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Results for “Model performance”

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PubMed2002

[D-Dimer determination combined with clinical probability for the diagnosis of leg venous thrombosis].

OBJECTIVE: To evaluate the results of combination of D-Dimer test and simple clinical model for the diagnosis of deep vein thrombosis (DVT). MATERIALS AND METHODS: Inclusion: clinical suspicion of DVT. Non inclusion criteria were Clinical model performed by the referring physician included probability varying from high to low. D-Dimer test was performed by five different rapid techniques. Standard of reference was Doppler ultrasonography (DU) performed by a senior radiologist. RESULTS: Eight hundred and fifty-four DU were performed on a 14 months time period, including 206 suspicion of pulmonary embolism, 109 postoperative time period, 120 non-included or excluded patients, 278 incomplete observations, 141 complete observations. DVT was present in 33 cases and absent in the other 108 cases (prevalence 23%). Sensitivity and negative predictive value of the five tests were between 82 and 97% and 90 et 97%. The most sensitive test had a specificity of 36% and a positive predictive value of 32%. Combination of clinical model and D-Dimer test did not improve the diagnostic accuracy. CONCLUSION: None of the test evaluated in the present study, even when combined with the clinical model results, did allow the exclusion of DVT.

Formycins↗

PubMed2003

Social capital, life expectancy and mortality: a cross-national examination.

This paper analyses the relationship between social capital and population health. The analysis is carried out within an econometric model of population health in 19 countries in the Organisation for Economic Co-operation and Development countries using panel data covering three different time periods. Social capital is measured by the proportion of people who say that that they generally trust other people and by membership in voluntary associations. The model performs well in explaining health outcomes. We find very little statistically significant evidence that the standard indicators of social capital have a positive effect on population health. By contrast, per capita income and the proportion of health expenditure financed by the government are both significantly and positively associated with better health outcomes. The paper casts doubt upon the widely accepted hypothesis that social capital has a positive effect on health and illustrates the importance of testing this kind of hypothesis in an extended model.

Cooperative Behavior↗

PubMed2005

Monitoring coyote population dynamics by genotyping faeces.

Reliable population estimates are necessary for effective conservation and management, and faecal genotyping has been used successfully to estimate the population size of several elusive mammalian species. Information such as changes in population size over time and survival rates, however, are often more useful for conservation biology than single population estimates. We evaluated the use of faecal genotyping as a tool for monitoring long-term population dynamics, using coyotes (Canis latrans) in the Alaska Range as a case study. We obtained 544 genotypes from 56 coyotes over 3 years (2000-2002). Tissue samples from all 15 radio-collared coyotes in our study area had > or = 1 matching faecal genotypes. We used flexible maximum-likelihood models to study coyote population dynamics, and we tested model performance against radio telemetry data. The staple prey of coyotes, snowshoe hares (Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold with a 1(1/2)-year time lag. Survival rates declined the year after hares crashed but recovered the following year. We conclude that long-term monitoring of elusive species using faecal genotyping is feasible and can provide data that are useful for wildlife conservation and management. We highlight some drawbacks of standard open-population models, such as low precision and the requirement of discrete sampling intervals, and we suggest that the development of open models designed for continuously collected data would enhance the utility of faecal genotyping as a monitoring tool.

Alaska↗

PubMed2006

Clinical prognostic rules for severe acute respiratory syndrome in low- and high-resource settings.

