942 resultados para Quality models


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In this paper, we develop Bayesian hierarchical distributed lag models for estimating associations between daily variations in summer ozone levels and daily variations in cardiovascular and respiratory (CVDRESP) mortality counts for 19 U.S. large cities included in the National Morbidity Mortality Air Pollution Study (NMMAPS) for the period 1987 - 1994. At the first stage, we define a semi-parametric distributed lag Poisson regression model to estimate city-specific relative rates of CVDRESP associated with short-term exposure to summer ozone. At the second stage, we specify a class of distributions for the true city-specific relative rates to estimate an overall effect by taking into account the variability within and across cities. We perform the calculations with respect to several random effects distributions (normal, t-student, and mixture of normal), thus relaxing the common assumption of a two-stage normal-normal hierarchical model. We assess the sensitivity of the results to: 1) lag structure for ozone exposure; 2) degree of adjustment for long-term trends; 3) inclusion of other pollutants in the model;4) heat waves; 5) random effects distributions; and 6) prior hyperparameters. On average across cities, we found that a 10ppb increase in summer ozone level for every day in the previous week is associated with 1.25 percent increase in CVDRESP mortality (95% posterior regions: 0.47, 2.03). The relative rate estimates are also positive and statistically significant at lags 0, 1, and 2. We found that associations between summer ozone and CVDRESP mortality are sensitive to the confounding adjustment for PM_10, but are robust to: 1) the adjustment for long-term trends, other gaseous pollutants (NO_2, SO_2, and CO); 2) the distributional assumptions at the second stage of the hierarchical model; and 3) the prior distributions on all unknown parameters. Bayesian hierarchical distributed lag models and their application to the NMMAPS data allow us estimation of an acute health effect associated with exposure to ambient air pollution in the last few days on average across several locations. The application of these methods and the systematic assessment of the sensitivity of findings to model assumptions provide important epidemiological evidence for future air quality regulations.

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In most species, some individuals delay reproduction or occupy inferior breeding positions. The queue hypothesis tries to explain both patterns by proposing that individuals strategically delay breeding (queue) to acquire better breeding or social positions. In 1995, Ens, Weissing, and Drent addressed evolutionarily stable queuing strategies in situations with habitat heterogeneity. However, their model did not consider the non - mutually exclusive individual quality hypothesis, which suggests that some individuals delay breeding or occupy inferior breeding positions because they are poor competitors. Here we extend their model with individual differences in competitive abilities, which are probably plentiful in nature. We show that including even the smallest competitive asymmetries will result in individuals using queuing strategies completely different from those in models that assume equal competitors. Subsequently, we investigate how well our models can explain settlement patterns in the wild, using a long-term study on oystercatchers. This long-lived shorebird exhibits strong variation in age of first reproduction and territory quality. We show that only models that include competitive asymmetries can explain why oystercatchers' settlement patterns depend on natal origin. We conclude that predictions from queuing models are very sensitive to assumptions about competitive asymmetries, while detecting such differences in the wild is often problematic.

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The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model's ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality's residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained.

