Evaluation of the effect of appropriate antimicrobial therapy on mortality associated with Acinetobacter nosocomialis bacteraemia

AbstractAppropriate antimicrobial therapy is effective for severe infections caused by Acinetobacter baumannii, but efficacy for other Acinetobacter species remains to be established. The current study was designed to determine whether appropriate antimicrobial therapy reduces the mortality of patients with Acinetobacter nosocomialis bacteraemia. A 9-year retrospective study of 266 patients with monomicrobial A. nosocomialis bacteraemia was conducted at a large teaching hospital in Taiwan. Multivariable analysis was performed to evaluate the impact on 14-day mortality according to clinical characteristics, severity of disease and use of appropriate antimicrobial therapy. The influence of APACHE II score on the impact of appropriate antimicrobial therapy was analysed by including an interaction term. The overall 14-day mortality was 9.4%. Multivariable analysis revealed that APACHE II score was the only factor significantly associated with mortality (odds ratio, 1.18; 95% confidence interval, 1.11–1.25; p <0.001). Appropriate antimicrobial therapy was not associated with reduced mortality regardless of disease severity. In the subgroup analyses in patients with different clinical conditions, APACHE II score was consistently an independent factor for 14-day mortality, and appropriate antimicrobial therapy did not affect the mortality in any group. In conclusion, severity of disease, based on the APACHE II score, was the independent risk factor for 14-day mortality for patients with monomicrobial A. nosocomialis bacteraemia, even in different clinical conditions. In contrast, appropriate antimicrobial therapy did not reduce the 14-day mortality. The result highlighted a different effect of appropriate antimicrobial therapy on infections caused by two phenotypically undifferentiated Acinetobacter

Betel nut chewing and incidence of newly diagnosed type 2 diabetes mellitus in Taiwan.

<p>Abstract</p> <p>Background</p> <p>Betel nut chewing is associated with type 2 diabetes mellitus (T2DM) in a recent prevalence study in Taiwan. The present study further investigated its link with the incidence of newly diagnosed T2DM during the years 1992-1996.</p> <p>Methods</p> <p>Population-based datasets of a sample of 93,484 out of 256,036 diabetic patients from 66 medical settings using the National Health Insurance scheme covering > 96% of the population, published population prevalence of betel nut chewing and the governmental census of national population were used for calculation of odds ratios, incidence rates and incidence rate ratios between chewers and never-chewers in the male population for the year 1992 to 1996.</p> <p>Results</p> <p>Ever chewers among the diabetic patients were younger, more obese and had higher prevalence of parental diabetes than never-chewers (all <it>p </it>values < 0.001). Odds ratios for T2DM for ever chewers vs. never-chewers in the age of < 40, 40-49, 50-59, 60-69 and ≥70 years were 1.06 (0.92-1.23), 1.60 (1.45-1.76), 2.12 (1.88-2.39), 3.58 (3.10-4.13) and 7.14 (5.47-9.31), respectively. In 1996, incidence rates (per 100,000 population) in the respective age groups were 19.1, 251.5, 567.3, 721.7 and 971.4 for never-chewers; and were 30.2, 520.9, 2566.9, 11672.8 and 630.3 for ever chewers. The respective incidence rate ratios were 1.58, 2.07, 4.52, 16.17 and 0.65. The age-specific incidence rates and rate ratios were relatively consistent from 1992 to 1996. The differences in obesity and parental diabetes between ever chewers and never-chewers were mostly not statistically significant after age stratification, suggesting the link could not be attributed to these two factors.</p> <p>Conclusions</p> <p>Chewing betel nut is associated with newly diagnosed T2DM, supporting the suggestion that the habit is diabetogenic.</p

Engineered swift equilibration of a Brownian particle

A fundamental and intrinsic property of any device or natural system is its relaxation time relax, which is the time it takes to return to equilibrium after the sudden change of a control parameter [1]. Reducing $tau$ relax , is frequently necessary, and is often obtained by a complex feedback process. To overcome the limitations of such an approach, alternative methods based on driving have been recently demonstrated [2, 3], for isolated quantum and classical systems [4--9]. Their extension to open systems in contact with a thermostat is a stumbling block for applications. Here, we design a protocol,named Engineered Swift Equilibration (ESE), that shortcuts time-consuming relaxations, and we apply it to a Brownian particle trapped in an optical potential whose properties can be controlled in time. We implement the process experimentally, showing that it allows the system to reach equilibrium times faster than the natural equilibration rate. We also estimate the increase of the dissipated energy needed to get such a time reduction. The method paves the way for applications in micro and nano devices, where the reduction of operation time represents as substantial a challenge as miniaturization [10]. The concepts of equilibrium and of transformations from an equilibrium state to another, are cornerstones of thermodynamics. A textbook illustration is provided by the expansion of a gas, starting at equilibrium and expanding to reach a new equilibrium in a larger vessel. This operation can be performed either very slowly by a piston, without dissipating energy into the environment, or alternatively quickly, letting the piston freely move to reach the new volume

Simple deterministic dynamical systems with fractal diffusion coefficients

We analyze a simple model of deterministic diffusion. The model consists of a one-dimensional periodic array of scatterers in which point particles move from cell to cell as defined by a piecewise linear map. The microscopic chaotic scattering process of the map can be changed by a control parameter. This induces a parameter dependence for the macroscopic diffusion coefficient. We calculate the diffusion coefficent and the largest eigenmodes of the system by using Markov partitions and by solving the eigenvalue problems of respective topological transition matrices. For different boundary conditions we find that the largest eigenmodes of the map match to the ones of the simple phenomenological diffusion equation. Our main result is that the difffusion coefficient exhibits a fractal structure by varying the system parameter. To understand the origin of this fractal structure, we give qualitative and quantitative arguments. These arguments relate the sequence of oscillations in the strength of the parameter-dependent diffusion coefficient to the microscopic coupling of the single scatterers which changes by varying the control parameter.Comment: 28 pages (revtex), 12 figures (postscript), submitted to Phys. Rev.

