929 resultados para Discharge coefficients


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BACKGROUND It is often assumed that horses with mild respiratory clinical signs, such as mucous nasal discharge and occasional coughing, have an increased risk of developing recurrent airway obstruction (RAO). HYPOTHESIS Compared to horses without any clinical signs of respiratory disease, those with occasional coughing, mucous nasal discharge, or both have an increased risk of developing signs of RAO (frequent coughing, increased breathing effort, exercise intolerance, or a combination of these) as characterized by the Horse Owner Assessed Respiratory Signs Index (HOARSI 1-4). ANIMALS Two half-sibling families descending from 2 RAO-affected stallions (n = 65 and n = 47) and an independent replication population of unrelated horses (n = 88). METHODS In a retrospective cohort study, standardized information on occurrence and frequency of coughing, mucous nasal discharge, poor performance, and abnormal breathing effort-and these factors combined in the HOARSI-as well as management factors were collected at intervals of 1.3-5 years. RESULTS Compared to horses without clinical signs of respiratory disease (half-siblings 7%; unrelated horses 3%), those with mild respiratory signs developed clinical signs of RAO more frequently: half-siblings with mucous nasal discharge 35% (P < .001, OR: 7.0, sensitivity: 62%, specificity: 81%), with mucous nasal discharge and occasional coughing 43% (P < .001, OR: 9.9, sensitivity: 55%, specificity: 89%); unrelated horses with occasional coughing: 25% (P = .006, OR = 9.7, sensitivity: 75%, specificity: 76%). CONCLUSIONS AND CLINICAL IMPORTANCE Occasional coughing and mucous nasal discharge might represent an increased risk of developing RAO.

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BACKGROUND Cold atmospheric plasma (CAP, i.e. ionized air) is an innovating promising tool in reducing bacteria. OBJECTIVE We conducted the first clinical trial with the novel PlasmaDerm(®) VU-2010 device to assess safety and, as secondary endpoints, efficacy and applicability of 45 s/cm(2) cold atmospheric plasma as add-on therapy against chronic venous leg ulcers. METHODS From April 2011 to April 2012, 14 patients were randomized to receive standardized modern wound care (n = 7) or plasma in addition to standard care (n = 7) 3× per week for 8 weeks. The ulcer size was determined weekly (Visitrak(®) , photodocumentation). Bacterial load (bacterial swabs, contact agar plates) and pain during and between treatments (visual analogue scales) were assessed. Patients and doctors rated the applicability of plasma (questionnaires). RESULTS The plasma treatment was safe with 2 SAEs and 77 AEs approximately equally distributed among both groups (P = 0.77 and P = 1.0, Fisher's exact test). Two AEs probably related to plasma. Plasma treatment resulted in a significant reduction in lesional bacterial load (P = 0.04, Wilcoxon signed-rank test). A more than 50% ulcer size reduction was noted in 5/7 and 4/7 patients in the standard and plasma groups, respectively, and a greater size reduction occurred in the plasma group (plasma -5.3 cm(2) , standard: -3.4 cm(2) ) (non-significant, P = 0.42, log-rank test). The only ulcer that closed after 7 weeks received plasma. Patients in the plasma group quoted less pain compared to the control group. The plasma applicability was not rated inferior to standard wound care (P = 0.94, Wilcoxon-Mann-Whitney test). Physicians would recommend (P = 0.06, Wilcoxon-Mann-Whitney test) or repeat (P = 0.08, Wilcoxon-Mann-Whitney test) plasma treatment by trend. CONCLUSION Cold atmospheric plasma displays favourable antibacterial effects. We demonstrated that plasma treatment with the PlasmaDerm(®) VU-2010 device is safe and effective in patients with chronic venous leg ulcers. Thus, larger controlled trials and the development of devices with larger application surfaces are warranted.

