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At least 127 records · Page 7Linked to original sources

PubMed2002

Determination of antibiotic effect in an in vitro pharmacodynamic model: comparison with an established animal model of infection.

Animal infection models have historically been used to study pharmacodynamic relationships. Similar results could theoretically be produced by using an in vitro pharmacodynamic model as an alternative to animal models. We compared the antibiotic effects of ticarcillin administered in various doses and dosing regimens against Pseudomonas aeruginosa ATCC 27853 under conditions analogous to those previously employed in a neutropenic-mouse thigh infection model (B. Vogelman et al., J. Infect. Dis. 158:831-847, 1988). Ticarcillin dosages of either 96, 192, or 384 mg/day were administered at 1-, 2-, 3-, 4-, 8-, 12-, or 24-h intervals into a two-compartment model in order to duplicate the concentration-time profiles of the animal model. Colony counts were enumerated at 0 and 24 h. Linear regression and sigmoidal maximum-effect (Emax) model fitting were used to assess the relationship between the percentage of time that the concentration remained above the MIC (%T>MIC) or above four times the MIC (%T>4xMIC) and the change in the log(10) CFU per milliliter (Deltalog(10) CFU/ml) in the central and peripheral compartments. Statistical analysis of the Deltalog(10) CFU/ml values was performed for matched regimens of the in vitro and animal models based on the %T>MICs. The slopes of the regression equations of %T>MICs relative to Deltalog(10) CFU/ml values were similar for the in vitro and animal models, but the y intercept was greater with the in vitro model. The Deltalog(10) CFU/ml values of the 0- to 24-h colony counts at equivalent %T>MICs in the two models were not statistically different (P = 0.087). Overall, the peripheral compartment of the in vitro model was a better predictor of effect than the central compartment. This study, which compares pharmacodynamic principles between an in vitro and an animal model, demonstrated similar relationships between %T>MICs and effects.

Animals↗

PubMed2000

A model for facilitation of critical reflective practice: Part I--Introductory discussion and explanation of the phases followed to construct the model.

The purpose of this inquiry was to construct a model for facilitation of critical reflective practice, based on thorough analysis of the main concepts (critical thinking and reflection), related viewpoints, models and theories; and the data gathered and analyzed during, the naturalistic inquiry. The constructed model evolved from empirical observations, intuitive insights of the inquirer and from deductions combining ideas from several fields of inquiry. The model for facilitation of critical reflective practice postualates that practitioners have the inherent potential to change from auto-pilot practice to critical reflective practice. The purpose of the model is the facilitation of heightened awareness of the self, to enable health care professionals to consciously meet community needs and expectations. The desired outcome is transformative intellectuals who will strive to empower others to become critical reflective learners and practitioners themselves. The process followed during the construction of the model and the constructed model will be discussed in three (3) articles, namely: A model for facilitation of critical reflective practice: Part I--Introductory discussion and explanation of the phases followed to construct the model. A model for facilitation of critical reflective practice: Part II--Conceptual analysis within the context of constructing the model. A model for facilitation of critical reflective practice: Part III--Description of the model.

Attitude of Health Personnel↗

PubMed2001

Population pharmacokinetic modeling and model validation of a spicamycin derivative, KRN5500, in phase 1 study.

