Comparison of the Value of Nursing Work Environments in Hospitals Across Different Levels of Patient Risk

Importance The literature suggests that hospitals with better nursing work environments provide better quality of care. Less is known about value (cost vs quality). Objectives To test whether hospitals with better nursing work environments displayed better value than those with worse nursing environments and to determine patient risk groups associated with the greatest value. Design, Setting, and Participants A retrospective matched-cohort design, comparing the outcomes and cost of patients at focal hospitals recognized nationally as having good nurse working environments and nurse-to-bed ratios of 1 or greater with patients at control group hospitals without such recognition and with nurse-to-bed ratios less than 1. This study included 25 752 elderly Medicare general surgery patients treated at focal hospitals and 62 882 patients treated at control hospitals during 2004-2006 in Illinois, New York, and Texas. The study was conducted between January 1, 2004, and November 30, 2006; this analysis was conducted from April to August 2015. Exposures Focal vs control hospitals (better vs worse nursing environment). Main Outcomes and Measures Thirty-day mortality and costs reflecting resource utilization. Results This study was conducted at 35 focal hospitals (mean nurse-to-bed ratio, 1.51) and 293 control hospitals (mean nurse-to-bed ratio, 0.69). Focal hospitals were larger and more teaching and technology intensive than control hospitals. Thirty-day mortality in focal hospitals was 4.8% vs 5.8% in control hospitals (P \u3c .001), while the cost per patient was similar: the focal-control was −$163 (95$542 to $215; P = .40), suggesting better value in the focal group. For the focal vs control hospitals, the greatest mortality benefit (17.3$941 per patient ($53 701 vs$52 760; P = .25). The greatest difference in value between focal and control hospitals appeared in patients in the second-highest risk quintile, with mortality of 4.2% vs 5.8% (P \u3c .001), with a nonsignificant cost difference of −$862 ($33 513 vs $34 375; P = .12). Conclusions and Relevance Hospitals with better nursing environments and above-average staffing levels were associated with better value (lower mortality with similar costs) compared with hospitals without nursing environment recognition and with below-average staffing, especially for higher-risk patients. These results do not suggest that improving any specific hospital’s nursing environment will necessarily improve its value, but they do show that patients undergoing general surgery at hospitals with better nursing environments generally receive care of higher value

Crop Updates 2000 - Oilseeds

This session covers seventeen papers from different authors: Introduction, Paul Carmody, Centre for Cropping Systems CANOLA AGRONOMY 2. Genotype, location and year influence the quality of canola grown across southern Australia, PingSi1, Rodney Mailer2, Nick Galwey1 and David Turner1, 1Plant Sciences, Faculty of Agriculture, The University of Western Australia, 2Agricultural Research Institute, New South Wales Agriculture 3. Development of Pioneer® Canola varieties for Australian market,Kevin Morthorpe, StephenAddenbrooke, Pioneer Hi-Bred Australia Pty Ltd 4. Canola, Erucic Acid, Markets and Agronomic Implications, Peter Nelson, The Grain Pool of Western Australia 5. The control of Capeweed in Clearfield Production System for Canola, Mike Jackson and ScottPaton, Cyanamid Agriculture Pty Ltd 6. Responsiveness of Canola to Soil Potassium Levels: How Low Do We Have To Go? Ross Brennan, Noeleen Edwards, Mike Bolland and Bill Bowden,Agriculture Western Australia 7. Adaption of Indian Mustard (Brassica juncea) in the Mediterranean Environment of South Western Australia, C.P. Gunasekera1, L.D. Martin1, G.H. Walton2 and K.H.M. Siddique2 1Muresk Institute of Agriculture, Curtin University of Technology, Northam, 2Agriculture Western Australia 8. Physiological Aspects of Drought Tolerance in Brassica napus and B.juncea, Sharon R. Niknam and David W. Turner, Plant Sciences, Faculty of Agriculture, The University of Western Australia 9. Cross resistance of chlorsulfuron-resistant wild radish to imidazolinones, Abul Hashem, Harmohinder Dhammu and David Bowran, Agriculture Western Australia 10. Canola Variety and PBR Update 2000, From The Canola Association of Western Australia 11. Development of a canola ideotype for the low rainfall areas of the western Australian wheat belt, Syed H. Zaheer, Nick W. Galwey and David W. Turner, Faculty of Agriculture, The University of Western Australia DISEASE MANAGEMENT 12. Evaluation of fungicides for the management of blackleg in canola, Ravjit Khangura and Martin J. Barbetti, Agriculture Western Australia 13. Impact-IFÒ: Intergral in the control of Blackleg, Peter Carlton, Trials Coordinator, Elders Limited 14. Forecasting aphid and virus risk in canola, Debbie Thackray, Jenny Hawkes and Roger Jones, Agriculture Western Australia and Centre for Legumes in Mediterranean Agriculture 15. Beet western yellow virus in canola: 1999 survey results, wild radish weed reservoir and suppression by insecticide, Roger Jones and Brenda Coutts, Agriculture Western Australia 16. Are canola crops resilient to damage by aphids and diamond back moths? Françoise Berlandier, Agriculture Western Australia ECONOMIC OUTLOOK 17. Outlook for prices and implications for rotations, Ross Kingwell1,2, Michael O’Connell1 and Simone Blennerhasset11Agriculture Western Australia 2University of Western Australi

Hyperbaric treatment for children with autism: a multicenter, randomized, double-blind, controlled trial

