Related Covariates Research Articles

Real-Time Estimation of Arterial Travel Times with Spatial Travel Time Covariance Relationships

This paper investigates the use of real-time automatic vehicle identification (AVI) data and an offline travel time database for real-time estimation of arterial travel times in Hong Kong, China. The offline database consists of average link travel times and spatial link travel time covariance matrices by time of day, day of week, and week of month. Three-month historical travel time estimates and real-time AVI data are adopted for calibration and updating of the spatial covariance relationships of link travel times on Hong Kong arterial roads. A case study has been carried out on a selected path in a Hong Kong urban area to evaluate the performance of three alternative methods for real-time estimation of arterial travel times: fixed offline database (Method 1), continuously updated offline database (Method 2), and continuously updated offline database generated by the nonparametric regression method (Method 3). The validation results show that the travel time estimation errors of Methods 2 and 3 are significantly reduced when compared with those using the fixed offline database.

An analytical formulation of the law of intersegmental coordination during human locomotion

The law of intersegmental coordination is a kinematic law that describes the coordination patterns among the elevation angles of the lower limb segments during locomotion (Borghese et al. in J Physiol 494:863-879, 1996). This coordination pattern reduces the number of degrees of freedom of the lower limb to two, i.e. the elevation angles covary along a plane in angular space. The properties of the plane that constrains the time course of the elevation angles have been extensively studied, and its orientation was found to be correlated with gait velocity and energy expenditure (Bianchi et al. in J Neurophysiol 79:2155-2170, 1998). Here, we present a mathematical model that represents the rotations of the elevation angles in terms of simple oscillators with appropriate phase shifts between them. The model explains what requirements the time courses of the elevation angles must fulfill in order for the angular covariation relationship to be planar. Moreover, an analytical formulation is proposed for both the orientation of the plane and for the eccentricity of the nearly elliptical shape that is generated within this plane, in terms of the amplitudes and relative phases of the first harmonics of the segments elevation angles. The model presented here sheds some new light on the possible interactions among the Central Pattern Generators possibly underlying the control of biped locomotion. The model precisely specifies how any two segments in the limb interact, and how a change in gait velocity affects the orientation of the intersegmental coordination plane mainly through a change in phase shifts between the segments. Implications of this study with respect to neural control of locomotion and other motor activities are discussed.

Chemometrics description of measurement error structure: Study of an ultrafast absorption spectroscopy experiment

The error structure inherent to a transient absorption spectroscopy kinetic experiment is described through the examination of the related measurement error covariance matrices in the time and the spectral direction. The systematic approach proposed by Wentzell's group to characterize the measurement error covariance matrices is used for this purpose. The goals of this study are identifying and modelling the factors contributing to the error measurement and proposing a weighting error-based scheme that can be generally used when analysing data coming from this experimental setup. From the analysis performed, independent noise structure is associated with the time direction of the data sets, whereas the spectral direction is affected by two sources of correlated errors, which can be related to the probe spectrum and to the mean signal registered.

Epidemiology of chronic kidney disease: Results from a population of older adults in Germany

Objective To determine prevalences and stages of chronic kidney disease (CKD), and evaluate association of CKD with related covariables in a large population of older adults. Methods This cross-sectional analysis included 9806 participants of a general health check-up aged 50–74 years in Germany. We performed multivariate analysis to identify association of CKD with related covariables. Partial spearman correlations of eGFR with related biomarkers were calculated. Results Overall, 17.4% of subjects had CKD. Prevalences of stages 1, 2, 3, 4/5 CKD were 4.6%, 4.7%, 17.0% and 0.4%, respectively. Prevalence of CKD increased with age and peaked in age 70–74 years with 23.9%. In multivariable analysis of older age, female, self-reported history of cardiovascular diseases, diabetes and statin usage were independently associated with increased risk for CKD. Significant correlations were found between eGFR and serum cystatin C (− 0.28), C-reactive protein (− 0.04), fasting glucose (0.12), HbA 1c (− 0.06), total cholesterol (− 0.32), and triglycerides (− 0.07) after adjustment for covariates. Conclusions This study shows a high prevalence of CKD among older adults. It highlights the association of eGFR with history of cardiovascular diseases, glycemic markers, and cardiovascular risk factors and may point to further possible targets in early prevention of CKD.