BACKGROUND: An accurate prognostic model for patients with severe acute respiratory syndrome (SARS) could provide a practical clinical decision aid. We developed and validated prognostic rules for both high- and low-resource settings based on data available at the time of admission. METHODS: We analyzed data on all 1755 and 291 patients with SARS in Hong Kong (derivation cohort) and Toronto (validation cohort), respectively, using a multivariable logistic scoring method with internal and external validation. Scores were assigned on the basis of patient history in a basic model, and a full model additionally incorporated radiological and laboratory results. The main outcome measure was death. RESULTS: Predictors for mortality in the basic model included older age, male sex, and the presence of comorbid conditions. Additional predictors in the full model included haziness or infiltrates on chest radiography, less than 95% oxygen saturation on room air, high lactate dehydrogenase level, and high neutrophil and low platelet counts. The basic model had an area under the receiver operating characteristic (ROC) curve of 0.860 in the derivation cohort, which was maintained on external validation with an area under the ROC curve of 0.882. The full model improved discrimination with areas under the ROC curve of 0.877 and 0.892 in the derivation and validation cohorts, respectively. CONCLUSION: The model performs well and could be useful in assessing prognosis for patients who are infected with re-emergent SARS.

Adult↗

PubMed1998

Increased immunogold labelling of neural cell adhesion molecule isoforms in synaptic active zones of the chick striatum 5-6 hours after one-trial passive avoidance training.

An area of the chick striatum, the lobus parolfactorius plays an important role in one-trial passive avoidance learning tasks. In the present study we report evidence that 5-6 h post-training, a significantly higher proportion of synaptic active zones in this area contain labelled epitopes of the neural cell adhesion molecule, with the greatest occurrence of labels at the edges of active zone profiles (in both control and trained groups). This suggests that there is a period after training when expression of the neural cell adhesion molecule in synaptic membranes almost doubles, and that events at active zone edges may play a specific role in mechanisms of synaptic adhesion. Cellular mechanisms of long-term memory formation are believed to include alterations in neural circuitry at the synaptic level. The involvement of the neural cell adhesion molecule (NCAM) in functional synaptic modifications has been demonstrated using a number of physiological models. Performance of rats in the Morris water maze, a spatial learning paradigm which requires the hippocampus, is impaired by either intraventricular injection of NCAM antibodies, or injection into the hippocampus of an enzyme which increases homophilic adhesion of the molecule, due to the removal of polysialic acid residuals from extracellular NCAM domains. In addition, intraventricular injections of anti-NCAM antibodies 6-8 h post-training were shown to impair memory for a one-trial passive avoidance task in the rat. An avoidance training model in the one-day-old chick indicates a similar time window, 5-6 h post-training during which memory for the task can be impaired by intraventricular injection of NCAM antibodies. In the hyperstriatum ventrale, a chick forebrain area involved in the passive avoidance task. subtle changes in the distribution pattern, but not density of NCAM molecules in synaptic membranes were revealed 5-6 h post-training. However, on the basis of studies of synaptic morphometry, a region of striatum, the lobus parolfactorius (LPO), appears to play a more important role in longer term memory storage for the task.

Animals↗

PubMed2001

A tournament of linkage tests in complex inheritance.

The performance of some weakly parametric linkage tests in common use was compared on 200 replicates of oligogenic inheritance from Genetic Analysis Workshop 10. Each random sample for the quantitative trait was dichotomized at different thresholds and also selected through 2 affected sibs, generating 8 combinations of sample and variable. The variance component program SOLAR performed best with a continuous trait, even in selected samples, when the population mean was used. The sib-pair program SIBPAL2 was best in most other cases when the phenotype product, population mean, and empirical estimates of pair correlations were used. The BETA program that introduced phenotype products was slightly more powerful than maximum likelihood scores under the null hypothesis and approached but did not exceed SIBPAL2 under its optimal conditions. Type I errors generally exceeded expectations from a chi(2) test, but were conservative with respect to bounds on lods. All methods can be improved by use of the population mean, empirical correlations, logistic representation for affection status, and correct lods for samples that favour the null hypothesis. It remains uncertain whether all information can be extracted by weakly parametric methods and whether correction for ascertainment bias demands a strongly parametric model. Performance on a standard set of simulated data is indispensable for recognising optimal methods.

Algorithms↗

PubMed2003

Factors associated with erectile dysfunction in male kidney transplant recipients.

