Implementation of the Resuscitation Quality Improvement Program in a System of Hospitals: A Map for Success

Introduction: To prevent cardiopulmonary resuscitation (CPR) skills decay, the International Consensus on Resuscitation suggested retraining every three to six months. Current retraining practices nationwide exceed one to two years, suggesting that clinical staff\u27s CPR skills are rarely at optimum proficiency. The Resuscitation Quality Improvement (RQI) program offers skills decay prevention through quarterly sessions. This manuscript addresses the challenges and opportunities of implementing the RQI program in a hospital system to increase CPR skills quality and cost-savings. Purpose & Methods: This manuscript describes the challenges and opportunities of implementing the RQI program as a quality improvement initiative in a system of hospitals and serves as a guide for implementation at similar institutions considering the adoption of RQI-basic life support (BLS). Results: Multiple successes and challenges were identified during the program implementation. Challenges included learning management system integration and RQI station damage. Successes included a 47% improvement in clinical staff’s psychomotor CPR skills (i.e., compressions, ventilation, and chest compression fraction) and a $1.6 million cost avoidance for the system of hospitals. The RQI program implementation significantly increased the psychomotor skills of the RQI users, satisfaction, staff productivity, and cost avoidance. Discussion: Although implementing the RQI in a system of hospitals brought many challenges, the overall improvement in staff CPR skills and cost-avoidance superseded the cost-benefit analysis and justified its implementation. Implementing this program promotes superior CPR skills that could improve patient outcomes

Capturing optically important constituents and properties in a marine biogeochemical and ecosystem model

We present a numerical model of the ocean that couples a three-stream radiative transfer component with a marine biogeochemical–ecosystem component in a dynamic three-dimensional physical framework. The radiative transfer component resolves the penetration of spectral irradiance as it is absorbed and scattered within the water column. We explicitly include the effect of several optically important water constituents (different phytoplankton functional types; detrital particles; and coloured dissolved organic matter, CDOM). The model is evaluated against in situ-observed and satellite-derived products. In particular we compare to concurrently measured biogeochemical, ecosystem, and optical data along a meridional transect of the Atlantic Ocean. The simulation captures the patterns and magnitudes of these data, and estimates surface upwelling irradiance analogous to that observed by ocean colour satellite instruments. We find that incorporating the different optically important constituents explicitly and including spectral irradiance was crucial to capture the variability in the depth of the subsurface chlorophyll a (Chl a) maximum. We conduct a series of sensitivity experiments to demonstrate, globally, the relative importance of each of the water constituents, as well as the crucial feedbacks between the light field, the relative fitness of phytoplankton types, and the biogeochemistry of the ocean. CDOM has proportionally more importance at attenuating light at short wavelengths and in more productive waters, phytoplankton absorption is relatively more important at the subsurface Chl a maximum, and water molecules have the greatest contribution when concentrations of other constituents are low, such as in the oligotrophic gyres. Scattering had less effect on attenuation, but since it is important for the amount and type of upwelling irradiance, it is crucial for setting sea surface reflectance. Strikingly, sensitivity experiments in which absorption by any of the optical constituents was increased led to a decrease in the size of the oligotrophic regions of the subtropical gyres: lateral nutrient supplies were enhanced as a result of decreasing high-latitude productivity. This new model that captures bio-optical feedbacks will be important for improving our understanding of the role of light and optical constituents on ocean biogeochemistry, especially in a changing environment. Further, resolving surface upwelling irradiance will make it easier to connect to satellite-derived products in the future

What is the best workup for hypocalcemia?

Unexplained hypocalcemia can usually be diagnosed by a limited number of serum tests when the cause isn't obvious from the history (recent neck surgery or renal failure): calcium corrected for serum albumin); creatinine; phosphorus; magnesium; parathyroid hormone (PTH). The most common causes, categorized according to the results of these tests, are (strength of recommendation: C, expert opinion, case series, and physiologic principles): high PTH, high phosphorus, and high creatinine: renal failure; high PTH, low or normal phosphorus, and normal creatinine: vitamin D deficiency or pancreatitis; low PTH, high phosphorus, and normal creatinine: inadequate parathyroid gland function or hypomagnesemia

Absorption and fluorescence properties of chromophoric dissolved organic matter of the eastern Bering Sea in the summer with special reference to the influence of a cold pool