Vaccination Uptake and Awareness of a Free Hepatitis B Vaccination Program Among Female Commercial Sex Workers

We sought to explore the reach of a free hepatitis B vaccination program among female commercial sex workers (CSWs) within a legalized prostitution setting in the Netherlands. We also investigated the reasons for nonparticipation and noncompliance. In this cross-sectional study based on ethnographic mapping and targeted sampling, 259 CSWs were interviewed at their work in 3 regions in the Netherlands. The semistructured interviews contained questions on sociodemographics, sexual risk behavior, sex work, awareness of the opportunity to obtain free hepatitis B vaccination, vaccination uptake, and compliance with the full vaccination schedule. Of our sample, 79% reported awareness of the opportunity to obtain hepatitis B vaccination, and 63% reported to be vaccinated against hepatitis B (received > or =1 vaccination). A personal approach by health professionals or was associated with vaccination uptake, when specific sociodemographic variables, sexual behavior, and sex work related covariates were controlled for in the analysis. Window prostitution and the duration of working in the region were associated with awareness of the opportunity to obtain free hepatitis B vaccination. The results of this study suggest that outreach activities (i.e., a personal approach) within this program are beneficial. Transient CSWs are more difficult to reach within the current vaccination program. These results can be used to increase the success of future health programs among this risk group.

Living in Partner-violent Families: Developmental Links to Antisocial Behavior and Relationship Violence

Links between living in a partner-violent home and subsequent aggressive and antisocial behavior are suggested by the "cycle of violence" hypothesis derived from social learning theory. Although there is some empirical support, to date, findings have been generally limited to cross-sectional studies predominantly of young children, or retrospective studies of adults. We address this issue with prospective data from the Rochester Youth Development Study (RYDS), an ongoing longitudinal investigation of the development of antisocial behavior in a community sample of 1,000 urban youth followed from age 14 to adulthood. The original panel included 68% African American, 17% Hispanic, and 15% White participants, and was 72.9% male, and 27.1% female. Measures come from a combination of sources including interviews with parents, interviews with youth, and official records. We test the general hypothesis that there is a relationship between living in partner-violent homes during adolescence, and later antisocial behavior and relationship violence. Employing logistic regression and controlling for related covariates, including child physical abuse, we find a significant relationship between exposure to parental violence and adolescent conduct problems. The relationship between exposure to parental violence and measures of antisocial behavior and relationship aggression dissipates in early adulthood, however, exposure to severe parental violence is significantly related to early adulthood violent crime, and intimate partner violence. Our results suggest that exposure to severe parental violence during adolescence is indeed consequential for violent interactions in adulthood.

Mapping surface currents from HF radar radial velocity measurements using optimal interpolation

An optimal interpolation (OI) method to compute surface vector current fields from radial velocity measurements derived from high‐frequency (HF) radars is presented. The method assumes a smooth spatial covariance relationship between neighboring vector currents, in contrast to the more commonly used un‐weighted least‐squares fitting (UWLS) method, which assumes a constant vector velocity within a defined search radius. This OI method can directly compute any quantities linearly related to the radial velocities, such as vector currents and dynamic quantities (divergence and vorticity) as well as the uncertainties of those respective fields. The OI method is found to be more stable than the UWLS method and reduces spurious vector solutions near the baselines between HF radar installations. The OI method produces a covariance of the uncertainty of the estimated vector current fields. Three nondimensional uncertainty indices are introduced to characterize the uncertainty of the vector current at a point, representing an ellipse with directional characteristics. The vector current estimation using the OI method eliminates the need for multiple mapping steps and optimally fills intermittent coverage gaps. The effects of angular interpolation of radial velocities, a commonly used step in the preprocessing of radial velocity data prior to vector current computation in the UWLS method, are presented.

Population pharmacokinetics of darbepoetin alfa in peritoneal dialysis and non-dialysis patients with chronic kidney disease after single subcutaneous administration

To characterize the pharmacokinetics of darbepoetin alpha and covariate relationships in chronic kidney disease (CKD) patients after a single subcutaneous administration. A total of 989 serum concentration recordings from 64 patients were analyzed using NONMEM with a model including endogenous erythropoietin production. The basic and final models were evaluated for stability using bootstrapping. The selected basic model had one-compartment with a combination of the additive and constant coefficient of variation error models for residual variability. The significant covariate was weight for apparent clearance (CL/f) and apparent volume of central compartment (V(1)/f). The typical values of CL/f, V(1)/f, and absorption rate constant were 0.158 l/h, 13.7 l, and 0.0376/h, respectively. Evaluation by bootstrapping showed that the final model was stable. The present analysis indicated that weight is a significant covariate for CL/f and V(1)/f. However, dosage adjustment according to weight is not necessary for subcutaneous administration of darbepoetin alpha in CKD patients.