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Radiogenic He is produced by the decay of uranium and thorium in the Earth’s mantle and crust. From here, it is degassed to the atmosphere and eventually escapes to space. Assuming that all of the 4He produced is degassed, about 70% of the total He degassed from Earth comes from the continental crust. However, the outgoing flux of crustal He has not been directly measured at the Earth’s surface and the migration pathways are poorly understood. Here we present measurements of helium isotopes and the long-lived cosmogenic radio-isotope Kr in the deep, continental-scale Guarani aquifer in Brazil and show that crustal He reaches the atmosphere primarily by the surficial discharge of deep groundwater. We estimate that He in Guarani groundwater discharge accounts for about 20% of the assumed global flux from continental crust, and that other large aquifers may account for about 33%. Old groundwater ages suggest that He in the Guarani aquifer accumulates over half- to one-millionyear timescales. We conclude that He degassing from the continents is regulated by groundwater discharge, rather than episodic tectonic events, and suggest that the assumed steady state between crustal production and degassing of He, and its resulting atmospheric residence time, should be re-examined.

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Graphical display of regression results has become increasingly popular in presentations and in scientific literature because graphs are often much easier to read than tables. Such plots can be produced in Stata by the marginsplot command (see [R] marginsplot). However, while marginsplot is versatile and flexible, it has two major limitations: it can only process results left behind by margins (see [R] margins), and it can handle only one set of results at a time. In this article, I introduce a new command called coefplot that overcomes these limitations. It plots results from any estimation command and combines results from several models into one graph. The default behavior of coefplot is to plot markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce other types of graphs. I illustrate the capabilities of coefplot by using a series of examples.

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PURPOSE To determine the variability of apparent diffusion coefficient (ADC) values in various anatomic regions in the upper abdomen measured with magnetic resonance (MR) systems from different vendors and with different field strengths. MATERIALS AND METHODS Ten healthy men (mean age, 36.6 years ± 7.7 [standard deviation]) gave written informed consent to participate in this prospective ethics committee-approved study. Diffusion-weighted (DW) MR imaging was performed in each subject with 1.5- and 3.0-T MR systems from each of three vendors at two institutions. Two readers independently measured ADC values in seven upper abdominal regions (left and right liver lobe, gallbladder, pancreas, spleen, and renal cortex and medulla). ADC values were tested for interobserver differences, as well as for differences related to field strength and vendor, with repeated-measures analysis of variance; coefficients of variation (CVs) and variance components were calculated. RESULTS Interreader agreement was excellent (intraclass coefficient, 0.876). ADC values were (77.5-88.8) ×10(-5) mm(2)/sec in the spleen and (250.6-278.5) ×10(-5) mm(2)/sec in the gallbladder. There were no significant differences between ADC values measured at 1.5 T and those measured at 3.0 T in any anatomic region (P >.10 for all). In two of seven regions at 1.5 T (left and right liver lobes, P < .023) and in four of seven regions at 3.0 T (left liver lobe, pancreas, and renal cortex and medulla, P < .008), intervendor differences were significant. CVs ranged from 7.0% to 27.1% depending on the anatomic location. CONCLUSION Despite significant intervendor differences in ADC values of various anatomic regions of the upper abdomen, ADC values of the gallbladder, pancreas, spleen, and kidney may be comparable between MR systems from different vendors and between different field strengths.

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Objectives: Depression is associated with poor prognosis in patients with cardiovascular disease (CVD). We hypothesized that depressive symptoms at discharge from a cardiac rehabilitation program are associated with an increased risk of future CVD-related hospitalizations. Methods: We examined 486 CVD patients (mean age = 59.8 ± 11.2) who enrolled in a comprehensive 3-month rehabilitation program and completed the depression subscale of the Hospital Anxiety and Depression Scale (HADS-D). At follow-up we evaluated the predictive value of depressive symptoms for CVD-related hospitalizations, controlling for sociodemographic factors, cardiovascular risk factors, and disease severity. Results: During a mean follow-up of 41.5 ± 15.6 months, 63 patients experienced a CVD-related hospitalization. The percentage of depressive patients (HADS-D ≥ 8) decreased from 16.9% at rehabilitation entry to 10.7% at discharge. Depressive symptoms at discharge from rehabilitation were a significant predictor of outcome (HR 1.32, 95% CI 1.09–1.60; p =0.004). Patients with clinically relevant depressive symptoms at discharge had a 2.5-fold increased relative risk of poor cardiac prognosis compared to patients without clinically relevant depressive symptoms independently of other prognostic variables. Conclusion: In patients with CVD, depressive symptoms at discharge from rehabilitation indicated a poor cardiac prognosis.