<p>Abstract</p> <p>Background</p> <p>Several uncontrolled studies of hyperbaric treatment in children with autism have reported clinical improvements; however, this treatment has not been evaluated to date with a controlled study. We performed a multicenter, randomized, double-blind, controlled trial to assess the efficacy of hyperbaric treatment in children with autism.</p> <p>Methods</p> <p>62 children with autism recruited from 6 centers, ages 2–7 years (mean 4.92 ± 1.21), were randomly assigned to 40 hourly treatments of either hyperbaric treatment at 1.3 atmosphere (atm) and 24% oxygen ("treatment group", n = 33) or slightly pressurized room air at 1.03 atm and 21% oxygen ("control group", n = 29). Outcome measures included Clinical Global Impression (CGI) scale, Aberrant Behavior Checklist (ABC), and Autism Treatment Evaluation Checklist (ATEC).</p> <p>Results</p> <p>After 40 sessions, mean physician CGI scores significantly improved in the treatment group compared to controls in overall functioning (p = 0.0008), receptive language (p < 0.0001), social interaction (p = 0.0473), and eye contact (p = 0.0102); 9/30 children (30%) in the treatment group were rated as "very much improved" or "much improved" compared to 2/26 (8%) of controls (p = 0.0471); 24/30 (80%) in the treatment group improved compared to 10/26 (38%) of controls (p = 0.0024). Mean parental CGI scores significantly improved in the treatment group compared to controls in overall functioning (p = 0.0336), receptive language (p = 0.0168), and eye contact (p = 0.0322). On the ABC, significant improvements were observed in the treatment group in total score, irritability, stereotypy, hyperactivity, and speech (p < 0.03 for each), but not in the control group. In the treatment group compared to the control group, mean changes on the ABC total score and subscales were similar except a greater number of children improved in irritability (p = 0.0311). On the ATEC, sensory/cognitive awareness significantly improved (p = 0.0367) in the treatment group compared to the control group. Post-hoc analysis indicated that children over age 5 and children with lower initial autism severity had the most robust improvements. Hyperbaric treatment was safe and well-tolerated.</p> <p>Conclusion</p> <p>Children with autism who received hyperbaric treatment at 1.3 atm and 24% oxygen for 40 hourly sessions had significant improvements in overall functioning, receptive language, social interaction, eye contact, and sensory/cognitive awareness compared to children who received slightly pressurized room air.</p> <p>Trial Registration</p> <p>clinicaltrials.gov NCT00335790</p

Hybrid finite-volume–finite-element scheme for 3D simulation of thermal plasma arc configuration

The plasma dynamics in a three-dimensional free-burning arc configuration are studied using an iterative hybrid finite-volume–finite-element scheme. In this scheme, Navier–Stokes equations are solved with a classical finite volume approach. It is a conservative method that is suitable for solving conservation equations. In addition, a nodal finite element analysis is used to solve Maxwell’s equations for the scalar and vector potentials. The finite-volume and finite-element modules are verified against well-known simple problems. The plasma is considered an incompressible fluid in chemical and thermal equilibrium or local thermodynamic equilibrium. The profiles of fluid and electromagnetic characteristics are depicted for a total current equal to 200 A. The results of this simulation method are in agreement with experimental and numerical predictions

Graph representation learning based on deep generative gaussian mixture models

Graph representation learning is an effective tool for facilitating graph analysis with machine learning methods. Most GNNs, including Graph Convolutional Networks (GCN), Graph Recurrent Neural Networks (GRNN), and Graph Auto-Encoders (GAE), employ vectors to represent nodes in a deterministic way without exploiting the uncertainty in hidden variables. Deep generative models are combined with GAE in the Variational Graph Auto-Encoder (VGAE) framework to address this issue. While traditional VGAE-based methods can capture hidden and hierarchical dependencies in latent spaces, they are limited by the data’s multimodality. Here, we propose the Gaussian Mixture Model (GMM) to model the prior distribution in VGAE. Furthermore, an adversarial regularization is incorporated into the proposed approach to ensure the fruitful impact of the latent representations on the results. We demonstrate the performance of the proposed method on clustering and link prediction tasks. Our experimental results on real datasets show remarkable performance compared to state-of-the-art methods

Improved solubility model for pure gas and binary mixture of CO2-H2S in water: A geothermal case study with total reinjection

Geothermal energy is acknowledged globally as a renewable resource, which, unlike solar, wind or wave energy, can be continuously exploited. The geothermal fluids usually have some acid gas content, which needs to be precisely taken into account when predicting the actual potential of a power plant in dealing with an effective reinjection. One of the key parameters to assess is the solubility of the acid gas, as it influences the thermodynamic conditions (saturation pressure and temperature) of the fluid. Therefore, an enhanced solubility model for the CO2-H2S-water system is developed in this study, based on the mutual solubility of gases. The model covers a wide range of pressures and temperatures. The genetic algorithm is employed to calculate the correlation constants and corresponding solubility values of both CO2 and H2S as functions of pressure, temperature and the balance of the gas. The results are validated against previously published models and experimental data available in the literature. The proposed model estimates the pure gas solubility, which is also a feature of other models. The more innovative feature of the model is the solubility estimation of each CO2 or H2S in simultaneous presence, such as when the binary gas is injected into the pure water of the geothermal reinjection well. The proposed solubility model fits well with the available experimental data, with a mean deviation lower than 0.2%