PURPOSE: KRN5500, a novel spicamycin derivative, shows the greatest activity against a human tumor xenograft model and the highest therapeutic index among spicamycin derivatives. KRN5500 is currently under clinical development in Japan and the United States. The objective of this study was to develop a population pharmacokinetic model that describes the KRN5500 plasma concentration versus time data. METHODS: Data were collected from 18 patients entered in a phase 1 study. These patients received KRN5500 3-21 mg/m2 as a 2-h infusion. A total of 219 concentration measurements were available. The data were analyzed using the nonlinear mixed effect model (NONMEM) program. In addition, the basic and final population pharmacokinetic models were evaluated using bootstrapping resampling. RESULTS: The basic model selected was a two-compartment model with a combination of additive and constant coefficient of variation error models. The basic model fitted well not only the original data, but also 100 bootstrap replicates generated from the original data set. With regard to the effect of covariates selected by generalized additive modeling analysis, gender (SEX) and performance status were found to be possible determinants of the volume of central compartment by NONMEM analysis. The final regression model for V1 was V1 = theta V1 (1--SEX x theta SEX), where V1 is the typical population value of the volume of central compartment, and SEX = 0 if the patient is male, otherwise SEX = 1. The final model was fitted to the 200 bootstrapped samples. The mean parameter estimates were within 15% of those obtained with the original data set. CONCLUSIONS: The KRN5500 plasma concentration versus time data obtained from the phase 1 study were well described by the population pharmacokinetic model. Further evaluation by bootstrapping showed that the population pharmacokinetic model was stable.

Adult↗

PubMed2006

Comparison of the performance of tracer kinetic model-driven registration for dynamic contrast enhanced MRI using different models of contrast enhancement.

RATIONALE AND OBJECTIVES: The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. MATERIALS AND METHODS: Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. RESULTS: Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. CONCLUSION: When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents.

Abdominal Neoplasms↗

PubMed2004

HIV hollow fiber SCID model for antiviral therapy comparison with SCID/hu model.

Severe combined immunodeficient (SCID) mice have been evaluated for applicability as hosts for a human immunodeficiency virus (HIV) animal model, compatible with the pathogenesis of HIV disease and/or for testing compounds for antiviral efficacy. McCune et al. [Science 241 (1988) 1632] described the SCID/hu model and Namikawa et al. [J. Exp. Med. 172 (1990) 1055] and Rabin et al. [Antimicrob. Agents Chemother. 40 (1996) 755] described the SCID/hu (Thy/Liv) model which was developed for the evaluation of HIV pathogenic mechanisms and for the prioritization of antiviral compounds that were efficacious in vitro. Hollingshead et al. [Antiviral Res. 28 (1995) 265] and Xu et al. [Bioorg. Med Chem. Lett. 9 (1999) 133] described the HIV hollow fiber SCID mouse model. This model was developed to be a low cost, high throughput, time efficient, simple in vivo screening system for preliminary anti-HIV efficacy evaluation for the prioritization of antiviral compounds that demonstrated in vitro efficacy. The hollow fiber model is used as a pharmacologic tool to help separate active and inactive agents and direct the best lead compounds into additional animal model testing (e.g. SCID/hu). Compounds that are known to have an antiviral effect in man (e.g. 3'-azo-3'-deoxythymidine (AZT), dideoxyinosine (ddI) and dideoxycytidine (ddC)) were evaluated in both models. The endpoints (e.g. PCR, flow cytometry, MTT, p24, RT) evaluated in both models indicate that HIV-1 virus replicates in both models and infection is suppressed in the SCID/hu and hollow fiber SCID mouse models when treated with approved clinical antiviral agents. While both models are useful for the evaluation of antiviral therapies, there are distinct advantages (e.g. cost, time, material, equipment, expediency) with the hollow fiber assay over the SCID/hu model (Thy/Liv) for antiviral drug evaluations particularly in terms of cost effectiveness.

Animals↗

PubMed2005

An animal model of chronic inflammatory pain: pharmacological and temporal differentiation from acute models.