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The evolution of landscapes crucially depends on the climate history. This is particularly evident in South America where landscape responses to orbital climate shifts have been well documented. However, while most studies have focused on inferring temperature variations from paleoclimate proxy data, estimates of water budget changes have been complicated because of a lack of adequate physical information. Here, we present a methodology and related results, which allowed us to extract water discharge values from the sedimentary record of the 40 Ka-old fluvial terrace deposits in the Pisco valley, western Peru. In particular, this valley hosts a Quaternary cut-and-fill succession that we used, in combination with beryllium-10 (10Be)-based sediment flux, gauging records, channel geometries and grain size measurements, to quantitatively assess sediment and water discharge values c. 40 Ka ago in relation to present-day conditions. We compare these discharge estimates to the discharge regime of the modern Pisco River and find that the water discharge of the paleo-Pisco River, during the Minchin pluvial period c. 40 Ka ago, was c. 7–8 times greater than the modern Pisco River if considering the mean and the maximum water discharge. In addition, the calculations show that inferred water discharge estimates are mainly dependent on channel gradients and grain size values, and to a lesser extent on channel width measures. Finally, we found that the c. 40 Ka-old Minchin terrace material was poorer sorted than the modern deposits, which might reflect that sediment transport during the past period was characterized by a larger divergence from equal mobility compared to the modern situation. In summary, the differences in grain size distribution and inferred water discharge estimates between the modern and the paleo-Pisco River suggests that the 40 Ka-old Minchin period was characterized by a wetter climate and more powerful flood events.

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Accurate rainfall data are the key input parameter for modelling river discharge and soil loss. Remote areas of Ethiopia often lack adequate precipitation data and where these data are available, there might be substantial temporal or spatial gaps. To counter this challenge, the Climate Forecast System Reanalysis (CFSR) of the National Centers for Environmental Prediction (NCEP) readily provides weather data for any geographic location on earth between 1979 and 2014. This study assesses the applicability of CFSR weather data to three watersheds in the Blue Nile Basin in Ethiopia. To this end, the Soil and Water Assessment Tool (SWAT) was set up to simulate discharge and soil loss, using CFSR and conventional weather data, in three small-scale watersheds ranging from 112 to 477 ha. Calibrated simulation results were compared to observed river discharge and observed soil loss over a period of 32 years. The conventional weather data resulted in very good discharge outputs for all three watersheds, while the CFSR weather data resulted in unsatisfactory discharge outputs for all of the three gauging stations. Soil loss simulation with conventional weather inputs yielded satisfactory outputs for two of three watersheds, while the CFSR weather input resulted in three unsatisfactory results. Overall, the simulations with the conventional data resulted in far better results for discharge and soil loss than simulations with CFSR data. The simulations with CFSR data were unable to adequately represent the specific regional climate for the three watersheds, performing even worse in climatic areas with two rainy seasons. Hence, CFSR data should not be used lightly in remote areas with no conventional weather data where no prior analysis is possible.

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There is a growing concern by regulatory authorities for the selection of antibiotic resistance caused by the use of biocidal products. We aimed to complete the detailed information on large surveys by investigating the relationship between biocide and antibiotic susceptibility profiles of a large number of Staphylococcus aureus isolates using four biocides and antibiotics commonly used in clinical practice. The minimal inhibitory concentration (MIC) for most clinically-relevant antibiotics was determined according to the standardized methodology for over 1600 clinical S. aureus isolates and compared to susceptibility profiles of benzalkonium chloride, chlorhexidine, triclosan, and sodium hypochlorite. The relationship between antibiotic and biocide susceptibility profiles was evaluated using non-linear correlations. The main outcome evidenced was an absence of any strong or moderate statistically significant correlation when susceptibilities of either triclosan or sodium hypochlorite were compared for any of the tested antibiotics. On the other hand, correlation coefficients for MICs of benzalkonium chloride and chlorhexidine were calculated above 0.4 for susceptibility to quinolones, beta-lactams, and also macrolides. Our data do not support any selective pressure for association between biocides and antibiotics resistance and furthermore do not allow for a defined risk evaluation for some of the compounds. Importantly, our data clearly indicate that there does not involve any risk of selection for antibiotic resistance for the compounds triclosan and sodium hypochlorite. These data hence infer that biocide selection for antibiotic resistance has had so far a less significant impact than feared.

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A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

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As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^