Clinical predictors for Legionella in patients presenting with community-acquired pneumonia to the emergency department.

BACKGROUND: Legionella species cause severe forms of pneumonia with high mortality and complication rates. Accurate clinical predictors to assess the likelihood of Legionella community-acquired pneumonia (CAP) in patients presenting to the emergency department are lacking. METHODS: We retrospectively compared clinical and laboratory data of 82 consecutive patients with Legionella CAP with 368 consecutive patients with non-Legionella CAP included in two studies at the same institution. RESULTS: In multivariate logistic regression analysis we identified six parameters, namely high body temperature (OR 1.67, p < 0.0001), absence of sputum production (OR 3.67, p < 0.0001), low serum sodium concentrations (OR 0.89, p = 0.011), high levels of lactate dehydrogenase (OR 1.003, p = 0.007) and C-reactive protein (OR 1.006, p < 0.0001) and low platelet counts (OR 0.991, p < 0.0001), as independent predictors of Legionella CAP. Using optimal cut off values of these six parameters, we calculated a diagnostic score for Legionella CAP. The median score was significantly higher in Legionella CAP as compared to patients without Legionella (4 (IQR 3-4) vs 2 (IQR 1-2), p < 0.0001) with a respective odds ratio of 3.34 (95%CI 2.57-4.33, p < 0.0001). Receiver operating characteristics showed a high diagnostic accuracy of this diagnostic score (AUC 0.86 (95%CI 0.81-0.90), which was better as compared to each parameter alone. Of the 191 patients (42%) with a score of 0 or 1 point, only 3% had Legionella pneumonia. Conversely, of the 73 patients (16%) with > or =4 points, 66% of patients had Legionella CAP. CONCLUSION: Six clinical and laboratory parameters embedded in a simple diagnostic score accurately identified patients with Legionella CAP. If validated in future studies, this score might aid in the management of suspected Legionella CAP.

Adoption of the Healthy Heart Kit by Alberta family physicians

OBJECTIVE: The Healthy Heart Kit (HHK) is a risk management and patient education kit for the prevention of cardiovascular disease (CVD) and the promotion of CV health. There are currently no published data examining predictors of HHK use by physicians. The main objective of this study was to examine the association between physicians' characteristics (socio-demographic, cognitive, and behavioural) and the use of the HHK. METHODS: All registered family physicians in Alberta (n=3068) were invited to participate in the "Healthy Heart Kit" Study. Consenting physicians (n=153) received the Kit and were requested to use it for two months. At the end of this period, a questionnaire collected data on the frequency of Kit use by physicians, as well as socio-demographic, cognitive, and behavioural variables pertaining to the physicians. RESULTS: The questionnaire was returned by 115 physicians (follow-up rate = 75%). On a scale ranging from 0 to 100, the mean score of Kit use was 61 [SD=26]. A multiple linear regression showed that "agreement with the Kit" and the degree of "confidence in using the Kit" was strongly associated with Kit use, explaining 46% of the variability for Kit use. Time since graduation was inversely associated with Kit use, and a trend was observed for smaller practices to be associated with lower use. CONCLUSION: Given these findings, future research and practice should explore innovative strategies to gain initial agreement among physicians to employ such clinical tools. Participation of older physicians and solo-practitioners in this process should be emphasized.

Beliefs and practices in the assessment of workplace pollutants

OBJECTIVES: A survey was undertaken among Swiss occupational hygienists and other professionals to identify the different exposure assessment methods used, the contextual parameters observed and the uses, difficulties and possible developments of exposure models for field application. METHODS: A questionnaire was mailed to 121 occupational hygienists, all members of the Swiss Occupational Hygiene Society. A shorter questionnaire was also sent to registered occupational physicians and selected safety specialists. Descriptive statistics and multivariate analyses were performed. RESULTS: The response rate for occupational hygienists was 60%. The so-called expert judgement appeared to be the most widely used method, but its efficiency and reliability were both judged with very low scores. Long-term sampling was perceived as the most efficient and reliable method. Various determinants of exposure, such as emission rate and work activity, were often considered important, even though they were not included in the exposure assessment processes. Near field local phenomena determinants were also judged important for operator exposure estimation. CONCLUSION: Exposure models should be improved to integrate factors which are more easily accessible to practitioners. Descriptors of emission and local phenomena should also be included.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Self-reported smoking cessation activities among Swiss primary care physicians.