Climate change, land use change, and China’s food security in the twenty-first century: an integrated perspective

Food security in China, the world’s most populous country, has long been a concern because of the challenges of population growth, water shortages, and loss of cropland through urbanization, soil degradation, and climate change. Here, we present an integrated analysis of China’s food demand and supply under IPCC Special Report on Emissions Scenarios A1, A2, B1, and B2 in 2020, 2050, and 2080, based on official statistics and future development scenarios. Our analysis accounts for future socioeconomic, technological, and resource developments, as well the impact of climate change. We present a covariant relationship between changes in cereal productivity due to climate change and the cereal harvest area required to satisfy China’s food demand. We also estimated the effects of changing harvested areas on the productivity required to satisfy the food demand; of productivity changes due to climate change on the harvest area required to satisfy food demand; and of productivity and land use changes on the population at risk of undernutrition. China could be able to feed herself without disturbing the global food market in the twenty-first century, but whether the government will choose self-sufficiency or increased food imports may depend on the cost of change, which remains unknown.

Covariate adjustment for two‐sample treatment comparisons in randomized clinical trials: A principled yet flexible approach

There is considerable debate regarding whether and how covariate-adjusted analyses should be used in the comparison of treatments in randomized clinical trials. Substantial baseline covariate information is routinely collected in such trials, and one goal of adjustment is to exploit covariates associated with outcome to increase precision of estimation of the treatment effect. However, concerns are routinely raised over the potential for bias when the covariates used are selected post hoc and the potential for adjustment based on a model of the relationship between outcome, covariates, and treatment to invite a 'fishing expedition' for that leading to the most dramatic effect estimate. By appealing to the theory of semiparametrics, we are led naturally to a characterization of all treatment effect estimators and to principled, practically feasible methods for covariate adjustment that yield the desired gains in efficiency and that allow covariate relationships to be identified and exploited while circumventing the usual concerns. The methods and strategies for their implementation in practice are presented. Simulation studies and an application to data from an HIV clinical trial demonstrate the performance of the techniques relative to the existing methods.

Changes in neuropsychological functioning following treatment with risperidone, olanzapine, and conventional antipsychotic medications

To compare changes in neuropsychological functioning over time among adults with schizophrenia treated with atypical and conventional antipsychotics, controlling for phenomenological changes, medication dosage, concomitant use of anticholinergic medications, and practice effects. In a larger clinical trial, 108 patients diagnosed with schizophrenia or schizoaffective disorder were randomly assigned to medication groups (risperidone, olanzapine, or conventional medications), treated in an open-label design, and monitored prospectively for 12 months using standard neuropsychological and symptomatology instruments. Significant differential effects were evident on the ability to maintain and rapidly shift mental set within a psychomotor task, with patients in the conventional medication group consistently making more errors over time until the 12-month follow-up, when the olanzapine group made significantly more errors. Significant differential effects were also evident on delayed memory, with patients receiving olanzapine improving more steadily over time until the 12-month follow-up, when patients in the conventional group were able to recall significantly more. Positive and negative symptomatology was a significant, inversely related covariate on most of the cognitive measures examined. The atypical and conventional medications examined were not consistently differential enhancers of cognitive functioning on disparate cognitive functioning measures over time.

Obesity and Cardiac Risk After Kidney Transplantation: Experience at One Center and Comprehensive Literature Review

The cardiac implications of obesity in kidney transplant recipients are not well-described. We examined associations of body mass index (BMI) at transplant with posttransplant cardiac risk among 1102 renal allograft recipients at a single center in 1991 to 2004. Cumulative posttransplant incidences of congestive heart failure (CHF), atrial fibrillation (AF), myocardial infarction, and a composite of these cardiac diagnoses were estimated by the Kaplan-Meier method. Bivariate (hazards ratio) and covariate (adjusted hazards ratio) relationships of BMI increments with cardiac risk were modeled by Cox's regression. We also systematically reviewed the literature on BMI and cardiac events after transplant. In the local data, 5-year cumulative incidence of any cardiac diagnosis rose from 8.67% to 29.35% across the lowest to highest BMI quartiles (P=0.02), driven primarily by increases in CHF and AF. In contrast, the rate of myocardial infarction did not differ by BMI quartile (P=0.56). Each 5 U BMI increase predicted 25% higher risk of the cardiac composite (hazards ratio 1.25, 95% CI 1.07-1.47, P=0.005), a relationship that persisted with significance after covariate adjustment (adjusted hazards ratio 1.19, 95% CI 1.00-1.43, P=0.049). BMI independently predicted cardiac risk in subcohorts with pretransplant heart disease and with nondiabetic renal failure. Data from 26 original articles support BMI as a risk factor for posttransplant CHF and AF, whereas findings for coronary/ischemic outcomes are inconsistent and predominantly negative. High BMI at transplant predicts increased cardiac risk, especially of CHF and AF. Further research should examine whether obesity treatment modifies cardiac risk after kidney transplantation.

