Monte Carlo simulation of a whole-body counter using IGOR phantoms.

Whole-body counting is a technique of choice for assessing the intake of gamma-emitting radionuclides. An appropriate calibration is necessary, which is done either by experimental measurement or by Monte Carlo (MC) calculation. The aim of this work was to validate a MC model for calibrating whole-body counters (WBCs) by comparing the results of computations with measurements performed on an anthropomorphic phantom and to investigate the effect of a change in phantom's position on the WBC counting sensitivity. GEANT MC code was used for the calculations, and an IGOR phantom loaded with several types of radionuclides was used for the experimental measurements. The results show a reasonable agreement between measurements and MC computation. A 1-cm error in phantom positioning changes the activity estimation by >2%. Considering that a 5-cm deviation of the positioning of the phantom may occur in a realistic counting scenario, this implies that the uncertainty of the activity measured by a WBC is ∼10-20%.

Risk perception by healthcare professionals related to drug use during pregnancy: a Swiss survey.

PRINCIPLE: Healthcare professionals' (HCPs') perception of risk associated with drug use in pregnancy may have an impact on the pharmacological treatment of some women. The aim of this study was to examine this risk perception in a sample of Swiss HCPs with a special focus on their knowledge and use of available specialised information sources. METHOD: An online, French and German, questionnaire was e-mailed to 7,136 members of four Swiss professional societies (gynaecologists, paediatricians, midwives and pharmacists). The questionnaire was designed (a) to collect demographic characteristics, (b) to evaluate the frequency of use of several specialised sources of information on drugs in pregnancy in their daily practice, and (c) to examine the perception of risk associated with drug use during pregnancy. RESULTS: A total of 1,310 questionnaires were collected (response rate of 18.4%). More than 80% of the respondent HCPs use the Swiss Drug Reference Book (Compendium) to assess the risk associated with drugs during pregnancy and are not aware of available specialised information sources (books, websites or information centres). Despite some disparities between HPCs, the risk related to drug intake was overall highly misperceived. Blinded reading of three product monographs in the Compendium was associated with an overestimated perception of risk (e.g., after reading the "paracetamol" monograph, 38% of the participants stated they would probably not advise the use of this drug to a pregnant patient). CONCLUSION: Overall, an overestimation of the risk associated with drug use during pregnancy has been observed in our sample of HCPs, which might be related to the underuse of specialised information source among other factors. These findings evidenced the need for increased training for HCPs in order to optimise medication use during pregnancy. Further studies are needed to confirm these results and identify causes.

Simulation of interface dynamics across pore discontinuities

We study the dynamics of a water-oil meniscus moving from a smaller to a larger pore. The process is characterised by an abrupt change in the configuration, yielding a sudden energy release. A theoretic study for static conditions provides analytical solutions of the surface energy content of the system. Although the configuration after the sudden energy release is energetically more convenient, an energy barrier must be overcome before the process can happen spontaneously. The energy barrier depends on the system geometry and on the flow parameters. The analytical results are compared to numerical simulations that solve the full Navier-Stokes equation in the pore space and employ the Volume Of Fluid (VOF) method to track the evolution of the interface. First, the numerical simulations of a quasi-static process are validated by comparison with the analytical solutions for a static meniscus, then numerical simulations with varying injection velocity are used to investigate dynamic effects on the configuration change. During the sudden energy jump the system exhibits an oscillatory behaviour. Extension to more complex geometries might elucidate the mechanisms leading to a dynamic capillary pressure and to bifurcations in final distributions of fluid phases in porous

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Factors associated with healthcare professionals' intent to stay in hospital: a comparison across five occupational categories.

OBJECTIVE: To identify factors associated with intent to stay in hospital among five different categories of healthcare professionals using an adapted version of the conceptual model of intent to stay (CMIS). DESIGN: A cross-sectional survey targeting Lausanne University Hospital employees performed in the fall of 2011. Multigroup structural equation modeling was used to test the adapted CMIS model among professional groups. Measures Satisfaction, self-fulfillment, workload, working conditions, burnout, overall job satisfaction, institutional identification and intent to stay. PARTICIPANTS: Surveys of 3364 respondents: 494 physicians, 1228 nurses, 509 laboratory technicians, 935 administrative staff and 198 psycho-social workers. RESULTS: For all professional categories, self-fulfillment increased intent to stay (all β > 0.14, P < 0.05). Burnout decreased intent to stay by weakening job satisfaction (β < -0.23 and β > 0.22, P < 0.05). Some factors were associated with specific professional categories: workload was associated with nurses' intent to stay (β = -0.15), and physicians' institutional identification mitigated the effect of burnout on intent to stay (β = -0.15 and β = 0.19). CONCLUSION: Respondents' intent to stay in a position depended both on global and profession-specific factors. The identification of these factors may help in mapping interventions and retention plans at both a hospital level and professional groups' level.

Impact de la prophylaxie hormonale sur les fractures du fémur proximal des femmes postménopausiques: une étude de simulation. [Impact of hormonal prevention on fractures of the proximal femur in postmenopausal women: a simulation study].

A simulation model of the effects of hormone replacement therapy (HRT) on hip fractures and their consequences is based on a population of 100,000 post-menopausal women. This cohort is confronted with literature derived probabilities of cancers (endometrium or breast, which are contra-indications to HRT), hip fracture, disability requiring nursing home or home care, and death. Administration of HRT for life prevents 55,5% of hip fractures, 22,6% of years with home care and 4,4% of years in nursing homes. If HRT is administered for 15 years, these results are 15,5%, 10% and 2,2%, respectively. A slight gain in life expectancy is observed for both durations of HRT. The net financial loss in the simulated population is 222 million Swiss Francs (cost/benefit ratio 1.25) for lifelong administration of HRT, and 153 million Swiss Francs (cost/benefit ratio 1.42) if HRT is administered during 15 years.

Diabetes care: opinions, needs and proposed solutions of Swiss patients and healthcare professionals: a qualitative study.

AIMS: To explore, both among patients with diabetes and healthcare professionals, opinions on current diabetes care and the development of the "Regional Diabetes Program". METHODS: We employed qualitative methods (focus groups - FG) and used purposive sampling strategy to recruit patients with diabetes and healthcare professionals. We conducted one diabetic and one professional FG in each of the four health regions of the canton of Vaud/Switzerland. The eight FGs were audio-taped and transcribed verbatim. Thematic analysis was then undertaken. RESULTS: Results showed variability in the perception of the quality of diabetes care, pointed to insufficient information regarding diabetes, and lack of collaboration. Participants also evoked patients' difficulties for self-management, as well as professionals' and patients' financial concerns. Proposed solutions included reinforcing existing structures, developing self-management education, and focusing on comprehensive and coordinated care, communication and teamwork. Patients and professionals were in favour of a "Regional Diabetes Program" tailored to the actors' needs, and viewed it as a means to reinforce existing care delivery. CONCLUSIONS: Patients and professionals pointed out similar problems and solutions but explored them differently. Combined with coming quantitative data, these results should help to further develop, adapt and implement the "Regional Diabetes Program".

Simulit, un modèle de simulation pour la planification hospitalière. [Simulit, a simulation model for hospital planning].

The aim of this computerized simulation model is to provide an estimate of the number of beds used by a population, taking into accounts important determining factors. These factors are demographic data of the deserved population, hospitalization rates, hospital case-mix and length of stay; these parameters can be taken either from observed data or from scenarii. As an example, the projected evolution of the number of beds in Canton Vaud for the period 1893-2010 is presented.

Simulated-annealing-based conditional simulation for the local-scale characterization of heterogeneous aquifers

Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.