The absorption and fluorescence properties of chromophoric dissolved organic matter (CDOM) are reported for the inner shelf, slope waters and outer shelf regions of the eastern Bering Sea during the summer of 2008, when a warm, thermally stratified surface mixed layer lay over a cold pool (< 2 °C) that occupied the entire middle shelf. CDOM absorption at 355 nm (<i>a</i>_g355) and its spectral slope (<i>S</i>) in conjunction with excitation–emission matrix (EEM) fluorescence and parallel factor analysis (PARAFAC) revealed large variability in the characteristics of CDOM in different regions of the Bering Sea. PARAFAC analysis aided in the identification of three humic-like (components one, two and five) and two protein-like (a tyrosine-like component three, and a tryptophan-like component four) components. In the extensive shelf region, average absorption coefficients at 355 nm (<i>a</i>_g355, m⁻¹) and DOC concentrations (μM) were highest in the inner shelf (0.342 ± 0.11 m⁻¹, 92.67 ± 14.60 μM) and lower in the middle (0.226 ± 0.05 m⁻¹, 78.38 ± 10.64 μM) and outer (0.185 ± 0.05 m⁻¹, 79.24 ± 18.01 μM) shelves, respectively. DOC concentrations, however were not significantly different, suggesting CDOM sources and sinks to be uncoupled from DOC. Mean spectral slopes <i>S</i> were elevated in the middle shelf (24.38 ± 2.25 μm⁻¹) especially in the surface waters (26.87 ± 2.39 μm⁻¹) indicating high rates of photodegradation in the highly stratified surface mixed layer, which intensified northwards in the northern middle shelf likely contributing to greater light penetration and to phytoplankton blooms at deeper depths. The fluorescent humic-like components one, two, and five were most elevated in the inner shelf most likely from riverine inputs. Along the productive "green belt" in the outer shelf/slope region, absorption and fluorescence properties indicated the presence of fresh and degraded autochthonous DOM. Near the Unimak Pass region of the Aleutian Islands, low DOC and <i>a</i>_g355 (mean 66.99 ± 7.94 μM; 0.182 ± 0.05 m⁻¹) and a high <i>S</i> (mean 25.95 ± 1.58 μm⁻¹) suggested substantial photobleaching of the Alaska Coastal Water, but high intensities of humic-like and protein-like fluorescence suggested sources of fluorescent DOM from coastal runoff and glacier meltwaters during the summer. The spectral slope <i>S</i> vs. <i>a</i>_g355 relationship revealed terrestrial and oceanic end members along with intermediate water masses that were modeled using nonlinear regression equations that could allow water mass differentiation based on CDOM optical properties. Spectral slope <i>S</i> was negatively correlated (<i>r</i>² = 0.79) with apparent oxygen utilization (AOU) for waters extending from the middle shelf into the deep Bering Sea indicating increasing microbial alteration of CDOM with depth. Although our data show that the CDOM photochemical environment of the Bering Sea is complex, our current information on its optical properties will aid in better understanding of the biogeochemical role of CDOM in carbon budgets in relation to the annual sea ice and phytoplankton dynamics, and to improved algorithms of ocean color remote sensing for this region

An Interactive Narrative Platform for Story Understanding Experiments

Interactive Narratives are systems that use automated narrative generation techniques to create multiple story variants which can be shown to an audience, as virtual narratives, using cinematic staging techniques. The focus of previous research has included aspects such as the quality of automatically generated narratives and the way in which audiences respond to them. However in this work we have developed a mechanism for control of interactive narratives that supports their use in experiments to assess story understanding. This is implemented in our demonstration system, which features two parts: an interface that allows high-level specification of criteria for story understanding experiments; and a participant interface in which virtual narratives, conforming to the experimental design, are presented as 3D visualizations. The virtual narrative is based on a pre-existing children’s story, and features a cast of virtual characters

Theology, News and Notes - Vol. 41, No. 02

Theology News & Notes was a theological journal published by Fuller Theological Seminary from 1954 through 2014.https://digitalcommons.fuller.edu/tnn/1120/thumbnail.jp

Expanding understanding of optical variability in Lake Superior with a 4-year dataset

Lake Superior is one of the largest freshwater lakes on our planet, but few optical observations have been made to allow for the development and validation of visible spectral satellite remote sensing products. The dataset described here focuses on coincidently observing inherent and apparent optical properties along with biogeochemical parameters. Specifically, we observe remote sensing reflectance, absorption, scattering, backscattering, attenuation, chlorophyll concentration, and suspended particulate matter over the ice-free months of 2013&ndash;2016. The dataset substantially increases the optical knowledge of the lake. In addition to visible spectral satellite algorithm development, the dataset is valuable for characterizing the variable light field, particle, phytoplankton, and colored dissolved organic matter distributions, and helpful in food web and carbon cycle investigations. The compiled data can be freely accessed at https://seabass.gsfc.nasa.gov/archive/URI/Mouw/LakeSuperior/