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OBJECTIVE: To describe the electronic medical databases used in antiretroviral therapy (ART) programmes in lower-income countries and assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. METHODS: In 15 countries of Africa, South America and Asia, a survey was conducted from December 2006 to February 2007 on the use of electronic medical record systems in ART programmes. Patients enrolled in the sites at the time of the survey but not seen during the previous 12 months were considered lost to follow-up. The quality of the data was assessed by computing the percentage of missing key variables (age, sex, clinical stage of HIV infection, CD4+ lymphocyte count and year of ART initiation). Associations between site characteristics (such as number of staff members dedicated to data management), measures to reduce loss to follow-up (such as the presence of staff dedicated to tracing patients) and data quality and loss to follow-up were analysed using multivariate logit models. FINDINGS: Twenty-one sites that together provided ART to 50 060 patients were included (median number of patients per site: 1000; interquartile range, IQR: 72-19 320). Eighteen sites (86%) used an electronic database for medical record-keeping; 15 (83%) such sites relied on software intended for personal or small business use. The median percentage of missing data for key variables per site was 10.9% (IQR: 2.0-18.9%) and declined with training in data management (odds ratio, OR: 0.58; 95% confidence interval, CI: 0.37-0.90) and weekly hours spent by a clerk on the database per 100 patients on ART (OR: 0.95; 95% CI: 0.90-0.99). About 10 weekly hours per 100 patients on ART were required to reduce missing data for key variables to below 10%. The median percentage of patients lost to follow-up 1 year after starting ART was 8.5% (IQR: 4.2-19.7%). Strategies to reduce loss to follow-up included outreach teams, community-based organizations and checking death registry data. Implementation of all three strategies substantially reduced losses to follow-up (OR: 0.17; 95% CI: 0.15-0.20). CONCLUSION: The quality of the data collected and the retention of patients in ART treatment programmes are unsatisfactory for many sites involved in the scale-up of ART in resource-limited settings, mainly because of insufficient staff trained to manage data and trace patients lost to follow-up.

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Northern peatlands are large reservoirs of soil organic carbon (C). Historically peatlands have served as a sink for C since decomposition is slowed primarily because of a raised water table (WT) that creates anoxic conditions. Climate models are predicting dramatic changes in temperature and precipitation patterns for the northern hemisphere that contain more than 90% of the world’s peatlands. It is uncertain whether climate change will shift northern peatlands from C sequestering systems to a major global C source within the next century because of alterations to peatland hydrology. This research investigated the effects of 80 years of hydrological manipulations on peatland C cycling in a poor fen peatland in northern Michigan. The construction of an earthen levee within the Seney National Wildlife Refuge in the 1930’s resulted in areas of raised and lowered WT position relative to an intermediate WT site that was unaltered by the levee. We established sites across the gradient of long-term WT manipulations to examine how decadal changes in WT position alter peatland C cycling. We quantified vegetation dynamics, peat substrate quality, and pore water chemistry in relation to trace gas C cycling in these manipulated areas as well as the intermediate site. Vegetation in both the raised and lowered WT treatments has different community structure, biomass, and productivity dynamics compared to the intermediate site. Peat substrate quality exhibited differences in chemical composition and lability across the WT treatments. Pore water dissolved organic carbon (DOC) concentrations increased with impoundment and WT drawdown. The raised WT treatment DOC has a low aromaticity and is a highly labile C source, whereas WT drawdown has increased DOC aromaticity. This study has demonstrated a subtle change of the long-term WT position in a northern peatland will induce a significant influence on ecosystem C cycling with implications for the fate of peatland C stocks.

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This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.

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In 186 patients with early colon cancer, we investigated the assumption that the meaning of 'quality of life' (QL) remains constant over time. Within a phase-III trial (SAKK 40/93), patients estimated both their overall QL and a range of disease- and treatment-related domains at five timepoints, comprising three concurrent and 2 retrospective estimates: their pre-surgery QL both before surgery and retrospectively thereafter, and their pre-adjuvant QL both at the beginning of adjuvant treatment and retrospectively about 2 months later, and their current QL 2 weeks thereafter. Multilevel models were developed to determine whether the selected domains made stable contributions to overall QL at the concurrent estimates. The weights of the domains changed over time. They did not differ significantly according to whether patients were considering their concurrent state or reflecting on this state at a later timepoint. In the process of adaptation, patients with early colon cancer substantially change the relative importance of QL domains to overall QL. This finding argues for QL as a changing construct and against the assumption that domain-specific weights are stable across distinct clinical phases.

