28 research outputs found

    Residual effects of esmirtazapine on actual driving performance: overall findings and an exploratory analysis into the role of CYP2D6 phenotype

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    INTRODUCTION: Esmirtazapine is evaluated as a novel drug for treatment of insomnia. PURPOSE: The present study was designed to assess residual effects of single and repeated doses of esmirtazapine 1.5 and 4.5 mg on actual driving in 32 healthy volunteers in a double-blind, placebo-controlled study. Treatment with single doses of zopiclone 7.5 mg was included as active control. METHODS: Treatments were administered in the evening. Driving performance was assessed in the morning, 11 h after drug intake, in a standardized on-the-road highway driving test. The primary study parameter was standard deviation of lateral position (SDLP), a measure of "weaving". All subjects were subjected to CYP2D6 phenotyping in order to distinguish poor metabolizers from extensive metabolizers of esmirtazapine. RESULTS: Overall, esmirtazapine 1.5 mg did not produce any clinically relevant change in SDLP after single and repeated dosing. Driving impairment, i.e., a rise in SDLP, did occur after a single-dose administration of esmirtazapine 4.5 mg but was resolved after repeated doses. Acute driving impairment was more pronounced after both doses of esmirtazapine in a select group of poor metabolizers (N = 7). A single-dose zopiclone 7.5 mg also increased SDLP as expected. CONCLUSION: It is concluded that single and repeated doses of 1.5 mg esmirtazapine are generally not associated with residual impairment. Single-dose administration of 4.5 mg esmirtazapine was associated with residual impairment that generally resolved after repeated administration. Exploratory analysis in a small group of poor CYP 2D6 metabolizers suggested that these subjects are more sensitive to the impairing effects of esmirtazapine on car driving

    Autologous Hematopoietic Stem Cell Transplantation vs Intravenous Pulse Cyclophosphamide in Diffuse Cutaneous Systemic Sclerosis: A Randomized Clinical Trial

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    Importance: High-dose immunosuppressive therapy and autologous hematopoietic stem cell transplantation (HSCT) have shown efficacy in systemic sclerosis in phase 1 and small phase 2 trials. Objective: To compare efficacy and safety of HSCT vs 12 successive monthly intravenous pulses of cyclophosphamide. Design, Setting, and Participants: The Autologous Stem Cell Transplantation International Scleroderma (ASTIS) trial, a phase 3, multicenter, randomized (1:1), open-label, parallel-group, clinical trial conducted in 10 countries at 29 centers with access to a European Group for Blood and Marrow Transplantation–registered transplant facility. From March 2001 to October 2009, 156 patients with early diffuse cutaneous systemic sclerosis were recruited and followed up until October 31, 2013. Interventions: HSCT vs intravenous pulse cyclophosphamide. Main Outcomes and Measures: The primary end point was event-free survival, defined as time from randomization until the occurrence of death or persistent major organ failure. Results: A total of 156 patients were randomly assigned to receive HSCT (n = 79) or cyclophosphamide (n = 77). During a median follow-up of 5.8 years, 53 events occurred: 22 in the HSCT group (19 deaths and 3 irreversible organ failures) and 31 in the control group (23 deaths and 8 irreversible organ failures). During the first year, there were more events in the HSCT group (13 events [16.5%], including 8 treatment-related deaths) than in the control group (8 events [10.4%], with no treatment-related deaths). At 2 years, 14 events (17.7%) had occurred cumulatively in the HSCT group vs 14 events (18.2%) in the control group; at 4 years, 15 events (19%) had occurred cumulatively in the HSCT group vs 20 events (26%) in the control group. Time-varying hazard ratios (modeled with treatment × time interaction) for event-free survival were 0.35 (95% CI, 0.16-0.74) at 2 years and 0.34 (95% CI, 0.16-0.74) at 4 years. Conclusions and Relevance: Among patients with early diffuse cutaneous systemic sclerosis, HSCT was associated with increased treatment-related mortality in the first year after treatment. However, HCST conferred a significant long-term event-free survival benefit. Trial Registration: isrctn.org Identifier: ISRCTN5437125

    Variational Cumulant Expansions for Intractable Distributions

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    Intractable distributions present a common difficulty in inference within the probabilistic knowledge representation framework and variational methods have recently been popular in providing an approximate solution. In this article, we describe a perturbational approach in the form of a cumulant expansion which, to lowest order, recovers the standard Kullback-Leibler variational bound. Higher-order terms describe corrections on the variational approach without incurring much further computational cost. The relationship to other perturbational approaches such as TAP is also elucidated. We demonstrate the method on a particular class of undirected graphical models, Boltzmann machines, for which our simulation results confirm improved accuracy and enhanced stability during learning. 1. Introduction In recent years, interest has steadily grown over many associated fields in representing and processing information in a probabilistic framework. Arguably, the reason for this is tha..

    Boltzmann Machines and the EM algorithm

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    In this paper we formulate the Expectation Maximization (EM) algorithm for Boltzmann Machines and we prove that the Kullback distance is a Lyaponov function for the EM algorithm. As a result the EM algorithm yields the same solutions as the original learning rule of Ackley, Hinton and Sejnowski. We give an example of the EM algorithm applied to a special class of Boltzmann Machines (BM). This class of BM's includes feedforward networks, radial basis networks and unsupervised clustering and probability density estimation networks. For this Boltzmann Machine the EM algorithm gives a significant speed up compared to standard methods such as (conjugate) gradient descent. 1 email: [email protected] 1 Introduction Boltzmann Machines are an interesting class of Neural Networks, because they have explicit parallelism of neuron and weight dynamics. They describe a general class of networks of which feedforward networks and clustering networks are special cases. However, their practical us..

    Partial Retraining: A New Approach to Input Relevance Determination

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    In this article we introduce partial retraining, an algorithm to determine the relevance of the input variables of a trained neural network. We place this algorithm in the context of other approaches to relevance determination. Numerical experiments on both artificial and real-world problems show that partial retraining outperforms its competitors, which include methods based on constant substitution, analysis of weight magnitudes, and "optimal brain surgeon". 1 Introduction Feedforward neural networks are able to learn the relationship between input and output variables. Even when knowledge about the problem is limited, as for example in cases where no explicit physical or economical model can be built, neural networks may still capture some of the underlying principles. Especially with a lack of domain knowledge, the usual approach in neural network modeling is to include all input variables that may have an effect on the output. This approach is suboptimal in several aspects. First..
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