in fetal life and disease. Design/Methods: Indiana State Health Department FC values (tandem mass spec) and demographic variables were obtained for the years 2005-2010. Gender, race, birth weight, gestation, NICU admission, age at collec-tion information was also evaluated. Multivariate fixed effect models were used to compare carnitine values with independent variables. Results: The number of newborns analyzed was 459,932. FC levels were lowest in babies with gestational age 37-40 weeks and higher in both preterm and post-term babies (Table 1). Table 1. Free Carnitine vs. Gestation Gestation FC mean SE mean Gestation FC mean SE mean 23 40.88 1.00 33 39.81 0.28 24 39.86 0.73 34 38.28 0.22 25 42.61 0.69 35 37.14 0.19 26 42.77 0.64 36 36.37 0.17 27 42.65 0.63 37 35.76 0.20 28 42.47 0.57 38 35.11 0.22 29 43.51 0.53 39 35.04 0.19 30 40.4 0.46 40 35.36 0.07 31 41.96 0.41 41 38.58 0.48 32 40.65 0.34 42 40.96 1.52 FC levels were lowest in babies with birth weights between 3150-4050g (34.390.07) and higher in groups with both lower (<2500g;39.540.08**, 2500-2850g;35.82 0.08**, 2850-3150g;34.890.08) and higher weights (>4500g;35.660.1**). FC levels were lowest when collected be-tween 24-48 hours (34.290.05) and higher either before (36.930.1**) or after that time (2-3,3-4,4-5,>5days;34.960.06**,36.210.11**,37.320.15**,36.80.14**). Female, white, non singleton and non NICU babies had significantly lower FC levels (Table 2). Table 2. Free Carnitine vs. Demographics Category FC mean SE mean Male 39.40 0.08 Female 36.60 0.08** White 37.16 0.06 Black 37.34 0.08* Asian 39.12 0.18** Other 38.39 0.1** Singleton 38.30 0.06 Multiple 37.70 0.11** NICU 40.46 0.09 Non-NICU 35.55 0.07** *&** are p<0.05 & <0.01 vs. comp group Conclusions: FC values are significantly influenced by gestation, gender, race, time of collection, NICU admission, multiple birth and birth weight. Generally, factors which increased mortality and morbidity (immaturity, post maturity, low birth weight, male gender, black race) were associated with higher FC values. These data will be used to construct normative curves and may be useful in predicting neonatal outcomes (Figure 1). 1Biostatistics, University of Cincinnati Medical Center, Cincinnati, Ohio, 45267
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    The NeoWarm biomedical device: Assessment of feasibility and cultural acceptability, identification of potential barriers and challenges, and stakeholder mapping
    (Office of the Vice Chancellor for Research, 2016-04-08) Watts, Thomasina; Siddiki, Furhan; Savita, Aakash
    Introduction: Across the globe, approximately 4 million newborns die each year; complications from hypothermia underlie many of these deaths. Regions with fewer resources for neonatal care have higher rates of hypothermia­related death. Kangaroo Mother Care (KMC) is the practice of prolonged skin­to­skin contact to prevent hypothermia among small and premature infants. KMC is cost effective, and proven to reduce hypothermia; however, KMC programs are often discontinued or fail to expand. A built prototype of a biomedical device, called NeoWarm, has been developed to augment KMC initiatives. Identification of potential barriers and facilitators to adoption the NeoWarm technology is urgently needed. Methods: In order to assess the feasibility of NeoWarm, and to identify current barriers to implementation of KMC and NeoWarm, a comprehensive literature review was conducted. Key barriers and facilitators to existing KMC programs in sub­Saharan Africa, Asia, and Latin America were identified. Stakeholder mapping and analysis in relation to the NeoWarm device for three “target countries” within each of these global regions was performed. Potential stakeholders were identified and categorically ranked in terms of influence and relevance. Results: Three key barriers to KMC programs were identified. These included: unacceptability among male stakeholders; lack of support from health care providers and insufficient health infrastructure, leading to fears of tuberculosis and other infections spreading in crowded KMC wards. Comprehensive stakeholder mapping for Kenya, India, and Guatemala revealed a complex web of potential influencers and regulatory processes for adoption of NeoWarm technology. Conclusion: The NeoWarm device may support increased acceptance of KMC among male stakeholders and some health care providers; however, the concerns regarding spread of tuberculosis among KMC mother­baby pairs was an unexpected finding, which will significantly inform subsequent NeoWarm development and testing. Stakeholder mapping and analysis revealed many potential NeoWarm partners within each region whom had not been previously identified.