Impact of phytoplankton community size on a linked global ocean optical and ecosystem model

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 89 (2012): 61-75, doi:10.1016/j.jmarsys.2011.08.002.We isolated the effect phytoplankton cell size has on varying remote sensing reflectance spectra (Rrs(λ)) in the presence of optically active constituents by using optical and radiative transfer models linked in an offline diagnostic calculation to a global biogeochemical/ecosystem/circulation model with explicit phytoplankton size classes. Two case studies were carried out, each with several scenarios to isolate the effects of chlorophyll concentration, phytoplankton cell size, and size-varying phytoplankton absorption on Rrs(λ). The goal of the study was to determine the relative contribution of phytoplankton cell size and chlorophyll to overall Rrs(λ) and to understand where a standard band ratio algorithm (OC4) may under/overestimate chlorophyll due to Rrs(λ) being significantly affected by phytoplankton size. Phytoplankton cell size was found to contribute secondarily to Rrs(λ) variability and to amplify or dampen the seasonal cycle in Rrs(λ), driven by chlorophyll. Size and chlorophyll were found to change in phase at low to mid-latitudes, but were anti-correlated or poorly correlated at high latitudes. Phytoplankton size effects increased model calculated Rrs(443) in the subtropical ocean during local spring through early fall months in both hemispheres and decreased Rrs(443) in the Northern Hemisphere high latitude regions during local summer to fall months. This study attempts to tease apart when/where variability about the OC4 relationship may be associated with cell size variability. The OC4 algorithm may underestimate [Chl] when the fraction of microplankton is elevated, which occurs in the model simulations during local spring/summer months at high latitudes in both hemispheres.Funding for this study came from a NASA Earth and Space Science Fellowship and University of Rhode Island Graduate School Oceanography Alumni Fellowship, both awarded to C. Mouw. The CCSM-3 BEC simulations were generated with support from NASA Ocean Biology and Biogeochemistry Program (NNX07AL80G) and the NSF Center for Microbial Oceanography Research and Education (C-MORE, EF-0424599)

Application of the Beer–Lambert Model to Attenuation of Photosynthetically Active Radiation in a Shallow, Eutrophic Lake

Models of primary production in aquatic systems must include a means to estimate subsurface light. Such models often use the Beer–Lambert law, assuming exponential attenuation of light with depth. It is further assumed that the diffuse attenuation coefficient may be estimated as a summation of scattering/absorbing constituent concentrations multiplied by their respective specific attenuation coefficients. While theoretical deviations from these assumptions have been documented, it is useful to consider the empirical performance of this common approach. Photosynthetically active radiation (PAR) levels and water quality conditions were recorded weekly from six to eight monitoring stations in western Lake Erie between 2012 and 2016. Exponential PAR extinction models yielded a mean attenuation coefficient of 1.55 m (interquartile range = 0.74–1.90 m). While more complex light attenuation models are available, analysis of residuals indicated that the simple Beer–Lambert model is adequate for shallow, eutrophic waters similar to western Lake Erie (R2 > 0.9 for 96% of samples). Three groups of water quality variables were predictive of PAR attenuation: total and nonvolatile suspended particles, dissolved organic substances (dissolved organic carbon and chromophoric dissolved organic matter), and organic solids (volatile suspended solids and chlorophyll). Multiple regression models using these variables predicted 3–90% of the variability in PAR attenuation, with a median adjusted R2 = 0.86. Explanatory variables within these groups may substitute for each other while maintaining similar model performance, indicating that various combinations of water quality variables may be useful to predict PAR attenuation, depending on availability within a model framework or monitoring program.Key PointsThe Beer–Lambert law effectively models photosynthetically active radiation in western Lake Erie, despite some systematic deviationsField‐obtained water quality parameters can predict photosynthetically active radiation attenuation with a high degree of confidenceSuspended particle concentration is most predictive of photosynthetically active radiation attenuation in this turbid, eutrophic basinPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/1/wrcr23654_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/2/wrcr23654-sup-0001-2018WR023024-SI.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147097/3/wrcr23654.pd

Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOcean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are inter-compared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sum of sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among them exist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models show single annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.NASAEuropean Space Agency (ESA