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R Hovorka

Publications and source records attributed to R Hovorka.

16 recordsLinked to original sources
PubMed1991

Identification of insulin receptor systems: assessing the impact of model selection and measurement error on precision of parameter estimates using Monte Carlo study.

An extensive Monte Carlo study has been carried out in order to study the effect of measurement error on the precision of parameter estimates of an insulin binding system. Hypothetical radioimmunoassay experiments were generated for insulin binding to erythrocytes. The design of experiments followed strictly the protocol of real experiments. Randomly generated error was added to the synthetic data. The standard technique, a weighted non-linear regression analysis, was employed to re-estimate parameters of a model of two receptor sites and a model of negative co-operativity. As the original parameter values were known, the differences between original and estimated values was studied for (a) measurement error in the range from 0-17%, (b) random initial estimates and (c) error-free non-specific binding. In addition, analytical estimates of parameter precision were compared with the true between-experiment variation of parameter estimates. At the measurement error of 12%, a one site model is recommended to estimate the high affinity population of the two sites model. Plausible results can be expected in 90% of experiments, the between-experiment variation being approximately 30%. The model of two receptor sites gives approximately two thirds of plausible results. The high affinity population can be estimated with the between-experiment variation of 40%, the low affinity population is virtually unidentifiable with the between-experiment variation of approximately 100% and parameter estimates biased to higher values. Only half of the results obtained from the model of negative co-operativity are plausible, the variation in parameter estimates ranges from 90-150% and estimates are biased to higher values. At the level of 12% measurement error, random initial estimates do not significantly affect the estimation process, provided initial estimates are selected from a feasible range. At the same measurement error, the error-free non-specific binding does not improve the results, indicating that the mean of six replicates may be taken as a reliable estimate of non-specific binding. The analytical estimates of the coefficient of variation systematically underestimates the true between-experiments coefficient of variation, the difference has been found to be about 50%.

Erythrocytes↗
PubMed1990

[Experience with a computer database in a cytogenetic laboratory].

The paper describes a computer system to support the data management in cytogenetics. Two major objectives are considered: the improvement of the quality and consistency of laboratory data and the support of data management in a large data set for research purposes. The entire system is divided into two logical parts. Firstly, a data collection module reads data from keyboard in an user-friendly way and checks for consistency including syntactic analysis of karyotype description. Secondly, the data are manipulated by a professional database system where three hierarchical data structures are introduced: 1. identification data, 2. investigation data and 3. karyotype description. Since 1984 we collected 1820 patients, 2800 investigations and 2760 karyotypes in the system. Currently, the system is reimplemented on IBM compatible machine using "dBase" database system in order to increase the operational speed and enhance the transportability of the system.

Chromosome Aberrations↗
PubMed1990

[A consulting system for insulin therapy in diabetes].

The authors describe a computer system which provides consultations on insulin treatment of diabetes. The intentions and aims of computer consultation and means for their implementation are described. The basic element of the system is the model of insulin pharmacodynamics. Two concepts are used to differentiate individual characteristics of the patient: the basal need and insulin sensitivity. The basal need is the amount of insulin which maintains the blood sugar level at the desired level in the course of the day, provided the subject adheres to a standard regime. The insulin sensitivity represents the sensitivity of the glucose metabolism to deviations from the basal requirement. These purely individual parameters are currently adapted by the "learning" module. The module compares the assessed and predicted blood sugar levels and corrects the parameters to achieve a minimum difference. The accuracy of approximation depends on the number of assessed blood sugar levels. The system foresees a minimum of two assessments per day. Individualized parameters are used for the prediction of the blood sugar level. The system visualizes predicted blood sugar levels for manually administered alternative insulin doses. The module of the automatic therapeutic plan is part of the module. The system recommends treatment with an "optimal" development of the predicted blood sugar level. As a criterium of the optimal profile of the blood sugar level the M-value was selected which is used for the evaluation of the daily blood sugar profile. The predictive capacity of the system was evaluated on the basis of retrospective data.(ABSTRACT TRUNCATED AT 250 WORDS)

Diabetes Mellitus↗
PubMed1990

[Analysis of dynamic changes in glycosylated blood proteins using a computer model].

UNLABELLED: The authors elaborated a computer model of albumin glycosylation based on the irreversible glycosylation reaction with first order kinetics. The dynamics of changes of glycosylated albumin in relation to the glycaemic profile was confirmed with an older model of haemoglobin glycosylation. By means of regression analysis parameters of the model in three groups of patients were calculated. CONCLUSION: 1. Stratification of the red cell pool is the reason why there is a smaller clinical difference between glycosylated protein and haemoglobin than corresponds to their half-times. 2. Glycosylated proteins are probably eliminated more rapidly than non-glycosylated ones. 3. Higher levels of glycosylated proteins sometimes do not correspond to model calculations are probably due to other factors.

Computer Simulation↗
PubMed1990

Analysis of glycosylated serum protein changes using a computer model.

UNLABELLED: The authors devised a computer model of albumin glycosylation based on irreversible glycosylation reaction of first-order kinetics. The dynamism of glycosylated albumin changes in relation to glycaemic profiles was compared with an earlier model of haemoglobin glycosylation. A non-linear regression analysis was employed to calculate the parameters of the model in three groups of patients. CONCLUSIONS: 1. Erythrocyte pool stratification accounts for the smaller clinical difference between glycosylated protein and haemoglobin than would correspond to their respective half-life values. 2. Glycosylated proteins are probably eliminated more rapidly than non-glycosylated proteins. 3. Higher levels of glycosylated proteins are occasionally at variance with model calculations, a fact which is probably due to other factors.

Computer Simulation↗
PubMedDate not supplied

Computer models of albumin and haemoglobin glycation.

UNLABELLED: Two first-order mathematical models were developed to mimic the glycation of haemoglobin (H) and albumin (A). The total concentrations of A and H were assumed to be constant. The responses of the two models to varying blood glucose level were compared. The parameters of the haemoglobin model were not numerically estimated, only an informal fit was performed using clinical and published data. Nonlinear regression analysis was used to estimate the parameters of the albumin model. The level of glycated A (GA) was derived from the measured fructosamine level. Three diabetics were monitored daily for the level of fructosamine and blood glucose profile over a period of 10, 16 and 21 days, respectively. CONCLUSIONS: (1) The difference between GA and glycated H (GH) resulting from different elimination rates is decreased by the stratification of erythrocyte population. (2) Both GA and GH seem to have higher elimination rates than their nonglycated equivalents.

Blood Glucose↗
PubMedDate not supplied

A consultation system for insulin therapy.

This paper describes a computer system to advice on insulin therapy for diabetic in-patients. A mathematical model was developed to describe the effect of insulin on blood glucose (BG) level. The system uses an adaptive approach to analyse the response to an applied insulin dosage. It learns the patient's individual parameters. All conventional injection and insulin pump regimens are supported. The individualised model is used to predict BG level of the proposed insulin dosage. The system uses a generate-reject strategy to output optimum insulin therapy in terms of optimum BG. The predictive capability of the system was tested and it is able to predict BG with a precision of 2.5 mmol/l after 3 days and 6 days of insulin pump treatment and conventional injection therapy, respectively.

Blood Glucose Self-Monitoring↗