8 research outputs found

    Randomized controlled trial of artesunate or artemether in Vietnamese adults with severe falciparum malaria

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    <p>Abstract</p> <p>Background</p> <p>Both artemether and artesunate have been shown to be superior to quinine for the treatment of severe falciparum malaria in Southeast Asian adults, although the magnitude of the superiority has been greater for artesunate than artemether. These two artemisinin derivatives had not been compared in a randomized trial.</p> <p>Methods</p> <p>A randomized double blind trial in 370 adults with severe falciparum malaria; 186 received intramuscular artesunate (2.4 mg/kg immediately followed by 1.2 mg/kg at 12 hours then 24 hours then daily) and 184 received intramuscular artemether (3.6 mg per kilogram immediately followed by 1.8 mg per kilogram daily) was conducted in Viet Nam. Both drugs were given for a minimum of 72 hours.</p> <p>Results</p> <p>There were 13 deaths in the artesunate group (7 percent) and 24 in the artemether group (13 percent); P = 0.052; relative risk of death in the patients given artesunate, 0.54; (95 percent confidence interval 0.28-1.02). Parasitaemia declined more rapidly in the artesunate group. Both drugs were very well tolerated.</p> <p>Conclusions</p> <p>Intramuscular artesunate may be superior to intramuscular artemether for the treatment of severe malaria in adults.</p

    Modified Erlang Loss System for Cognitive Wireless Networks

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    This paper considers a modified Erlang loss system for cognitive wireless networks and related applications. A primary user has pre-emptive priority over secondary users, and the primary customer is lost if upon arrival all the channels are used by other primary users. Secondary users cognitively use idle channels, and they can stay (either in an infinite buffer or in an orbit) in cases where idle channels are not available upon arrival or they are interrupted by primary users. While the infinite buffer model represents the case with zero sensing time, the infinite orbit model represents the case with positive sensing time. We obtain an explicit stability condition for the cases where arrival processes of primary users and secondary users follow Poisson processes, and their service times follow two distinct arbitrary distributions. The stability condition is insensitive to the service time distributions and implies the maximal throughout of secondary users. Moreover, we extend the stability analysis to the system with outgoing calls. For a special case of exponential service time distributions, we analyze the buffered system in depth to show the effect of parameters on the delay performance and the mean number of interruptions of secondary users. Our simulations for distributions rather than exponential reveal that the mean number of terminations for secondary users is less sensitive to the service time distribution of primary users

    Learning meaningful latent space representations for patient risk stratification: model development and validation for dengue and other acute febrile illness

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    Background: Increased data availability has prompted the creation of clinical decision support systems. These systems utilise clinical information to enhance health care provision, both to predict the likelihood of specific clinical outcomes or evaluate the risk of further complications. However, their adoption remains low due to concerns regarding the quality of recommendations, and a lack of clarity on how results are best obtained and presented. Methods: We used autoencoders capable of reducing the dimensionality of complex datasets in order to produce a 2D representation denoted as latent space to support understanding of complex clinical data. In this output, meaningful representations of individual patient profiles are spatially mapped in an unsupervised manner according to their input clinical parameters. This technique was then applied to a large real-world clinical dataset of over 12,000 patients with an illness compatible with dengue infection in Ho Chi Minh City, Vietnam between 1999 and 2021. Dengue is a systemic viral disease which exerts significant health and economic burden worldwide, and up to 5% of hospitalised patients develop life-threatening complications. Results: The latent space produced by the selected autoencoder aligns with established clinical characteristics exhibited by patients with dengue infection, as well as features of disease progression. Similar clinical phenotypes are represented close to each other in the latent space and clustered according to outcomes broadly described by the World Health Organisation dengue guidelines. Balancing distance metrics and density metrics produced results covering most of the latent space, and improved visualisation whilst preserving utility, with similar patients grouped closer together. In this case, this balance is achieved by using the sigmoid activation function and one hidden layer with three neurons, in addition to the latent dimension layer, which produces the output (Pearson, 0.840; Spearman, 0.830; Procrustes, 0.301; GMM 0.321). Conclusion: This study demonstrates that when adequately configured, autoencoders can produce two-dimensional representations of a complex dataset that conserve the distance relationship between points. The output visualisation groups patients with clinically relevant features closely together and inherently supports user interpretability. Work is underway to incorporate these findings into an electronic clinical decision support system to guide individual patient management
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