Adverse drug events in an intensive care unit of a university hospital

Purpose Adverse drug events (ADEs) are harmful and occur with alarming frequency in critically ill patients. Complex pharmacotherapy with multiple medications increases the probability of a drug interaction (DI) and ADEs in patients in intensive care units (ICUs). The objective of the study is to determine the frequency of ADEs among patients in the ICU of a university hospital and the drugs implicated. Also, factors associated with ADEs are investigated. Methods This cross-sectional study investigated 299 medical records of patients hospitalized for 5 or more days in an ICU. ADEs were identified through intensive monitoring adopted in hospital pharmacovigilance and also ADE triggers. Adverse drug reactions (ADR) causality was classified using the Naranjo algorithm. Data were analyzed through descriptive analysis, and through univariate and multiple logistic regression. Results The most frequent ADEs were ADRs type A, of possible causality and moderate severity. The most frequent ADR was drug-induced acute kidney injury. Patients with ADEs related to DIs corresponded to 7% of the sample. The multiple logistic regression showed that length of hospitalization (OR = 1.06) and administration of cardiovascular drugs (OR = 2.2) were associated with the occurrence of ADEs. Conclusion Adverse drug reactions of clinical significance were the most frequent ADEs in the ICU studied, which reduces patient safety. The number of ADEs related to drug interactions was small, suggesting that clinical manifestations of drug interactions that harm patients are not frequent in ICUs.

H(infinity) filtering for rectangular discrete-time descriptor systems

This paper deals with the H(infinity) recursive estimation problem for general rectangular time-variant descriptor systems in discrete time. Riccati-equation based recursions for filtered and predicted estimates are developed based on a data fitting approach and game theory. In this approach, the nature determines a state sequence seeking to maximize the estimation cost, whereas the estimator tries to find an estimate that brings the estimation cost to a minimum. A solution exists for a specified gamma-level if the resulting cost is positive. In order to present some computational alternatives to the H(infinity) filters developed, they are rewritten in information form along with the respective array algorithms. (C) 2009 Elsevier Ltd. All rights reserved.

Recursive linear estimation for general discrete-time descriptor systems

This paper considers the optimal linear estimates recursion problem for discrete-time linear systems in its more general formulation. The system is allowed to be in descriptor form, rectangular, time-variant, and with the dynamical and measurement noises correlated. We propose a new expression for the filter recursive equations which presents an interesting simple and symmetric structure. Convergence of the associated Riccati recursion and stability properties of the steady-state filter are provided. (C) 2010 Elsevier Ltd. All rights reserved.

Information Filtering and Array Algorithms for Discrete-Time Markovian Jump Linear Systems

This technical note develops information filter and array algorithms for a linear minimum mean square error estimator of discrete-time Markovian jump linear systems. A numerical example for a two-mode Markovian jump linear system, to show the advantage of using array algorithms to filter this class of systems, is provided.

Discrete approximation to the global spectrum of the tangent operator for flow past a circular cylinder

This paper deals with the calculation of the discrete approximation to the full spectrum for the tangent operator for the stability problem of the symmetric flow past a circular cylinder. It is also concerned with the localization of the Hopf bifurcation in laminar flow past a cylinder, when the stationary solution loses stability and often becomes periodic in time. The main problem is to determine the critical Reynolds number for which a pair of eigenvalues crosses the imaginary axis. We thus present a divergence-free method, based on a decoupling of the vector of velocities in the saddle-point system from the vector of pressures, allowing the computation of eigenvalues, from which we can deduce the fundamental frequency of the time-periodic solution. The calculation showed that stability is lost through a symmetry-breaking Hopf bifurcation and that the critical Reynolds number is in agreement with the value presented in reported computations. (c) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Discrete-time mean variance optimal control of linear systems with Markovian jumps and multiplicative noise

In this article, we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the final value of the expectation and variance of the output. In the first problem it is desired to minimise the final variance of the output subject to a restriction on its final expectation, in the second one it is desired to maximise the final expectation of the output subject to a restriction on its final variance, and in the third one it is considered a performance criterion composed by a linear combination of the final variance and expectation of the output of the system. We present explicit sufficient conditions for the existence of an optimal control strategy for these problems, generalising previous results in the literature. We conclude this article presenting a numerical example of an asset liabilities management model for pension funds with regime switching.

Chaotic Synchronization in Discrete-Time Systems Connected by Bandlimited Channels

Due to the broadband characteristic of chaotic signals, many of the methods that have been proposed for synchronizing chaotic systems do not usually present a satisfactory performance when applied to bandlimited communication channels. Here, the effects of bandwidth limitations imposed by the channel on the synchronous solution of a discrete-time chaotic master-slave network are investigated. The discrete-time system considered in this study is the Henon map. It is analytically shown that synchronism can be achieved in such a network by introducing a digital filter in the feedback loop responsible for generating the chaotic signal that will be sent to the slave node. Numerical simulations relating the filter parameters, such as its order and cut-off frequency, to the maximum Lyapunov exponent of the master node, which determines if the transmitted signal is chaotic or not, are also presented. These results can be useful for practical communication schemes based on chaos.