ABSTRACT: BACKGROUND: Individual counselling, pharmacotherapy, and group therapy are evidence-based interventions that help patients stop smoking. Acupuncture, hypnosis, and relaxation have no demonstrated efficacy on smoking cessation, whereas self-help material may only have a small benefit. The purpose of this study is to assess physicians' current clinical practice regarding smokers motivated to stop smoking. METHODS: The survey included 3385 Swiss primary care physicians. Self-reported use of nine smoking cessation interventions was scored. One point was given for each positive answer about practicing interventions with demonstrated efficacy, i.e. nicotine replacement therapy, bupropion, counselling, group therapy, and smoking cessation specialist. No points were given for the recommendation of acupuncture, hypnosis, relaxation, and self-help material. Multivariable logistic analysis was performed to identify factors associated with a good practice score, defined as >1. RESULTS: The response rate was 55%. Respondents were predominately over the age of 40 years (88%), male (79%), and resided in urban areas (74%). Seventeen percent reported being smokers. Most of the physicians prescribed nicotine replacement therapy (84%), bupropion (65%), or provided counselling (70%). A minority of physicians recommended acupuncture (26%), hypnosis (8%), relaxation (7%), or self-help material (24%). A good practice score was obtained by 85% of respondents. Having attended a smoking cessation training program was the only significant predictor of a good practice score (odds ratio: 6.24 , 95% CI 1.95-20.04). CONCLUSION: The majority of respondents practice recommended smoking cessation interventions. However, there is room for improvement and implementing an evidence-based smoking cessation-training program could provide additional benefit.

Segmentation of Head and Neck Lymph Node Regions for Radiotherapy Planning Using Active Contour-Based Atlas Registration

In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.

Ecology and life history affect different aspects of the population structure of 27 high-alpine plants.

A plant species' genetic population structure is the result of a complex combination of its life history, ecological preferences, position in the ecosystem and historical factors. As a result, many different statistical methods exist that measure different aspects of species' genetic structure. However, little is known about how these methods are interrelated and how they are related to a species' ecology and life history. In this study, we used the IntraBioDiv amplified fragment length polymorphisms data set from 27 high-alpine species to calculate eight genetic summary statistics that we jointly correlate to a set of six ecological and life-history traits. We found that there is a large amount of redundancy among the calculated summary statistics and that there is a significant association with the matrix of species traits. In a multivariate analysis, two main aspects of population structure were visible among the 27 species. The first aspect is related to the species' dispersal capacities and the second is most likely related to the species' postglacial recolonization of the Alps. Furthermore, we found that some summary statistics, most importantly Mantel's r and Jost's D, show different behaviour than expected based on theory. We therefore advise caution in drawing too strong conclusions from these statistics.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Active deformation fields: dense deformation field estimation for atlas-based segmentation using the active contour framework.

This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and encompasses many of the state-of-the-art atlas-based segmentation methods. It also allows to perform the registration of atlas and target images based on only selected structures of interest. The versatility and potentiality of the proposed framework are demonstrated by presenting three diverse applications: In the first application, we show how the proposed framework can be used to simulate the growth of inconsistent structures like a tumor in an atlas. In the second application, we estimate the position of nonvisible brain structures based on the surrounding structures and validate the results by comparing with other methods. In the final application, we present the segmentation of lymph nodes in the Head and Neck CT images, and demonstrate how multiple registration forces can be used in this framework in an hierarchical manner.