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Access to sufficient quantities of safe drinking water is a human right. Moreover, access to clean water is of public health relevance, particularly in semi-arid and Sahelian cities due to the risks of water contamination and transmission of water-borne diseases. We conducted a study in Nouakchott, the capital of Mauritania, to deepen the understanding of diarrhoeal incidence in space and time. We used an integrated geographical approach, combining socio-environmental, microbiological and epidemiological data from various sources, including spatially explicit surveys, laboratory analysis of water samples and reported diarrhoeal episodes. A geospatial technique was applied to determine the environmental and microbiological risk factors that govern diarrhoeal transmission. Statistical and cartographic analyses revealed concentration of unimproved sources of drinking water in the most densely populated areas of the city, coupled with a daily water allocation below the recommended standard of 20 l per person. Bacteriological analysis indicated that 93% of the non-piped water sources supplied at water points were contaminated with 10-80 coliform bacteria per 100 ml. Diarrhoea was the second most important disease reported at health centres, accounting for 12.8% of health care service consultations on average. Diarrhoeal episodes were concentrated in municipalities with the largest number of contaminated water sources. Environmental factors (e.g. lack of improved water sources) and bacteriological aspects (e.g. water contamination with coliform bacteria) are the main drivers explaining the spatio-temporal distribution of diarrhoea. We conclude that integrating environmental, microbiological and epidemiological variables with statistical regression models facilitates risk profiling of diarrhoeal diseases. Modes of water supply and water contamination were the main drivers of diarrhoea in this semi-arid urban context of Nouakchott, and hence require a strategy to improve water quality at the various levels of the supply chain.

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Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow-mediated dilation (FMD). In a clinical research centre, 100 non-shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea-hypopnea index. Bivariate correlations and follow-up multiple regressions examined how FMD related to subjective (i.e., Pittsburgh Sleep Quality Index scores) and objective (i.e., polysomnography-derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea-hypopnea index, smoking and income (Ps < 0.05). Specifically, as FMD decreased, scores on the Pittsburgh Sleep Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps < 0.05). Poorer subjective sleep quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease.

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Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

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Health-related quality of life (HRQOL) is an important measure of the effects of chronic liver disease in affected patients that helps guide interventions to improve well-being. However, the relationship between HRQOL and survival in liver transplant candidates remains unclear. We examined whether the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores from the Short Form 36 (SF-36) Health Survey were associated with survival in liver transplant candidates. We administered the SF-36 questionnaire (version 2.0) to patients in the Pulmonary Vascular Complications of Liver Disease study, a multicenter prospective cohort of patients evaluated for liver transplantation in 7 academic centers in the United States between 2003 and 2006. Cox proportional hazards models were used with death as the primary outcome and adjustment for liver transplantation as a time-varying covariate. The mean age of the 252 participants was 54 +/- 10 years, 64% were male, and 94% were white. During the 422 person years of follow-up, 147 patients (58%) were listed, 75 patients (30%) underwent transplantation, 49 patients (19%) died, and 3 patients were lost to follow-up. Lower baseline PCS scores were associated with an increased mortality rate despite adjustments for age, gender, Model for End-Stage Liver Disease score, and liver transplantation (P for the trend = 0.0001). The MCS score was not associated with mortality (P for the trend = 0.53). In conclusion, PCS significantly predicts survival in liver transplant candidates, and interventions directed toward improving the physical status may be helpful in improving outcomes in liver transplant candidates.