Clinically, inflammatory pain is far more persistent than that typically modelled pre-clinically, with the majority of animal models focussing on short-term effects of the inflammatory pain response. The large attrition rate of compounds in the clinic which show pre-clinical efficacy suggests the need for novel models of, or approaches to, chronic inflammatory pain if novel mechanisms are to make it to the market. A model in which a more chronic inflammatory hypersensitivity phenotype is profiled may allow for a more clinically predictive tool. The aims of these studies were to characterise and validate a chronic model of inflammatory pain. We have shown that injection of a large volume of adjuvant to the intra-articular space of the rat knee results in a prolonged inflammatory pain response, compared to the response in an acute adjuvant model. Additionally, this model also results in a hypersensitive state in the presence and absence of inflammation. A range of clinically effective analgesics demonstrate activity in this chronic model, including morphine (3mg/kg, t.i.d.), dexamethasone (1mg/kg, b.i.d.), ibuprofen (30mg/kg, t.i.d.), etoricoxib (5mg/kg, b.i.d.) and rofecoxib (0.3-10mg/kg, b.i.d.). A further aim was to exemplify the utility of this chronic model over the more acute intra-plantar adjuvant model using two novel therapeutic approaches; NR2B selective NMDA receptor antagonism and iNOS inhibition. Our data shows that different effects were observed with these therapies when comparing the acute model with the model of chronic inflammatory joint pain. These data suggest that the chronic model may be more relevant to identifying mechanisms for the treatment of chronic inflammatory pain states in the clinic.

Animals↗

PubMed2003

The use of model selection in the model-free analysis of protein dynamics.

Model-free analysis of NMR relaxation data, which is widely used for the study of protein dynamics, consists of the separation of the global rotational diffusion from internal motions relative to the diffusion frame and the description of these internal motions by amplitude and timescale. Five model-free models exist, each of which describes a different type of motion. Model-free analysis requires the selection of the model which best describes the dynamics of the NH bond. It will be demonstrated that the model selection technique currently used has two significant flaws, under-fitting, and not selecting a model when one ought to be selected. Under-fitting breaks the principle of parsimony causing bias in the final model-free results, visible as an overestimation of S2 and an underestimation of taue and Rex. As a consequence the protein falsely appears to be more rigid than it actually is. Model selection has been extensively developed in other fields. The techniques known as Akaike's Information Criteria (AIC), small sample size corrected AIC (AICc), Bayesian Information Criteria (BIC), bootstrap methods, and cross-validation will be compared to the currently used technique. To analyse the variety of techniques, synthetic noisy data covering all model-free motions was created. The data consists of two types of three-dimensional grid, the Rex grids covering single motions with chemical exchange [S2,taue,Rex], and the Double Motion grids covering two internal motions [S f 2,S s 2,tau s ]. The conclusion of the comparison is that for accurate model-free results, AIC model selection is essential. As the method neither under, nor over-fits, AIC is the best tool for applying Occam's razor and has the additional benefits of simplifying and speeding up model-free analysis.

Amines↗

PubMed1986

Simultaneous modeling of pharmacokinetics and pharmacodynamics with nonparametric kinetic and dynamic models.

Three models, linked in series, can be used to analyze combined pharmacokinetic (PK) and pharmacodynamic (PD) data arising from non--steady-state experiments. A PK model relates dose to plasma drug concentration (Cp); a link model relates Cp to drug concentration at the effect site (Ce); and a PD model relates Ce to drug effect (E). All three submodels can be stated parametrically. Recently the use of a nonparametric PD submodel has been proposed (CLIN PHARMACOL THER 1984;35:733-41). In this article we use an extended nonparametric approach that represents both the PK and PD models nonparametrically, but retains a parametric link model. Cp data from several PK models and E data from several PD models were simulated. After the addition of noise to both the Cp and E data, they were analyzed by both the parametric and extended nonparametric methods. The methods were compared by how well they estimated the PD model. To assess robustness, the effect of misspecification of the PK submodel on the goodness of estimation of both methods was also compared. In the absence of model misspecification, the parametric method usually estimates the PD model better than the nonparametric method. However, this difference in the performances diminishes and even reverses when the PK model is misspecified. Because one can rarely be certain that model misspecification is absent, the nonparametric approach may offer a distinct advantage for routine analysis of PK/PD data.

Kinetics↗

PubMed2001

Body fat measurement among Singaporean Chinese, Malays and Indians: a comparative study using a four-compartment model and different two-compartment models.

