Predictors of thromboprophylaxis in hospitalised medical patients. Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE).

Both, underuse and overuse of thromboprophylaxis in hospitalised medical patients is common. We aimed to explore clinical factors associated with the use of pharmacological or mechanical thromboprophylaxis in acutely ill medical patients at high (Geneva Risk Score ≥ 3 points) vs low (Geneva Risk Score < 3 points) risk of venous thromboembolism. Overall, 1,478 hospitalised medical patients from eight large Swiss hospitals were enrolled in the prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study. The study is registered on ClinicalTrials.gov, number NCT01277536. Thromboprophylaxis increased stepwise with increasing Geneva Risk Score (p< 0.001). Among the 962 high-risk patients, 366 (38 %) received no thromboprophylaxis; cancer-associated thrombocytopenia (OR 4.78, 95 % CI 2.75-8.31, p< 0.001), active bleeding on admission (OR 2.88, 95 % CI 1.69-4.92, p< 0.001), and thrombocytopenia without cancer (OR 2.54, 95 % CI 1.31-4.95, p=0.006) were independently associated with the absence of prophylaxis. The use of thromboprophylaxis declined with increasing severity of thrombocytopenia (p=0.001). Among the 516 low-risk patients, 245 (48 %) received thromboprophylaxis; none of the investigated clinical factors predicted its use. In conclusion, in acutely ill medical patients, bleeding and thrombocytopenia were the most important factors for the absence of thromboprophylaxis among high-risk patients. The use of thromboprophylaxis among low-risk patients was inconsistent, without clearly identifiable predictors, and should be addressed in further research.

Jewish contributions to civilization : an estimate

by Joseph Jacobs

SALSA: a tool to estimate the stray light contamination for low-Earth orbit observatories

Stray light contamination reduces considerably the precision of photometric of faint stars for low altitude spaceborne observatories. When measuring faint objects, the necessity of coping with stray light contamination arises in order to avoid systematic impacts on low signal-to-noise images. Stray light contamination can be represented by a flat offset in CCD data. Mitigation techniques begin by a comprehensive study during the design phase, followed by the use of target pointing optimisation and post-processing methods. We present a code that aims at simulating the stray-light contamination in low-Earth orbit coming from reflexion of solar light by the Earth. StrAy Light SimulAtor (SALSA) is a tool intended to be used at an early stage as a tool to evaluate the effective visible region in the sky and, therefore to optimise the observation sequence. SALSA can compute Earth stray light contamination for significant periods of time allowing missionwide parameters to be optimised (e.g. impose constraints on the point source transmission function (PST) and/or on the altitude of the satellite). It can also be used to study the behaviour of the stray light at different seasons or latitudes. Given the position of the satellite with respect to the Earth and the Sun, SALSA computes the stray light at the entrance of the telescope following a geometrical technique. After characterising the illuminated region of the Earth, the portion of illuminated Earth that affects the satellite is calculated. Then, the flux of reflected solar photons is evaluated at the entrance of the telescope. Using the PST of the instrument, the final stray light contamination at the detector is calculated. The analysis tools include time series analysis of the contamination, evaluation of the sky coverage and an objects visibility predictor. Effects of the South Atlantic Anomaly and of any shutdown periods of the instrument can be added. Several designs or mission concepts can be easily tested and compared. The code is not thought as a stand-alone mission designer. Its mandatory inputs are a time series describing the trajectory of the satellite and the characteristics of the instrument. This software suite has been applied to the design and analysis of CHEOPS (CHaracterizing ExOPlanet Satellite). This mission requires very high precision photometry to detect very shallow transits of exoplanets. Different altitudes and characteristics of the detector have been studied in order to find the best parameters, that reduce the effect of contamination. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

A Genetic Algorithm to associate optical measurements and estimate orbits of geocentric objects

Cataloging geocentric objects can be put in the framework of Multiple Target Tracking (MTT). Current work tends to focus on the S = 2 MTT problem because of its favorable computational complexity of O(n²). The MTT problem becomes NP-hard for a dimension of S˃3. The challenge is to find an approximation to the solution within a reasonable computation time. To effciently approximate this solution a Genetic Algorithm is used. The algorithm is applied to a simulated test case. These results represent the first steps towards a method that can treat the S˃3 problem effciently and with minimal manual intervention.

Relative estimate of accuracy in orbit determination from a short tracklet

The Astronomical Institute of the University of Bern (AIUB) is conducting several search campaigns for orbital debris. The debris objects are discovered during systematic survey observations. In general only a short observation arc, or tracklet, is available for most of these objects. From this discovery tracklet a first orbit determination is computed in order to be able to find the object again in subsequent follow-up observations. The additional observations are used in the orbit improvement process to obtain accurate orbits to be included in a catalogue. In this paper, the accuracy of the initial orbit determination is analyzed. This depends on a number of factors: tracklet length, number of observations, type of orbit, astrometric error, and observation geometry. The latter is characterized by both the position of the object along its orbit and the location of the observing station. Different positions involve different distances from the target object and a different observing angle with respect to its orbital plane and trajectory. The present analysis aims at optimizing the geometry of the discovery observation is depending on the considered orbit.

Nonperturbative estimate of the heavy quark momentum diffusion coefficient

We estimate the momentum diffusion coefficient of a heavy quark within a pure SU(3) plasma at a temperature of about 1.5Tc. Large-scale Monte Carlo simulations on a series of lattices extending up to 1923×48 permit us to carry out a continuum extrapolation of the so-called color-electric imaginary-time correlator. The extrapolated correlator is analyzed with the help of theoretically motivated models for the corresponding spectral function. Evidence for a nonzero transport coefficient is found and, incorporating systematic uncertainties reflecting model assumptions, we obtain κ=(1.8–3.4)T3. This implies that the “drag coefficient,” characterizing the time scale at which heavy quarks adjust to hydrodynamic flow, is η−1D=(1.8–3.4)(Tc/T)2(M/1.5  GeV)  fm/c, where M is the heavy quark kinetic mass. The results apply to bottom and, with somewhat larger systematic uncertainties, to charm quarks.