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Many ecosystem models have been developed to study the ocean's biogeochemical properties, but most of these models use simple formulations to describe light penetration and spectral quality. Here, an optical model is coupled with a previously published ecosystem model that explicitly represents two phytoplankton (picoplankton and diatoms) and two zooplankton functional groups, as well as multiple nutrients and detritus. Surface ocean color fields and subsurface light fields are calculated by coupling the ecosystem model with an optical model that relates biogeochemical standing stocks with inherent optical properties (absorption, scattering); this provides input to a commercially available radiative transfer model (Ecolight). We apply this bio-optical model to the equatorial Pacific upwelling region, and find the model to be capable of reproducing many measured optical properties and key biogeochemical processes in this region. Our model results suggest that non-algal particles largely contribute to the total scattering or attenuation (> 50% at 660 nm) but have a much smaller contribution to particulate absorption (< 20% at 440 nm), while picoplankton dominate the total phytoplankton absorption (> 95% at 440 nm). These results are consistent with the field observations. In order to achieve such good agreement between data and model results, however, key model parameters, for which no field data are available, have to be constrained. Sensitivity analysis of the model results to optical parameters reveals a significant role played by colored dissolved organic matter through its influence on the quantity and quality of the ambient light. Coupling explicit optics to an ecosystem model provides advantages in generating: (1) a more accurate subsurface light-field, which is important for light sensitive biogeochemical processes such as photosynthesis and photo-oxidation, (2) additional constraints on model parameters that help to reduce uncertainties in ecosystem model simulations, and (3) model output which is comparable to basic remotely-sensed properties. In addition, the coupling of biogeochemical models and optics paves the road for future assimilation of ocean color and in-situ measured optical properties into the models.

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Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

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OBJECTIVE To assess the impact of dental caries and traumatic dental injuries (TDI) on the oral health-related quality of life (OHRQoL) of 5- to 6-year-olds according to both self- and parental reports. METHODS A total of 335 pairs of parents and children who sought dental screening at the Dental School, University of São Paulo, completed the Scale of Oral Health Outcomes for 5-year-old children (SOHO-5), which consists of a child self-report and a parental proxy-report version. Three calibrated examiners assessed the experience of caries according to primary teeth that were decayed, indicated for extraction due to caries, or filled (def-t). TDI were classified into uncomplicated and complicated injuries. Poisson regression models were used to associate the different clinical and sociodemographic factors to the outcome. RESULTS Overall, 74.6% of children reported an oral impact, and the corresponding estimate for parental reports was 70.5%. The mean (standard deviation) SOHO-5 scores in child self-report and parental versions were 3.32(3.22) and 5.18(6.28), respectively. In both versions, caries was associated with worse children's OHRQoL, for the total score and all SOHO-5 items (P < 0.001). In contrast, TDI did not have a negative impact on children's OHRQoL, with the exception of two items of the parental version and one item of the child self-report version. In the final multivariate adjusted models, there was a gradient in the association between caries experience and child's OHRQoL with worse SOHO-5 score at each consecutive level with more severe caries experience, for both child and parental perceptions [RR (CI 95%) = 6.37 (4.71, 8.62) and 10.81 (7.65, 15.27)], respectively. A greater family income had a positive impact on the children's OHRQoL for child and parental versions [RR (CI 95%) = 0.68 (0.49, 0.94) and 0.70 (0.54, 0.90)], respectively. CONCLUSIONS Dental caries, but not TDI, is associated with worse OHRQoL of 5- to 6-year-old children in terms of perceptions of both children and their parents. Families with higher income report better OHRQoL at this age, independent of the presence of oral diseases.

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Background:Coronary heart disease is a major contributor to women's health problems.Design:Self-perceived social support, well-being and health-related quality of life (HRQL) were documented in the cross-sectional HeartQoL survey of European women one and six months after a myocardial infarction.Methods:European women were recruited in 18 European countries and grouped into four geographical regions (Southern Europe, Northern Europe, Western Europe and Eastern Europe). Continuous socio-demographic variables and categorical variables were compared by age and region with ANOVA and χ(2), respectively; multiple regression models were used to identify predictors of social support, well-being and HRQL.Results:Women living in the Eastern European region rated social support, well-being and HRQL significantly lower than women in the other regions. Older women had lower physical HRQL scores than younger women. Eastern European women rated social support, well-being and HRQL significantly lower than women in the other regions. Prediction of the dependent variables (social support, well-being and HRQL) by socio-demographic factors varied by total group, in the older age group, and by region; body mass index and managerial responsibility were the most consistent significant predictors.