Bayesian analysis of within-field variability of corn yield using a spatial hierarchical model

Understanding relationships of soil and field topography to crop yield within a field is critical in site-specific management systems. Challenges for efficiently assessing these relationships include spatially correlated yield data and interrelated soil and topographic properties. The objective of this analysis was to apply a spatial Bayesian hierarchical model to examine the effects of soil, topographic and climate variables on corn yield. The model included a mean structure of spatial and temporal co-variates and an explicit random spatial effect. The spatial co-variates included elevation, slope and apparent soil electrical conductivity, temporal co-variates included mean maximum daily temperature, mean daily temperature range and cumulative precipitation in July and August. A conditional auto-regressive (CAR) model was used to model the spatial association in yield. Mapped corn yield data from 1997, 1999, 2001 and 2003 for a 36-ha Missouri claypan soil field were used in the analysis. The model building and computation were performed using a free Bayesian modeling software package, WinBUGS. The relationships of co-variates to corn yield generally agreed with the literature. The CAR model successfully captured the spatial association in yield. Model standard deviation decreased about 50% with spatial effect accounted for. Further, the approach was able to assess the effects of temporal climate co-variates on corn yield with a small number of site-years. The spatial Bayesian model appeared to be a useful tool to gain insights into yield spatial and temporal variability related to soil, topography and growing season weather conditions.

Bayesian Accelerated Failure Time Model With Multivariate Doubly Interval-Censored Data and Flexible Distributional Assumptions

In this article we consider the relationship of covariates to the time to caries of permanent first molars. This involves an analysis of multivariate doubly interval-censored data. To describe this relationship, we suggest an accelerated failure time model with random effects, taking into account that the observations are clustered. Indeed, up to four permanent molars per child enter into the analysis, implying up to four caries times for each child. Each distributional part of the model is specified in a flexible way as a penalized Gaussian mixture with an overspecified number of mixture components. A Bayesian approach with the Markov chain Monte Carlo methodology is used to estimate the model parameters, and a software package in the R language has been written that implements it.

Clinical Trial of Wellness Training

This randomized controlled trial examined benefits of adding active health promotion to basic primary care (BPC) services for SMI adults. It compared BPC with BPC plus wellness training (WT), a 12 months intervention promoting individual skills in self-management. Three hundred nine participants enrolled during short-term residential treatment completed baseline assessments and were assigned to treatment groups, before discharge. Outcomes of perceived health status (SF-36), global assessment of function, and ratings of self-efficacy were assessed at follow-up interviews at 6, 12, and 18 months. The intent-to-treat analysis employed multilevel regression to examine differences by group on outcomes across time, controlling for health related covariates. The WT group showed significantly better outcomes on the SF-36 physical functioning and general health scales. Findings affirm ability of SMI adults to benefit from active health promotion.

The influence of topography and fire in controlling landscape composition and structure in Sierra de Gredos (Central Spain)

Mediterranean landscapes are dynamic systems that undergo temporal changes in composition and structure in response to disturbances, such as fire. Neither landscape patterns nor driving factors that affect them are evenly distributed in space. Accordingly, disturbances and biophysical factors interact in space through time. The aim of this paper is to assess the relative influence of topography and fire on the landscape patterns of a large forested area located in Sierra de Gredos (Central Spain) through time. A series of Landsat MSS images from 1975 to 1990, and a digital elevation model (DEM) were used to map fires, assess topographical complexity and evaluate changes in landscape composition and structure. Functional regions across the entire landscape were identified using different classification criteria (i.e., percentage burned area and topographic properties) to model topographic and fire impacts at regional scales. A canonical variance partition method, with a time series split-plot design, quantified the relative influence and co-variation of topography and fire on land cover patterns through time. Main results indicated that analyzing portions of the landscape under similar environmental conditions and fire histories, the effects of different fire regimes on the spatio-temporal dynamics of main land covers can be highlighted. However, the impact of fire on landscape patterns was high variable among regions due to the different regeneration abilities of main land covers, the topographic constraints and the fire histories of each region. Hence, broad patterns of fire related variance and co-variation with topography emerged across the entire area due to the different conditions of each landscape portion in which this large Mediterranean landscape was divided.