This cross-sectional study compared body fat percentage (BF%) obtained from a four-compartment (4C) model with BF% from hydrometry (using 2H2O), dual-energy X-ray absorptiometry (DXA) and densitometry among the three main ethnic groups (Chinese, Malays and Indians) in Singapore, and determined the suitability of two-compartment (2C) models as surrogate methods for assessing BF% among different ethnic groups. A total of 291 subjects (108 Chinese, seventy-six Malays, 107 Indians) were selected to ensure an adequate representation of age range (18-75 years) and BMI range (16-40 kg/m2) of the general adult population, with almost equal numbers from each gender group. Body weight was measured, together with body height, total body water by 2H2O dilution, densitometry with Bodpod and bone mineral content with Hologic QDR-4500. BF% measurements with a 4C model for the subgroups were: Chinese females 33.5 (sd 7.5), Chinese males 24.4 (sd 6.1), Malay females 37.8 (sd 6.3), Malay males 26.0 (sd 7.6), Indian females 38.2 (sd 7.0), Indian males 28.1 (sd 5.5). Differences between BF% measured by the 4C and 2C models (hydrometry, DXA and densitometry) were found, with underestimation of BF% in all the ethnic-gender groups by DXA of 2.1-4.2 BF% and by densitometry of 0.5-3.2 BF%). On a group level, the differences in BF% between the 4C model and 2H2O were the lowest (0.0-1.4 BF% in the different groups), while differences between the 4C model and DXA were the highest. Differences between the 4C model and 2H2O and between the 4C model and DXA were positively correlated with the 4C model, water fraction (f(water)) of fat-free mass (FFM) and the mineral fraction (f(mineral)) of FFM, and negatively correlated with density of the FFM (D(FFM)), while the difference between 4C model and densitometry correlated with these variables negatively and positively respectively (i.e. the correlations were opposite). The largest contributors to the observed differences were f(water) and D(FFM). When validated against the reference 4C model, 2C models were found to be unsuitable for accurate measurements of BF% at the individual level, owing to the high errors and violation of assumptions of constant hydration of FFM and D(FFM) among the ethnic groups. On a group level, the best 2C model for measuring BF% among Singaporeans was found to be 2H2O.

Absorptiometry, Photon↗

PubMed2001

Biophysical modelling of proton radiation effects based on amorphous track models.

PURPOSE: To define a photon-equivalent dose in charged particle therapy one needs to know the RBE (Relative Biological Effectiveness) in the target region as well as in the surrounding tissue. RBE estimates are difficult since both the physical input parameters, i.e. LET distributions, and, even more so, the biological input parameters, i.e. cell nucleus size and local response, are not known in general. Track structure theory provides a basis for predicting dose-response curves for particle irradiation. There are (at least) two somewhat different algorithms: the Amorphous Track Partition model (ATP) and the Amorphous Track Local effect model (ATL). Both have been reported to give good agreement with observed radiobiological data. We were interested in a general comparison and in the predictive power of these models for protons. MATERIALS AND METHODS: We compared the principles of the two track structure approaches. The general dependencies of the model predictions on the input parameters are investigated. The model predictions for protons with respect to cell survival of V79 cells are compared with measurements. RESULTS: Although based on similar assumptions, the application of track structure theory in terms of the computational procedure is different for the two models. The ATP model provides a set of equations to predict inter- and intratrack radiation response whereas the ATL model is based on Monte Carlo simulations. One conceptual difference is the use of average doses in subtargets in the ATP model compared with the use of local doses in infinitesimal compartments in the ATL model. The ATP concept introduces an empirical scaling of the cross-section from subcellular to cellular response. The ATL concept inherently requires a critical adjustment of parameters handling the high local dose region near the track centre. The models predict proton survival curves reasonably well but neither shows good agreement with experimental data over the entire range of proton energy and absorbed dose considered. CONCLUSION: Designed for heavy ion applications, the models show weaknesses in the prediction of proton radiation effects. Amorphous track models are based on assumptions about the properties of the biological target and the radiation field that can be questioned. In particular, the assumption of subtargets and the multitarget/single-hit response function on one hand and the parameterization of radial dose and high dose cellular response on the other hand leave question marks.