Generalized Coupled Algebraic Riccati Equations for Discrete-time Markov Jump with Multiplicative Noise Systems

In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

Microbial activity and community composition in saline and non-saline soils exposed to multiple drying and rewetting events

The effects of drying and rewetting (DRW) have been studied extensively in non-saline soils, but little is known about the impact of DRW in saline soils. An incubation experiment was conducted to determine the impact of 1-3 drying and re-wetting events on soil microbial activity and community composition at different levels of electrical conductivity in the saturated soil extract (ECe) (ECe 0.7, 9.3, 17.6 dS m(-1)). A non-saline sandy loam was amended with NaCl to achieve the three EC levels 21 days prior to the first DRW; wheat straw was added 7 days prior to the first DRW. Each DRW event consisted of 1 week drying and 1 week moist (50% of water holding capacity, WHC). After the last DRW, the soils were maintained moist until the end of the incubation period (63 days after addition of the wheat straw). A control was kept moist (50% of WHC) throughout the incubation period. Respiration rates on the day after rewetting were similar after the first and the second DRW, but significantly lower after the third DRW. After the first and second DRW, respiration rates were lower at EC17.6 compared to the lower EC levels, whereas salinity had little effect on respiration rates after the third DRW or at the end of the experiment when respiration rates were low. Compared to the continuously moist treatment, respiration rates were about 50% higher on day 15 (d15) and d29. On d44, respiration rates were about 50% higher at EC9.7 than at the other two EC levels. Cumulative respiration was increased by DRW only in the treatment with one DRW and only at the two lower EC levels. Salinity affected microbial biomass and community composition in the moist soils but not in the DRW treatments. At all EC levels and all sampling dates, the community composition in the continuously moist treatment differed from that in the DRW treatments, but there were no differences among the DRW treatments. Microbes in moderately saline soils may be able to utilise substrates released after multiple DRW events better than microbes in non-saline soil. However, at high EC (EC17.6), the low osmotic potential reduced microbial activity to such an extent that the microbes were not able to utilise substrate released after rewetting of dry soil.

A modified discrete random pore model allowing for different initial surface reactivity

We investigate here a modification of the discrete random pore model [Bhatia SK, Vartak BJ, Carbon 1996;34:1383], by including an additional rate constant which takes into account the different reactivity of the initial pore surface having attached functional groups and hydrogens, relative to the subsequently exposed surface. It is observed that the relative initial reactivity has a significant effect on the conversion and structural evolution, underscoring the importance of initial surface chemistry. The model is tested against experimental data on chemically controlled char oxidation and steam gasification at various temperatures. It is seen that the variations of the reaction rate and surface area with conversion are better represented by the present approach than earlier random pore models. The results clearly indicate the improvement of model predictions in the low conversion region, where the effect of the initially attached functional groups and hydrogens is more significant, particularly for char oxidation. It is also seen that, for the data examined, the initial surface chemistry is less important for steam gasification as compared to the oxidation reaction. Further development of the approach must also incorporate the dynamics of surface complexation, which is not considered here.

Studies of Cognition and Emotion in Organisations: Attribution, Affective Events, Emotional Intelligence and Perception of Emotion

This article details the author’s attempts to improve understanding of organisational behaviour through investigation of the cognitive and affective processes that underlie attitudes and behaviour. To this end, the paper describes the author’s earlier work on the attribution theory of leadership and, more recently, in three areas of emotion research: affective events theory, emotional intelligence, and the effect of supervisors’ facial expression on employees’ perceptions of leader-member exchange quality. The paper summarises the author’s research on these topics, shows how they have contributed to furthering our understanding of organisational behaviour, suggests where research in these areas are going, and draws some conclusions for management practice.

Biomolecular interaction analysis of IFN gamma-induced signaling events in whole-cell lysates: Prevalence of latent STAT1 in high-molecular weight complexes

The basic framework for the JAK/STAT pathway is well documented. Recruitment of latent cytoplasmic STAT transcription factors to tyrosine phosphorylated docking sites on cytokine receptors and their JAK-mediated phosphorylation instigates their translocation to the nucleus and their ability to bind DNA, The biochemical processes underlying recruitment and activation of this pathway have commonly been studied in reconstituted in vitro systems using previously defined recombinant signaling components. We have dissected the Interferon gamma (IFN gamma) signal transduction pathway in crude extracts from wild-type and STAT1-negative mutant cell Lines by real-time BIAcore analysis, size-exclusion (SE) chromatography and immune-detection. The data indicate that in detergent-free cell extracts: (1) the phospho-tyrosine (Y440P)-containing peptide motif of the IFN gamma-receptor ct-chain interacts directly with STAT1, or STAT1 complexes, and no other protein; (2) nonactivated STAT 1 is present in a higher molecular weight complex(es) and, at least for IFN gamma-primed cells, is available for recruitment to the activated IFN gamma-receptor from only a subset of such complexes; (3) activated STAT1 is released from the receptor as a monomer.