Time-dependent covariates in the proportional subdistribution hazards model for competing risks

Separate Cox analyses of all cause-specific hazards are the standard technique of choice to study the effect of a covariate in competing risks, but a synopsis of these results in terms of cumulative event probabilities is challenging. This difficulty has led to the development of the proportional subdistribution hazards model. If the covariate is known at baseline, the model allows for a summarizing assessment in terms of the cumulative incidence function. black Mathematically, the model also allows for including random time-dependent covariates, but practical implementation has remained unclear due to a certain risk set peculiarity. We use the intimate relationship of discrete covariates and multistate models to naturally treat time-dependent covariates within the subdistribution hazards framework. The methodology then straightforwardly translates to real-valued time-dependent covariates. As with classical survival analysis, including time-dependent covariates does not result in a model for probability functions anymore. Nevertheless, the proposed methodology provides a useful synthesis of separate cause-specific hazards analyses. We illustrate this with hospital infection data, where time-dependent covariates and competing risks are essential to the subject research question.

Stochastic collocation and mixed finite elements for flow in porous media

The aim of this paper is to quantify uncertainty of flow in porous media through stochastic modeling and computation of statistical moments. The governing equations are based on Darcy’s law with stochastic permeability. Starting from a specified covariance relationship, the log permeability is decomposed using a truncated Karhunen–Loève expansion. Mixed finite element approximations are used in the spatial domain and collocation at the zeros of tensor product Hermite polynomials is used in the stochastic dimensions. Error analysis is performed and experimentally verified with numerical simulations. Computational results include incompressible and slightly compressible single and two-phase flow.

Population pharmacokinetics of sevoflurane in conjunction with the AnaConDa®: toward target‐controlled infusion of volatiles into the breathing system

The Anesthetic Conserving Device (AnaConDa) uncouples delivery of a volatile anesthetic (VA) from fresh gas flow (FGF) using a continuous infusion of liquid volatile into a modified heat-moisture exchanger capable of adsorbing VA during expiration and releasing adsorbed VA during inspiration. It combines the simplicity and responsiveness of high FGF with low agent expenditures. We performed in vitro characterization of the device before developing a population pharmacokinetic model for sevoflurane administration with the AnaConDa, and retrospectively testing its performance (internal validation). Eighteen females and 20 males, aged 31-87, BMI 20-38, were included. The end-tidal concentrations were varied and recorded together with the VA infusion rates into the device, ventilation and demographic data. The concentration-time course of sevoflurane was described using linear differential equations, and the most suitable structural model and typical parameter values were identified. The individual pharmacokinetic parameters were obtained and tested for covariate relationships. Prediction errors were calculated. In vitro studies assessed the contribution of the device to the pharmacokinetic model. In vivo, the sevoflurane concentration-time courses on the patient side of the AnaConDa were adequately described with a two-compartment model. The population median absolute prediction error was 27% (interquartile range 13-45%). The predictive performance of the two-compartment model was similar to that of models accepted for TCI administration of intravenous anesthetics, supporting open-loop administration of sevoflurane with the AnaConDa. Further studies will focus on prospective testing and external validation of the model implemented in a target-controlled infusion device.

A Continuous Latent Spatial Model for Crack Initiation in Bone Cement

SummaryHip replacements rovide a means of achieving a higher quality of life for individuals who have, through aging or injury, accumulated damage to their natural joints. This is a very common operation, with over a million people a year benefiting from the procedure. The replacements themselves fail mainly as a result of the mechanical loosening of the components of the artificial joint due to damage accumulation. This damage accumulation consists of the initiation and growth of cracks in the bone cement which is used to fixate the replacement in the human body. The data come from laboratory experiments that are designed to assess the effectiveness of the bone cement in resisting damage. We examine the properties of the bone cement, with the aim being to estimate the effect that both observable and unobservable spatially varying factors have on causing crack initiation. To do this, an explicit model for the damage process is constructed taking into account the tension and compression at different locations in the specimens. A gamma random field is used to model any latent spatial factors that may be influential in crack initiation. Bayesian inference is carried out for the parameters of this field and related covariates by using Markov chain Monte Carlo techniques.