Animals↗

PubMed2003

Modeling open-set spoken word recognition in postlingually deafened adults after cochlear implantation: some preliminary results with the neighborhood activation model.

HYPOTHESES: Do cochlear implants provide enough information to allow adult cochlear implant users to understand words in ways that are similar to listeners with acoustic hearing? Can we use a computational model to gain insight into the underlying mechanisms used by cochlear implant users to recognize spoken words? BACKGROUND: The Neighborhood Activation Model has been shown to be a reasonable model of word recognition for listeners with normal hearing. The Neighborhood Activation Model assumes that words are recognized in relation to other similar-sounding words in a listener's lexicon. The probability of correctly identifying a word is based on the phoneme perception probabilities from a listener's closed-set consonant and vowel confusion matrices modified by the relative frequency of occurrence of the target word compared with similar-sounding words (neighbors). Common words with few similar-sounding neighbors are more likely to be selected as responses than less common words with many similar-sounding neighbors. Recent studies have shown that several of the assumptions of the Neighborhood Activation Model also hold true for cochlear implant users. METHODS: Closed-set consonant and vowel confusion matrices were obtained from 26 postlingually deafened adults who use cochlear implants. Confusion matrices were used to represent input errors to the Neighborhood Activation Model. Responses to the different stimuli were then generated by the Neighborhood Activation Model after incorporating the frequency of occurrence counts of the stimuli and their neighbors. Model outputs were compared with obtained performance measures on the Consonant-Vowel Nucleus-Consonant word test. Information transmission analysis was used to assess whether the Neighborhood Activation Model was able to successfully generate and predict word and individual phoneme recognition by cochlear implant users. RESULTS: The Neighborhood Activation Model predicted Consonant-Vowel Nucleus-Consonant test words at levels similar to those correctly identified by the cochlear implant users. The Neighborhood Activation Model also predicted phoneme feature information well. CONCLUSION: The results obtained suggest that the Neighborhood Activation Model provides a reasonable explanation of word recognition by postlingually deafened adults after cochlear implantation. It appears that multichannel cochlear implants give cochlear implant users access to their mental lexicons in a manner that is similar to listeners with acoustic hearing. The lexical properties of the test stimuli used to assess performance are important to spoken-word recognition and should be included in further models of the word recognition process.

Adult↗

PubMed2003

Ping-pong cross-validation in real space: a method for increasing the phasing power of a partial model without risk of model bias.

Experimental phases could only be obtained to 4.4 A resolution for crystals of the SecA translocation ATPase. Density modification of these phases exploiting the 65% solvent content of the crystal produced a map from which an approximate backbone model could be built for 80% of the structure. Combining the phases inferred from this partial model with the MIR phases and repeating the density modification produced an improved map from which a more complete backbone model could be built. However, this procedure converged before yielding a map, that allowed unambiguous sequence assignment for the majority of the protein molecule. In order to avoid the likely model bias associated with a speculative attempt at sequence assignment, a real-space cross-validation procedure was employed to facilitate completion of the crystal structure based on partial model phasing. The protein was partitioned into two disjoint sets of residues. Models in which the side chains were built for residues in one of the two sets were used for phase combination and density modification in order to produce improved electron density for interpretation of residues in the other set that had not been included in the model. Residues in the two sets were therefore omitted from the model in alternation except at sites where the side chain could be identified definitively based on phasing with the other set. This ping-pong cross-validation procedure allowed partial model phasing to be used to complete the crystal structure of SecA without being impeded by model bias. These results show that the structure of a large protein molecule can be solved with exclusively low-resolution experimental phase information based on intensive use of partial model phasing and density modification. Real-space cross-validation can be applied to reduce the risk of model bias associated with partial model phasing, streamlining this approach and expanding its range of applicability.

