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R Hovorka

Publications and source records attributed to R Hovorka.

48 records · Page 3Linked to original sources
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↗