作者:
Crawford, WilliamOffice of Policy
Centers for Medicare and Medicaid Services 200 Independence Avenue SW Washington DC 20021 United States MIT Sloan School of Management
Harvard-MIT Division of Health Sciences and Technology Children's Hospital Informatics Program United States
Objectives: To determine the effectiveness and safety of procedural sedation and analgesia (PSA) in a Canadian community emergency department (ED) staffed primarily by family physicians and to assess the role of capno...
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Objectives: To determine the effectiveness and safety of procedural sedation and analgesia (PSA) in a Canadian community emergency department (ED) staffed primarily by family physicians and to assess the role of capnometry monitoring in PSA. Methods: One hundred and sixty (160) consecutive procedural sedation cases were reviewed from the ED of a rural hospital in Huntsville, Ont. The ED is mainly staffed by family physicians who have received in-house training in PSA. Safety and effectiveness measures were extrapolated from a standardized PSA from by a blinded research assistant. Results: The mean age of the patient population was 33.6 years (standard deviation = 23.6). Fifty-four percent of the patients were male and 33% of the cases were pediatric. PSA medications included propofol (84%), fentanyl (51%) and midazolam (15%), and the procedural success rate was 95.6%. The adverse event (AE) rate was 18% and included apnea (10%), inadequate sedation (3%), bradycardia (2%), desaturation (1%), hypotension (1%) and bag-valve-mask use (1%). In those aged ≥65 years there was a greater incidence of apnea. There were no episodes of emesis and there were no intubations. A modified jaw thrust manoeuvre was used in 23% of the case. In the 64% of cases where capnometry was used, there was no association between its use and any AE measures. Conclusion: Procedural sedation was safe and effective in our environment. Capnometry recording did not appear to alter outcomes, although the data are incomplete.
One of the most important work group support issues is providing information about the context under which a group interacts. The goal of this paper is evaluating the influence of contextual information on the coopera...
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ISBN:
(纸本)142440164X
One of the most important work group support issues is providing information about the context under which a group interacts. The goal of this paper is evaluating the influence of contextual information on the cooperation level in group interactions supported by groupware. A laboratory case study was set up and carried out with this purpose
Computational analysis of natural language is often focused on the syntactic structure of language-often with no regard to the overall context and area of expertise of the analyzed text. In this paper, we present a me...
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ISBN:
(纸本)9525677001
Computational analysis of natural language is often focused on the syntactic structure of language-often with no regard to the overall context and area of expertise of the analyzed text. In this paper, we present a means of analyzing text documents from various areas of expertise to discover groups of thematically similar texts with no prior information about the topics. The presented results show how a relatively simple keyword analysis combined with a SOM projection can be very descriptive in terms of analyzing the contextual relationships between documents and their authors.
Research has been done in order to propose solutions that enhance interactions among participants and improve activity coordination in the meeting cycle. Some of these are related to pre-meeting phase conduction. We a...
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ISBN:
(纸本)142440164X
Research has been done in order to propose solutions that enhance interactions among participants and improve activity coordination in the meeting cycle. Some of these are related to pre-meeting phase conduction. We argue that collaboration could be enhanced if we supplied relevant context information through awareness mechanisms. This paper aims at evaluating context elements in an asynchronous Web-based pre-meeting application. As a result, a context framework is discussed in order to support awareness design in the meeting support applications domain
This article presents the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) for a pharmaceutical research problem. Designing drugs is a current problem in the pharmaceutical research domain....
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Background: Widespread availability of geographic information systems software has facilitated the use of disease mapping in academia, government and private sector. Maps that display the address of affected patients ...
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Starting with the work of Jaakkola and Haussler, a variety of approaches have been proposed for coupling domain-specific generative models with statistical learning methods. The link is established by a kernel functio...
Starting with the work of Jaakkola and Haussler, a variety of approaches have been proposed for coupling domain-specific generative models with statistical learning methods. The link is established by a kernel function which provides a similarity measure based inherently on the underlying model. In computational biology, the full promise of this framework has rarely ever been exploited, as most kernels are derived from very generic models, such as sequence profiles or hidden Markov models. Here, we introduce the MTreeMix kernel, which is based on a generative model tailored to the underlying biological mechanism. Specifically, the kernel quantifies the similarity of evolutionary escape from antiviral drug pressure between two viral sequence samples. We compare this novel kernel to a standard, evolution-agnostic amino acid encoding in the prediction of HIV drug resistance from genotype, using support vector regression. The results show significant improvements in predictive performance across 17 anti-HIV drugs. Thus, in our study, the generative-discriminative paradigm is key to bridging the gap between population genetic modeling and clinical decision making.
Unlike wired networks, wireless networks have very dynamic channel properties and the data communication suffers from interference, multi-path fading and noise. Since wireless devices are mobile, factors such as energ...
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Unlike wired networks, wireless networks have very dynamic channel properties and the data communication suffers from interference, multi-path fading and noise. Since wireless devices are mobile, factors such as energy consumption, effective coverage area and most of all reliability and quality of service are of key importance. The 802.11a/b/g wireless protocols employ static link layer control and transmit packets/frames with pre-determined sizes. This paper focuses on benefits derived from combining adaptive packet/frame sizing with forward error correcting (FEC) turbo codes. Protecting the data frames on the channel, using FEC enhances efficiency of dynamic packet sizing and is shown to increase energy efficiency and communication range. Adaptive packet sizing software from SmartPackets Inc. and turbo code simulations are used to discover parameters that are common to both and affect communication efficiency. A multi-fold improvement in throughput is found when these technologies are used simultaneously
This article presents the application of meta-learning evolutionary artificial neural network (MLEANN) for a pharmaceutical research problem. Designing drugs is a current problem in the pharmaceutical research domain....
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This article presents the application of meta-learning evolutionary artificial neural network (MLEANN) for a pharmaceutical research problem. Designing drugs is a current problem in the pharmaceutical research domain. By designing a drug we mean to choose some variables of drug formulation (inputs), for obtaining optimal characteristics of drug (outputs). To solve such a problem we propose an evolutionary artificial neural network and the performance is compared with a neuro-fuzzy system and an artificial neural network trained using scaled conjugate gradient algorithm. This research used the experimental data obtained from the Laboratory of Pharmaceutical Techniques of the Faculty of Pharmacy in Cluj-Napoca, Romania. Bootstrap techniques were used to generate more samples of data and the number of experimental data is reduced due to the costs and time durations of experimentations. We obtain in this way a better estimation of some drug parameters. Experiment results indicate that the proposed method is efficient
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