Adenosine Triphosphatases↗

PubMed1990

Physiological interpretations based on lumped element models fit to respiratory impedance data: use of forward-inverse modeling.

Respiratory impedance (Zrs) data at lower (less than 4 Hz) and higher (greater than 32 Hz) frequencies require more complicated inverse models than the standard series combination of a respiratory resistance, inertance, and compliance. In this paper, a forward-inverse modeling approach was used to provide insight on how the parameters in these more complicated inverse models reflect the true physiological system. Forward models are set up to incorporate explicit physiological and anatomical detail. Simulated forward data are then fit with identifiable inverse models and the parameter estimates related to the known detail in the forward model. It is shown that inverse fitting of low frequency data alone will not allow a distinction between frequency dependence due to airway inhomogeneities and frequency dependence due to tissue viscoelasticity. With higher frequency data, a forward model based on an asymmetric branching airways network was used to simulate Zrs from 0.1-128 Hz with increasing amounts of nonuniform peripheral airway obstruction. Here, inverse modeling is more amenable to sensibly separating estimates of airway and tissue properties. A key result, however, is that changes in the tissue parameters of an inverse model (which provides an excellent fit to Zrs data) will appropriately occur in response to inhomogeneous alterations in airway diameters only. The apparent altered tissue properties reflect the decreased communication of some tissue segments with the airway opening and not an explicit change at the tissue level. These phenomena present a substantial problem for the inverse modeler. Finally, inverse model fitting of low and high frequency Zrs data simultaneously with a single model is not helpful for extracting additional physiological detail. Instead, separate models should be applied to each frequency range.

Airway Obstruction↗

PubMed2005

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models.

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.

Computer Simulation↗

PubMed2004

Development of a provisional domain model for the nursing process for use within the Health Level 7 reference information model.

OBJECTIVE: Since 1999, the Nursing Terminology Summits have promoted the development, evaluation, and use of reference terminology for nursing and its integration into comprehensive health care data standards. The use of such standards to represent nursing knowledge, terminology, processes, and information in electronic health records will enhance continuity of care, decision support, and the exchange of comparable patient information. As part of this activity, working groups at the 2001, 2002, and 2003 Summit Conferences examined how to represent nursing information in the Health Level 7 (HL7) Reference Information Model (RIM). DESIGN: The working groups represented the nursing process as a dynamic sequence of phases, each containing information specific to the activities of the phase. They used Universal Modeling Language (UML) to represent this domain knowledge in models. An Activity Diagram was used to create a dynamic model of the nursing process. After creating a structural model of the information used at each stage of the nursing process, the working groups mapped that information to the HL7 RIM. They used a hierarchical structure for the organization of nursing knowledge as the basis for a hierarchical model for "Findings about the patient." The modeling and mapping reported here were exploratory and preliminary, not exhaustive or definitive. The intent was to evaluate the feasibility of representing some types of nursing information consistently with HL7 standards. MEASUREMENTS: The working groups conducted a small-scale validation by testing examples of nursing terminology against the HL7 RIM class "Observation." RESULTS: It was feasible to map patient information from the proposed models to the RIM class "Observation." Examples illustrate the models and the mapping of nursing terminology to the HL7 RIM. CONCLUSION: It is possible to model and map nursing information into the comprehensive health care information model, the HL7 RIM. These models must evolve and undergo further validation by clinicians. The integration of nursing information, terminology, and processes in information models is a first step toward rendering nursing information machine-readable in electronic patient records and messages. An eventual practical result, after much more development, would be to create computable, structured information for nursing documentation.

Feasibility Studies↗

PubMed2001

Models for combining random and systematic errors. assumptions and consequences for different models.

