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Biomedical subjects

T Deutsch

Publications and source records attributed to T Deutsch.

At least 19 recordsLinked to original sources
PubMed1998

Compartmental models for glycaemic prediction and decision-support in clinical diabetes care: promise and reality.

This paper reviews and critically appraises the application of compartmental models for generating glycaemic predictions and offering clinical decision support in diabetes care. Comparisons are made with alternative algorithmic-based approaches. Unresolved issues raised for model-based techniques include the relative lack of input data necessary for generating reasonable blood glucose predictions, and the high level of uncertainty associated with such predictions which limits their use as guides for therapeutic insulin-dosage adjustments. It is concluded that compartmental model-based approaches, while not offering much benefit for clinical/therapeutic application, will have a role to play as research tools and for educational use. By contrast it is proposed that algorithmic-based approaches, especially in conjunction with telemedicine and Internet applications, are likely to see growing use for day-to-day therapeutic decision support. Randomised controlled clinical trials however will be required, together with other evaluation efforts, before algorithmic-based approaches-like any other clinical technique-can be widely adopted into routine medical practice.

Algorithms↗
PubMed1997

[Rule-based consultation systems].

This paper overviews the architecture of rule-based consultation systems and illustrates how such systems work by an Antibiotic Advisor. Knowledge representation and the inference engine implemented in the program are briefly described along with a sample consultation with the system. The paper is concluded with an analysis of the advantages and limitations of rule-based reasoning in clinical decision support.

Anti-Bacterial Agents↗
PubMed1997

[Electronic medical consultation].

This short paper introduces various preprogrammed and knowledge-based decision support methods. Fundamentals of case-based reasoning, clinical algorithms, statistical decision theory, decision trees, rule-based systems, causal networks and mathematical models that can be used to store and manipulate medical knowledge are reviewed. This brief introduction can serve as a guide to papers illustrating the use of different methodologies in clinical practice.

Humans↗
PubMed1996

Computer assisted diabetes care: a 6-year retrospective.

Over the past 6 years we have designed a number of computer-based prototypes for the provision of therapeutic advice and the generation of glycaemic predictions in insulin-dependent (type 1) diabetic patients. In this paper we provide an overview of some of this work, and describe our experiences in trying to develop such methods for clinical use. We review, as an example, a model of the glucoregulatory system which has been developed for patient and medical staff education about type 1 diabetes mellitus, as well as possibly for therapeutic use. Using individualised parameter values the predictions of the model can be applied to generate 24-h simulations of patient blood glucose profiles. Previous preliminary retrospective validation work performed with this model has revealed a mean predictive accuracy for blood glucose simulations of approximately 2 mmol/l. Conceptual limitations of such modelling approaches are considered. We comment that such "mechanistic' models may lack the necessary sophistication and flexibility to represent the complexity of the human glucoregulatory system and the challenges it has to face. Although such methodologies may therefore not be suitable for safe and effective application in routine clinical practice, we conclude that the evolution of such a system for demonstration/educational purposes could have widespread clinical utility as an interactive teaching tool.

Artificial Intelligence↗
PubMed1994

Time series analysis and control of blood glucose levels in diabetic patients.

This paper describes features of a computer-based decision support system which is being developed to assist in the management of insulin-dependent diabetic patients. The clinical context is the provision of advice on the adjustment of the basic insulin regimen such as occurs at regular visits to the clinician. The integrated system combines data processing and interpretation, generation of qualitative advice and testing the implications of that advice using a glucose/insulin dynamic simulator. The two major features described in this paper are time series analysis of blood glucose data, and their interpretation in relation to the provision of advice for controlling the patient's blood glucose level. It is demonstrated that two approaches may be adopted in such time series analysis: an intuitive approach, manipulating symbolic representations of the data, and formal time series methods which decompose the series into clinically related components.

Blood Glucose↗
PubMed1994

AIDA: an interactive diabetes advisor.

AIDA is a prototype computer system that incorporates a model of glucose-insulin interaction in type I diabetes mellitus alongside a knowledge-based system to make glycaemic predictions and to generate insulin dosage adjustment advice. The model attempts to reflect the underlying (patho)physiology of insulin action and carbohydrate absorption in quantitative terms. The prototype is intended to be used as a decision support system by clinical personnel in the context of day-to-day management of insulin-dependent diabetic patients. It is designed for use during consultations, as a simulator of patient response following changed insulin and dietary regimen and as a system for providing education on planning insulin therapy. Joe Daniels is a 41-year-old, 70-kg, male insulin-dependent diabetic patient who was diagnosed as being diabetic in 1972, at the age of 22. Joe recently found that he was having hypoglycaemic symptoms. Using self-monitoring blood glucose equipment, glycaemic levels below 3.0 mmol/l were recorded at least once a week, while hyperglycaemic readings (> 16 mmol/l) were observed two to three times per week. Joe came into hospital to have his glycaemic control improved, as doctors were concerned about the risks of him suffering a serious hypoglycaemic attack. Using some of the data collected by Joe while in hospital, we will demonstrate how AIDA might be applied either in a clinical setting to provide therapeutic advice or in an educational setting to interactively teach diabetic patients about their diabetes and educate them to adjust their own insulin injections and diet.