A transversal study was carried out in order to evaluate the prevalence of erectile dysfunction (ED) in adult kidney transplant patients of our region (N=243), and to investigate the sociodemographic, analytic, and clinical factors associated with it. To evaluate ED, the Spanish five items version of the International Index of Erectile Function (IIEF-5) was employed. Sociodemographic, analytic, and clinical data, including 12 cardiovascular risk factors, were also collected. A total of 199 patients (82%) were included. The median age was 52 y (43-62 y); 106 patients (54.9%) presented with ED. Variables associated with ED were: higher age; longer time on dialysis prior to transplantation; higher comorbidity; presence of diabetes mellitus; had undergone prostatic surgery or peripheric artheriopathy; lower diastolic pressure; and some anti hypertensive drugs. Logistic Regression Model performed step by step showed (R(2)=0.52) that factors independently associated with ED were: age, time on dialysis previous to transplant, and peripheric artheriopathy.

Adult↗

PubMed2003

Inhibitory effects in the side reactions occurring during the enzymic synthesis of amoxicillin: p-hydroxyphenylglycine methyl ester and amoxicillin hydrolysis.

Penicillin G acylase immobilized on glyoxyl-agarose is used to catalyse the reaction between p -hydroxyphenylglycine methyl ester (POHPGME) and 6-aminopenicillanic acid (6-APA). Inhibitory effects affecting the side reactions that occur during the synthesis of amoxicillin have been reported and need to be considered when proposing a kinetic model for the enzymic synthesis. In this work, we present a semi-empirical kinetic model that successively includes different inhibitory effects in the rate equations. The model performance was always compared with experimental data on amoxicillin synthesis. Enzyme load and stirring rate were chosen to prevent diffusional effects. Our results indicate that POHPGME and amoxicillin were competitive inhibitors of the hydrolysis of amoxicillin and POHPGME, respectively. 6-APA was a competitive inhibitor of the hydrolysis of amoxicillin. POHPG was a competitive inhibitor and methanol a non-competitive inhibitor of the hydrolysis of both ester and antibiotic, but the action of methanol was only noticeable at very high concentrations. Adding inhibitory effects to the kinetic model led to a significant increase in the accuracy of the simulations of the overall process of synthesis.

Amoxicillin↗

PubMed2003

Overview and quantification of the factors affecting the upstream and downstream movements of Gammarus pulex (Amphipoda).

Human activities have severely deteriorated the Flemish river systems, and many functions such as drinking water supply, fishing, ... are threatened. Because their restoration entails drastic social (e.g. change in habits with regard to water use and discharge, urban planning) and economical (e.g. investment in nature restoration, wastewater treatment system installation) consequences, the decisions should be taken with enough forethought. Ecosystem models can act as interesting tools to support decision-making in river restoration management. In particular models that can predict the habitat requirements of organisms are of considerable importance to ensure that the planned actions have the desired effects on the aquatic ecosystems. In preliminary studies, Artificial Neural Network (ANN) models were tested and optimized to obtain the best model configuration for the prediction of the habitat suitability for Gammarus pulex based on the abiotic characteristics of their aquatic environment in the Zwalm river basin (Flanders, Belgium). Although, these ANN models are in general quite robust with a rather high predictive reliability, the model performance has to be increased with regard to simulations for river restoration management. In particular, spatial-temporal expert-rules have to be included. Migration kinetics (downstream drift and upstream migration) of the organism and migration barriers along the river (weirs, impounded river sections, ...) can deliver important additional information on the effectiveness of the restoration plans, and also on the timing of the expected effects. This paper presents an overview and quantification of the factors affecting the upstream and downstream movements of Gammarus pulex. During further research, ANN models will be used to predict the habitat suitability for Gammarus pulex after several restoration options. The migration models, implemented in a Geographical Information System (GIS), are applied to calculate the migration time to the restored parts of the river. In this way, decision makers have an idea whether and when a selected restoration option has the desired effect.