A series of models for handling and combining systematic and random variations/errors are investigated in order to characterize the different models according to their purpose, their application, and discuss their flaws with regard to their assumptions. The following models are considered 1. linear model, where the random and systematic elements are combined according to a linear concept (TE = absolute value(bias) + z x sigma), where TE is total error, bias is the systematic error component, sigma is the random error component (standard deviation or coefficient of variation) and z is the probability factor; 2. squared model with two sub-models of which one is the classical statistical variance model and the other is the GUM (Guide to Uncertainty in Measurements) model for estimating uncertainty of a measurement; 3. combined model developed for the estimation of analytical quality specifications according to the clinical consequences (clinical outcome) of errors. The consequences of these models are investigated by calculation of the functions of transformation of bias into imprecision according to the assumptions and model calculations. As expected, the functions turn out to be rather different with considerable consequences for these types of transformations. It is concluded that there are at least three models for combining systematic and random variation/errors, each created for its own specific purpose, with its own assumptions and resulting in considerably different results. These models should be used according to their purposes.

Algorithms↗

PubMed1999

Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model: II. Comparison of models.

Several models were evaluated in terms of predictive ability for calving difficulty. Data included birth weight and calving difficulty scores provided by the American Gelbvieh Association from 26,006 calves born to first-parity cows and five simulated populations of 6,200 animals each. Included in the model were fixed age of dam x sex interaction effects, random herd-year-season effects, and random animal direct and maternal effects. Bivariate linear-threshold and linear-linear models for birth weight/calving ease and univariate threshold and linear models for calving ease were applied to the data sets. For each data set and model, one-half of calving ease records were randomly discarded. Predictive ability of the different models was defined with the mean square error (MSE) for the difference between a deleted calving ease score and its prediction obtained from the remaining data. In terms of correlation between simulated and predicted breeding values, the threshold models had a 1% advantage for direct genetic effects and 3% for maternal genetic effects. In simulation, the average MSE was .29 for linear-threshold, .32 for linear-linear, .37 for threshold, and .39 for linear model. For the field data set, the MSE was .31, .33, .39, and .40, respectively. Although the bivariate models for calving ease/birth weight were more accurate than univariate models, the threshold models showed a greater advantage under the bivariate model. For the purpose of genetic evaluation for calving difficulty in beef cattle, the use of the linear-threshold model seems justified. In dairy cattle, the evaluation for calving ease can benefit from recording birth weight.

Animals↗

PubMed2004

Modeling Hospital Information Systems (Part 2): using the 3LGM2 tool for modeling patient record management.

OBJECTIVES: We introduce the 3LGM(2) tool, a tool for modeling information systems, and describe the process of modeling parts of the hospital information system of the Leipzig University Hospital (UKL(a)). We modeled the sub information systems of five patient record archiving sections to support the creation of a proposal for governmental financial support for a new document management and archiving system. We explain the steps of identifying the model elements and their relations as well as the analyzing capabilities of the 3LGM(2) tool to answer questions about the information system. METHODS: The 3LGM(2) tool was developed on the basis of the meta model 3LGM(2) which is described in detail in [1]. 3LGM(2) defines an ontological basis, divided into three layers and their relationships. In addition to usual meta CASE tools, the 3LGM(2) tool meets certain requirements of information management in hospitals. The model described in this article was created on the base of on-site surveys in five archiving sections of the UKL. RESULTS: A prototype of the 3LGM(2) tool is available and is currently tested in some projects at the UKL and partner institutions. The model presented in this article is a structured documentation about the current state of patient record archiving at the UKL. The analyzing capabilities of the 3LGM(2) tool help to use the model and to answer questions about the information system. CONCLUSIONS: The 3LGM(2) tool can be used to model and analyze information systems. The presentation capabilities and the reliability of the prototype have to be improved. The initial modeling effort of an institution is only valuable if the model is maintained regularly and reused in other projects. Reference catalogues and reference models are needed to decrease this effort and to support the creation of comparable models.

Archives↗