Multivariate analyses of genotype x environment interaction of popcorn

The objectives of this work were to evaluate the genotype x environment (GxE) interaction for popcorn and to compare two multivariate analyses methods. Nine popcorn cultivars were sown on four dates one month apart during each of the agricultural years 1998/1999 and 1999/2000. The experiments were carried out using randomized block designs, with four replicates. The cv. Zélia contributed the least to the GxE interaction. The cv. Viçosa performed similarly to cv. Rosa-claro. Optimization of GxE was obtained for cv. CMS 42 for a favorable mega-environment, and for cv. CMS 43 for an unfavorable environment. Multivariate analysis supported the results from the method of Eberhart & Russell. The graphic analysis of the Additive Main effects and Multiplicative Interaction (AMMI) model was simple, allowing conclusions to be made about stability, genotypic performance, genetic divergence between cultivars, and the environments that optimize cultivar performance. The graphic analysis of the Genotype main effects and Genotype x Environment interaction (GGE) method added to AMMI information on environmental stratification, defining mega-environments and the cultivars that optimized performance in those mega-environments. Both methods are adequate to explain the genotype x environment interactions.

Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

A first population-based cohort study of risk factors of stroke mortality in Africa

Background: We are not aware of any population-based cohort study of risk factors of stroke in the African region. We conducted a longitudinal study in the Seychelles (Indian Ocean, east of Kenya), a middle-income island state with majority of the population of African descent. Data in Africa are important for international comparison and for advocacy in the region. Methods: Three population-based examination surveys were performed in 1989, 1994 and 2004 (n_1081, 1067, and 1255, respectively). Baseline data were linked with cause-specific mortality from vital statistics up to May 2007. We considered stroke (any type) as a cause of death if the diagnosis was reported in any of the 4 fields for underlying and concomitant causes of death. Results. Among the 3317 different persons aged 25-64 at baseline, 291 died including 58 with stroke during follow up (mean: 10.2 years). The prevalence of high blood pressure (BP _140/90 mmHg) was 38%. In multivariate Cox regression, stroke mortality was increased by 18% and 35% for a 10-mmHg increase in systolic, respectively diastolic BP (p_0.001). The hazard ratios were 2.4 (95% CI: 1.7-3.3) for a 10-year age increase, 0.32 (0.15- 0.67) for a 1-mmol HDL-cholesterol increase, 2.2 (1.1- 4.2) for smoking _5 cigarettes vs. no smoking and 1.7 for diabetes (0.93-3.3; p_0.08). No significant association was found for sex, LDL-cholesterol, alcohol intake, and occupation. Conclusion. This first populationbased cohort study in the African region demonstrates high mortality rates from stroke in middle-aged adults and confirms the important role of high BP. This emphasizes the critical importance of reducing BP and other modifiable risk factors in this population.

Dental service utilization by Europeans aged 50 plus.

OBJECTIVES: To describe variations in the utilization of dental services by persons aged 50+ from 14 European countries and to identify the extent to which such variations are attributable to differences in oral health need and in accessibility of dental care. METHODS: We use data from the Survey of Health, Ageing, and Retirement in Europe (SHARE Waves 2 and 3) and estimate a series of multivariate logistic regression models to analyze variations in dental service utilization (overall dental attendance, preventive treatment and/or operative treatment, dental attendance in early life years) RESULTS: Overall dental attendance and incidence of solely preventive treatment are comparatively high in the Netherlands, Sweden, Denmark, Germany, and Switzerland. In contrast, overall dental attendance is relatively low in Spain, Italy, France, Greece, Poland, and Ireland. Moreover, a high incidence of solely operative treatment is observed in Austria, Italy, and France, whereas in the Netherlands, Sweden, Denmark, Switzerland, and Ireland, the incidence of solely operative treatment is comparably low. By and large, these variations persist even when controlling for cross-country differences in oral health need and in accessibility of dental care. CONCLUSIONS: In comparison with other European regions, there is a tendency toward more frequent and preventive dental treatment of the elderly populations residing in Scandinavia and Western Europe. Such utilization patterns appear only partially attributable to differences in need for and accessibility of dental care.