Associations of the distance-saturation product and low-attenuation area percentage in pulmonary computed tomography with acute exacerbation in patients with chronic obstructive pulmonary disease

Background: Chronic obstructive pulmonary disease (COPD) has high global health concerns, and previous research proposed various indicators to predict mortality, such as the distance-saturation product (DSP), derived from the 6-min walk test (6MWT), and the low-attenuation area percentage (LAA%) in pulmonary computed tomographic images. However, the feasibility of using these indicators to evaluate the stability of COPD still remains to be investigated. Associations of the DSP and LAA% with other COPD-related clinical parameters are also unknown. This study, thus, aimed to explore these associations. Methods: This retrospective study enrolled 111 patients with COPD from northern Taiwan. Individuals’ data we collected included results of a pulmonary function test (PFT), 6MWT, life quality survey [i.e., the modified Medical Research Council (mMRC) scale and COPD assessment test (CAT)], history of acute exacerbation of COPD (AECOPD), and LAA%. Next, the DSP was derived by the distance walked and the lowest oxygen saturation recorded during the 6MWT. In addition, the DSP and clinical phenotype grouping based on clinically significant outcomes by previous study approaches were employed for further investigation (i.e., DSP of 290 m%, LAA% of 20%, and AECOPD frequency of ≥1). Mean comparisons and linear and logistic regression models were utilized to explore associations among the assessed variables. Results: The low-DSP group (<290 m%) had significantly higher values for the mMRC, CAT, AECOPD frequency, and LAA% at different lung volume scales (total, right, and left), whereas it had lower values of the PFT and 6MWT parameters compared to the high-DSP group. Significant associations (with high odds ratios) were observed of the mMRC, CAT, AECOPD frequency, and PFT with low- and high-DSP groupings. Next, the risk of having AECOPD was associated with the mMRC, CAT, DSP, and LAA% (for the total, right, and left lungs). Conclusion: A lower value of the DSP was related to a greater worsening of symptoms, more-frequent exacerbations, poorer pulmonary function, and more-severe emphysema (higher LAA%). These readily determined parameters, including the DSP and LAA%, can serve as indicators for assessing the COPD clinical course and may can serve as a guide to corresponding treatments

A clinically interpretable convolutional neural network for the real time prediction of early squamous cell cancer of the esophagus; comparing diagnostic performance with a panel of expert European and Asian endoscopists

BACKGROUND AND AIMS: Intrapapillary capillary loops (IPCLs) are microvascular structures that correlate with invasion depth of early squamous cell neoplasia (ESCN) and allow accurate prediction of histology. Artificial intelligence may improve human recognition of IPCL patterns and prediction of histology to allow prompt access to endoscopic therapy of ESCN where appropriate METHODS: One hundred fifteen patients were recruited at 2 academic Taiwanese hospitals. ME-NBI videos of squamous mucosa were labeled as dysplastic or normal according to their histology and IPCL patterns classified by consensus of 3 experienced clinicians. A convolutional neural network (CNN) was trained to classify IPCLs, using 67742 high quality ME-NBI by 5-fold cross validation. Performance measures were calculated to give an average F1 score, accuracy, sensitivity, and specificity. A panel of 5 Asian and 4 European experts predicted the histology of a random selection of 158 images using the JES IPCL classification; accuracy, sensitivity, specificity, positive and negative predictive values were calculated. RESULTS: Expert European Union (EU) and Asian endoscopists attained F1 scores (a measure of binary classification accuracy) of 97.0% and 98%, respectively. Sensitivity and accuracy of the EU and Asian clinicians were 97%, 98% and 96.9%, 97.1% respectively. The CNN average F1 score was 94%, sensitivity 93.7% and accuracy 91.7%. Our CNN operates at video rate and generates class activation maps that can be used to visually validate CNN predictions. CONCLUSIONS: We report a clinically interpretable CNN developed to predict histology based on IPCL patterns, in real-time, using the largest reported dataset of images for this purpose. Our CNN achieved diagnostic performance comparable to an expert panel of endoscopists

Nanofabrication by magnetic focusing of supersonic beams

We present a new method for nanoscale atom lithography. We propose the use of a supersonic atomic beam, which provides an extremely high-brightness and cold source of fast atoms. The atoms are to be focused onto a substrate using a thin magnetic film, into which apertures with widths on the order of 100 nm have been etched. Focused spot sizes near or below 10 nm, with focal lengths on the order of 10 microns, are predicted. This scheme is applicable both to precision patterning of surfaces with metastable atomic beams and to direct deposition of material.Comment: 4 pages, 3 figure