Amphipoda↗

PubMed2006

Model estimation and measurement of ammonia emission from naturally ventilated dairy cattle buildings with slatted floor designs.

Laboratory experiments were carried out in a wind tunnel with a model of a slurry pit to investigate the characteristics of ammonia emission from dairy cattle buildings with slatted floor designs. Ammonia emission at different temperatures and air velocities over the floor surface above the slurry pit was measured with uniform feces spreading and urine sprinkling on the surface daily. The data were used to improve a model for estimation of ammonia emission from dairy cattle buildings. Estimates from the updated emission model were compared with measured data from five naturally ventilated dairy cattle buildings. The overall measured ammonia emission rates were in the range of 11-88 g per cow per day at air temperatures of 2.3-22.4 degrees C. Ammonia emission rates estimated by the model were in the range of 19-107 g per cow per day for the surveyed buildings. The average ammonia emission estimated by the model was 11% higher than the mean measured value. The results show that predicted emission patterns generally agree with the measured one, but the prediction has less variation. The model performance may be improved if the influence of animal activity and management strategy on ammonia emission could be estimated and more reliable data of air velocities of the buildings could be obtained.

Air Pollutants↗

PubMed2004

The benefits of stereoscopic vision in robotic-assisted performance on bench models.

BACKGROUND: Previous studies have failed to establish clear advantages for the use of stereoscopic visualization systems in minimal-access surgery. The aim of this study was to objectively assess whether stereoscopic visualization improves performance on bench models using the da Vinci robotic system. METHODS: Eleven surgeons carried out a series of four tasks. Positional data streamed from the da Vinci system was analyzed by means of a previously validated custom-designed software-package. An independent blinded observer scored errors. Statistical analysis included the Wilcoxon signed rank test. A p < 0.05 was deemed significant. RESULTS: We found significant improvements in all tasks and for all parameters (p < 0.05). In addition, a significantly lower number of errors was scored using the stereoscopic mode as compared to the standard two-dimensional image (p < 0.001). CONCLUSION: Robotic-assisted performance on bench models is more efficient and accurate using stereoscopic visualization.

Data Display↗

PubMed2000

Consideration of endogenous backgrounds in pharmacokinetic analyses: a simulation study.

OBJECTIVE: The pharmacokinetic analysis of biologic compounds is frequently disturbed by the presence of endogenous levels, which cannot be discerned from exogenous levels. The frequently used method of subtracting baseline levels from subsequent measurements was compared to a fully adjusted regression model in a simulation study. METHODS: Simulations (5,000 each) were carried out for a standard one-compartment model with rich (n = 10) and poor (n = 6) postdose sampling, using unweighted as well as two-weighted types of non-linear regression. RESULTS: Whereas the fully adjusted model performed properly across various scenarios, the subtraction method showed a noteworthy bias (up to 14%) for area under the curve (AUC) and elimination half-life with weighted non-linear regression. For estimation of the Cmax parameter using any weighting scheme, and of any parameter using unweighted non-linear regression, the two methods performed equally well. As expected, poor in contrast to rich sampling resulted in larger coefficients of variation, but also in increasing failures (4.4%) of the regression algorithm (failure to converge, negative Cmax or half-life) for the subtraction method when it was combined with the weighting scheme giving highest weight to small concentrations. CONCLUSION: The risk of biased results may result from the subtraction method, which may also affect the analysis of dose linearity, bioequivalence and population kinetic studies with biologic compounds. When background endogenous levels are not negligible, a fully adjusted model is recommended.

Area Under Curve↗

PubMed1978

Model for human controller performance in vibration environments.

A model has been developed to predict biomechanical response and human controller performance as a function of vibration environment and tracking-task parameters. The model consists of three major elements: 1) a biodynamic model to predict limb and body motion resulting from platform vibration, 2) a pilot/vehicle model to predict tracking performance, and 3) an interface model to relate changes in certain pilot-related model parameters to biodynamic response. Linearity of biodynamic response mechanisms is demonstrated, and the model is shown to predict accurately the effects of tracking performance of vibration amplitude and spectrum, control gain, R.M.S. tracking input, and direction of vibration input.