A case-control study to estimate the effects of acute clinical infection with the Schmallenberg virus on milk yield, fertility and veterinary costs in Swiss dairy herds.

Schmallenberg virus (SBV) was first detected in Switzerland in July 2012 and many Swiss dairy farmers reported acute clinical signs in dairy cattle during the spread of the virus until December 2012. The objectives of the present study were to investigate the effects of an acute infection with SBV on milk yield, fertility and veterinary costs in dairy farms with clinical signs of SBV infection (case farms), and to compare those farms to a matched control group of dairy farms in which cattle did not show clinical signs of SBV infection. Herd size was significantly (p<0.001) larger in case farms (33 cows, n=77) than in control farms (25 cows, n=84). Within case herds, 14.8% (median) of the cows showed acute clinical signs. Managers from case farms indicated to have observed a higher abortion rate during the year with SBV (6.5%) than in the previous year (3.7%). Analysis of fertility parameters based on veterinary bills and data from the breeding associations showed no significant differences between case and control farms. The general veterinary costs per cow from July to December 2012 were significantly higher (p=0.02) in case (CHF 19.80; EUR 16.50) than in control farms (CHF 15.90; EUR 13.25). No differences in milk yield were found between groups, but there was a significant decrease in milk production in case farms in the second half year in 2012 compared to the same period in 2011 (p<0.001) and 2013 (p=0.009). The average daily milk yield per cow (both groups together) was +0.73kg higher (p=0.03) in the second half year 2011 and +0.52kg (p=0.12) in the second half year 2013 compared to the same half year 2012. Fifty-seven percent of the cows with acute clinical signs (n=461) were treated by a veterinarian. The average calculated loss after SBV infection for a standardized farm was CHF 1606 (EUR 1338), which can be considered as low at the national level, but the losses were subject to great fluctuations between farms, so that individual farms could have very high losses (>CHF 10,000, EUR 8333).

A Bootstrap-Regression Procedure to Capture Unit Specific Effects in Data Envelopment Analysis

The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.

Bexar County's dental safety net for children: An estimate of our current capacity and need

Introduction. It has been well established that poor uninsured children lack access to dental care and have greater dental needs than their insured counterparts. ^ Objective. To assess the capacity of Bexar County's dental safety net to treat children. To assess the dental needs of Bexar County children ages 0-18 who are uninsured or are Medicaid or SCHIP recipients. ^ Methods. Information was requested from dental safety net clinics that treat children ages 0-18. Data from the census, NHANES and other sources was used to estimate the dental needs. ^ Results. The capacity of the current safety net to treat children is 33,537 patient encounters per year. The dental needs of the community are 227,124 patient encounters per year. ^ Conclusion. The results of the study indicate that Bexar County is not prepared to treat the dental needs of the underserved children in San Antonio.^

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Aedes aegypti, Aedes albopictus, and Dengue virus in Harris county: An estimate of risk

Recent outbreaks of dengue fever (DF) along the United States/Mexico border, coupled with the high number of reported cases in Mexico suggest that there is the possibility for DF emergence in Houston, Texas1,2. To determine the presence of DF, populations of Aedes aegypti and Aedes albopictus were identified and tested for dengue virus. Maps were created to identify "hot spots" (Figure 1) based on historical data on Ae. aegypti and Ae. albopictus, demographic information, and locations of human cases of dengue fever. BG Sentinel Traps®, in conjunction with BG Lure® attractant, octanol and dry ice, were used to collect mosquitoes, which were then tested for presence of dengue virus using ELISA techniques. All samples tested were negative for dengue virus (DV). Survival of DV ultimately comes down to whether or not it will be vectored by a mosquito to a susceptible human host. The presence of infected humans and contact with the mosquito vectors are two critical factors necessary in the establishment of DF. Historical records indicate the presence of Ae. aegypti and Ae. albopictus in Harris County, which would support localized dengue transmission if infected individuals are present.^ (1) Brunkard JM, Robles-Lopez JL, Ramirez J, Cifuentes E, Rothenberg SJ, Hunsperger EA, Moore CG, Brussolo RM, Villarreal NA, Haddad BM, 2007. Dengue fever seroprevalence and risk factors, Texas-Mexico border, 2004. Emerg Infect Dis 13: 1477-1483. (2) Ramos MM, Mohammed H, Zielinski-Gutierrez E, Hayden MH, Lopez JL, Fournier M, Trujillo AR, Burton R, Brunkard JM, Anaya-Lopez L, Banicki AA, Morales PK, Smith B, Munoz JL, Waterman SH, 2008. Epidemic dengue and dengue hemorrhagic fever at the Texas-Mexico Border: results of a household-based seroepidemiologic survey, December 2005. Am J Trop Med Hyg 78: 364-369.^

A PROPOSED SAMPLE-BASED TECHNIQUE TO ESTIMATE THE STANDARDIZED MORTALITY RATIO

Evaluation of a series of deaths due to a particular disease is a frequently requested task in occupational epidemiology. There are several techniques available to determine whether a series represents an occupational health problem. Each of these techniques, however, is subject to certain limitations including cost, applicability to a given situation, feasibility relative to available resources, or potential for bias. In light of these problems, a technique was developed to estimate the standardized mortality ratio at a greatly reduced cost. The technique is demonstrated by its application in the investigation of brain cancer among employees of a large chemical company. ^