Adult↗
PubMed1994

Combining rule-based reasoning and mathematical modelling in diabetes care.

A prototype computer system utilising a model of carbohydrate metabolism linked to an expert system is described. The prototype which integrates quantitative and qualitative computational methodologies can be used to predict blood glucose profiles and adjust insulin doses in insulin-dependent (type I) diabetic subjects. A feedback loop insulin-dosage optimisation procedure which allows quantitative advice to be generated is also described. Possible clinical applications for the system, which is intended for educational use and clinically as a research tool to try and attain normoglycaemia, are discussed.

Algorithms↗
PubMed1994

Retrospective validation of a physiological model of glucose-insulin interaction in type 1 diabetes mellitus.

We have previously described a physiological model of glucose-insulin interaction in insulin-dependent (type 1) diabetes mellitus which has been developed for patient and medical staff education about diabetes mellitus, as well as possibly for clinical use. The model attempts to reflect the underlying (patho)physiology of insulin action and carbohydrate absorption in quantitative terms such as insulin sensitivity, volume of glucose and insulin distribution and maximal rate of gastric emptying. The model's predictions also allow a 24 h simulation of patient blood glucose profiles to be generated. Advice is provided by a qualitative knowledge based system which suggests what the next step in improving glycaemic control might be for a given patient, e.g. 'increase before breakfast long-acting insulin by 2 units'. Validation work performed on a previous version of the knowledge based system has demonstrated that it can provide qualitative advice comparable to that of a clinician. Furthermore, bench testing of the predictive accuracy of the model has yielded encouraging results. We therefore set out to perform a preliminary retrospective medical validation of the physiological model using data collected by 30 insulin-dependent diabetic patients attending diabetes out-patient clinics at various centres throughout Europe. We found that the physiological model could only be parameterized for data from 24 (80%) of the 30 patients in the study. Comparison of observed and predicted blood glucose data from these 24 patients over a period of 5-6 days following parameter estimation revealed a mean (+/- SD) root mean square deviation between measured and simulated blood glucose values of 1.93 +/- 0.86 mmol l-1. The implications of these results are discussed.

Blood Glucose↗
PubMed1994

Adaptive control in drug therapy.

In medical practice, drugs are administered with the goal of attaining a therapeutic effect without exceeding predetermined safety limits on any adverse action. This paper is intended to provide an introduction to pharmacokinetic-model based adaptive control of drug levels that can be of use in achieving such therapeutic objectives. The principles are illustrated by the problem of providing rapid relief of acute asthmatic symptoms by infusing theophylline.

Adaptation, Physiological↗
PubMed1993

AIDA2: a Mk. II automated insulin dosage advisor.

A prototype computer system has been developed to provide advice on the day-to-day adjustment of insulin dosage in the insulin-dependent (type 1) diabetic patient. The system also allows the patient's daily steady-state blood glucose profile to be generated based on these adjustments using a clinical model of glucose-insulin interaction. The prototype is intended to be used as a decision support system by clinical personnel. It is designed for use during consultations, as a simulator of patient response following changes in the insulin and/or dietary regimen, and as a system to provide education on planning insulin therapy. Advice is generated by a qualitative therapeutic advisor which suggests what the next step in improving glycaemic control might be for a given patient. The clinical model attempts to reflect the underlying (patho)physiology of insulin action and carbohydrate absorption in quantitative terms. It consists of a one-compartment glucose model linked to a model with plasma and 'active' insulin compartments. An overview of the integrated prototype is provided along with a detailed description of the new time-point-orientated logical reasoning methodology adopted by the therapeutic advisor. The operation of the system is illustrated by a clinical case study from a 70 kg, male, insulin-dependent diabetic patient.

Blood Glucose↗
PubMed1993

Control engineering for planning drug therapy.