Aviation↗

PubMed2006

Modeling and simulation of deformation of hydrogels responding to electric stimulus.

A model for simulation of pH-sensitive hydrogels is refined in this paper to extend its application to electric-sensitive hydrogels, termed the refined multi-effect-coupling electric-stimulus (rMECe) model. By reformulation of the fixed-charge density and consideration of finite deformation, the rMECe model is able to predict the responsive deformations of the hydrogels when they are immersed in a bath solution subject to externally applied electric field. The rMECe model consists of nonlinear partial differential governing equations with chemo-electro-mechanical coupling effects and the fixed-charge density with electric-field effect. By comparison between simulation and experiment extracted from literature, the model is verified to be accurate and stable. The rMECe model performs quantitatively for deformation analysis of the electric-sensitive hydrogels. The influences of several physical parameters, including the externally applied electric voltage, initial fixed-charge density, hydrogel strip thickness, ionic strength and valence of surrounding solution, are discussed in detail on the displacement and average curvature of the hydrogels.

Computer Simulation↗

PubMedDate not supplied

kappa Nearest neighbors QSAR modeling as a variational problem: theory and applications.

Variable selection k Nearest Neighbor (kNN) QSAR is a popular nonlinear methodology for building correlation models between chemical descriptors of compounds and biological activities. The models are built by finding a subspace of the original descriptor space where activity of each compound in the data set is most accurately predicted as the averaged activity of its k nearest neighbors in this subspace. We have formulated the problem of searching for the optimized kNN QSAR models with the highest predictive power as a variational problem. We have investigated the relative contribution of several model parameters such as the selection of variables, the number (k) of nearest neighbors, and the shape of the weighting function used to evaluate the contributions of k nearest neighbor compound activities to the predicted activity of each compound. We have derived the expression for the weighting function which maximizes the model performance. This optimization methodology was applied to several experimental data sets divided into the training and test sets. We report a significant improvement of both the leave-one-out cross-validated R(2) (q(2)) for the training sets and predictive R(2) of the test sets in all cases. Depending on the data set, the average improvements in the prediction accuracy (prediction R(2)) for the test sets ranged between 1.1% and 94% and for the training sets (q(2)) between 3.5% and 118%. We also describe a modified computational procedure for model building based on the use of relational databases to store descriptors and calculate compounds' similarities, which simplifies calculations and increases their efficiency.

Models, Molecular↗

PubMed2006

Is pre-operative anaemia a risk marker for in-hospital mortality and morbidity after valve replacement?

AIMS: To assess the level of pre-operative haemoglobin (HB) as a risk marker for morbidity and mortality in the early post-operative period of patients who underwent elective valve replacement. METHODS AND RESULTS: Between January 1998 and March 2004, clinical and outcomes data were collected for the 201 patients who had elective valve replacement. For each gender, the criterion to choose the best cut-off point was that which achieved the maximum likelihood after several General Additive Model models performed in a Bootstrap procedure. The best cut-off point obtained for pre-operative HB was 12 g/dL. Overall peri-operative mortality (deaths occurring during hospital period or within 30 days) was 9.5%. After adjusting well-known independent pre-operative risk factors for operative mortality, pre-operative HB <12 g/dL was identified as an independent predictor for in-hospital mortality (OR, 3.23; 95% CI, 1.09-9.55; P = 0.03). Also adjusting for EuroScore, pre-operative HB remained significant (OR, 3.64; 95% CI, 1.32-10.06; P = 0.01). The same model was applied to post-operative morbidity, and pre-operative HB <12 g/dL was identified as an independent predictor with and without EuroScore (OR, 4.67; 95% CI, 2.03-10.71; P < 0.001), (OR, 5.18; 95% CI, 2.18-12.3; P < 0.001), respectively. CONCLUSION: In patients undergoing elective valve replacement pre-operative HB <12 g/dL is a risk marker of in-hospital mortality and serious adverse outcomes.

Aged↗

PubMed2001

Best harmony, unified RPCL and automated model selection for unsupervised and supervised learning on Gaussian mixtures, three-layer nets and ME-RBF-SVM models.

After introducing the fundamentals of BYY system and harmony learning, which has been developed in past several years as a unified statistical framework for parameter learning, regularization and model selection, we systematically discuss this BYY harmony learning on systems with discrete inner-representations. First, we shown that one special case leads to unsupervised learning on Gaussian mixture. We show how harmony learning not only leads us to the EM algorithm for maximum likelihood (ML) learning and the corresponding extended KMEAN algorithms for Mahalanobis clustering with criteria for selecting the number of Gaussians or clusters, but also provides us two new regularization techniques and a unified scheme that includes the previous rival penalized competitive learning (RPCL) as well as its various variants and extensions that performs model selection automatically during parameter learning. Moreover, as a by-product, we also get a new approach for determining a set of 'supporting vectors' for Parzen window density estimation. Second, we shown that other special cases lead to three typical supervised learning models with several new results. On three layer net, we get (i) a new regularized ML learning, (ii) a new criterion for selecting the number of hidden units, and (iii) a family of EM-like algorithms that combines harmony learning with new techniques of regularization. On the original and alternative models of mixture-of-expert (ME) as well as radial basis function (RBF) nets, we get not only a new type of criteria for selecting the number of experts or basis functions but also a new type of the EM-like algorithms that combines regularization techniques and RPCL learning for parameter learning with either least complexity nature on the original ME model or automated model selection on the alternative ME model and RBF nets. Moreover, all the results for the alternative ME model are also applied to other two popular nonparametric statistical approaches, namely kernel regression and supporting vector machine. Particularly, not only we get an easily implemented approach for determining the smoothing parameter in kernel regression, but also we get an alternative approach for deciding the set of supporting vectors in supporting vector machine.

Algorithms↗

PubMed2006

A risk score for mortality after allogeneic hematopoietic cell transplantation.

BACKGROUND: Despite recent advances, mortality rates after allogeneic hematopoietic cell transplantation remain high and cannot be accurately predicted. OBJECTIVE: To develop a reliable and valid predictor of all-cause mortality during the first 2 years after allogeneic hematopoietic cell transplantation. DESIGN: Retrospective cohort. SETTING: Tertiary hematopoietic cell transplantation center. PATIENTS: Patients (n = 2802) who received a first hematopoietic cell transplant between 1990 and 2002 were assigned to a development group or a validation group. MEASUREMENTS: Potential predictor variables were assessed with univariate and multivariable Cox proportional hazards methods to generate a prediction model. The c-statistic was calculated for 5 validation cohorts to assess model performance across early and late time periods and among patients with different diagnoses. RESULTS: The authors constructed a 50-point Pretransplantation Assessment of Mortality (PAM) score that incorporated 8 pretransplantation clinical variables: patient age, donor type, disease risk, conditioning regimen, FEV1, carbon monoxide diffusion capacity, serum creatinine level, and serum alanine aminotransferase concentration. The risk for death within 2 years for patients with PAM scores in the highest category was significantly higher than for those with scores in the lowest category. C-statistic values ranged from 0.69 to 0.76 for all validation cohorts. LIMITATIONS: The predictor model was not validated in an external cohort and is only useful for predicting the risk for death within the first 2 years after hematopoietic cell transplantation. CONCLUSIONS: Integrating pretransplantation clinical variables into a single score reliably predicts survival within 2 years after allogeneic hematopoietic cell transplantation. Accurate estimates of the risk for death may be useful in clinical trials and in epidemiologic studies. Such information can also be used to help physicians counsel patients regarding the expected outcomes of this potentially curative procedure.

Adult↗