An optimal drug input may be defined as producing an ideal therapeutic effect as closely as possible without exceeding predetermined safety limits on any adverse drug effects. The intensity and time patterns of the drug-elicited response are functions of the pharmacodynamic properties of the drug in the patient. Drug input optimisation can be considered as a control problem and the different control engineering techniques may serve to assist in planning/implementing drug dosage regimens. This paper reviews some problems associated with planning optimal drug therapy in different clinical context and illustrates the solution of such problems by clinical examples.

Biomedical Engineering↗
PubMed1992

A physiological model of glucose-insulin interaction in type 1 diabetes mellitus.

A clinical model of glucose-insulin interaction in insulin-dependent diabetes mellitus has been developed for patient and medical staff education. The model attempts to reflect the underlying (patho)physiology of insulin action and carbohydrate absorption in quantitative terms such as insulin sensitivity, volume of glucose and insulin distribution and maximal rate of gastric emptying. The model's predictions also allow a 24 h simulation of patient blood glucose profiles to be generated. A description of the model is provided and its operation illustrated by clinical case studies of insulin-treated diabetic patients. The possible use of the model as a tool for automated insulin dosage adjustment is explored.

Blood Glucose↗
PubMed1992

Insulin dosage adjustment in diabetes.

A prototype computer system has been developed to provide advice on the day-to-day adjustment of carbohydrate intake and insulin regimen in the insulin-treated diabetic patient. The system also produces a 24-hour simulation of the patient's blood glucose profile based on these adjustments. Advice is generated by a qualitative knowledge-based system which suggests what the next step in improving glycaemic control might be for a given patient, e.g. 'decrease evening medium-acting insulin by two units'. Simulations are provided by a non-linear model which consists of a one-compartment glucose model linked to a model with plasma and 'active' insulin compartments. A description of the integrated system is provided and its operation illustrated by clinical case studies from insulin-treated diabetic patients.

Blood Glucose↗
PubMed1992

Pneumocystis carinii choroiditis in patients with AIDS: clinical features, response to therapy, and outcome.

To further characterize the clinical features, response to therapy, and outcome of Pneumocystis carinii choroiditis in patients with AIDS, we retrospectively reviewed the course of choroiditis for eight patients identified from two institutions through April 1991. Seven patients had prior Pneumocystis carinii pneumonia and had received aerosolized pentamidine prophylaxis for a median of 10 months; one patient had no prior history of pneumonia or prophylaxis. The median CD4+ lymphocyte count for six patients was 11 cells/mm3. Choroiditis was a preterminal diagnosis for three patients--two with associated disseminated pneumocystosis. Ocular manifestations improved or resolved with therapy for five of the six treated patients. All five subsequently received prophylaxis with dapsone (n = 2), dapsone/trimethoprim (n = 2), or aerosolized pentamidine (n = 1). Choroiditis recurred at 15 months in the one patient receiving aerosolized pentamidine. The median survival from time of diagnosis was 44 weeks. A literature review including an additional 40 cases support the conclusions that (a) Pneumocystis choroiditis is a rare complication of advanced HIV disease, occurring often in the context of systemic pneumocystosis; (b) ocular signs and symptoms may improve or resolve with specific antipneumocystis therapy; and (c) relapse may occur, particularly in those not receiving systemic prophylaxis.

AIDS-Related Opportunistic Infections↗
PubMed1992

An interactive, educational model for insulin dosage and dietary adjustment in type I diabetes mellitus.

Joe Daniels is a 41 year old, 76kg male, insulin-treated diabetic patient who was diagnosed as being diabetic in 1972, at the age of 22. Joe recently found that he was having hypoglycaemic symptoms. Using self-monitoring blood glucose equipment glycaemic levels below 3.0 mmol/l were recorded at least once a week while hyperglycaemic readings (> 16 mmol/l) were observed 2-3 times per week. Joe came into hospital to have his glycaemic control improved as doctors were concerned about the risks of him suffering a serious hypoglycaemic attack. Using some of the data collected by Joe while in hospital we will demonstrate how a computer model of glucose-insulin interaction in type I diabetes can be used interactively to teach diabetic patients about their diabetes and educate them to adjust their own insulin injections and diet.

Adult↗
PubMed1992

AIDA: an automated insulin dosage advisor.

A prototype computer system utilising a model of carbohydrate metabolism linked to an expert system is described. The prototype which integrates quantitative and qualitative computational methodologies can be used to predict blood glucose profiles and adjust insulin doses in type I diabetic subjects.

Blood Glucose↗
PubMed1989

The principles and prototyping of a knowledge-based diabetes management system.

This paper describes the principles and prototyping of a computer-based system being developed to assist in the management of diabetes mellitus. Unlike other approaches based upon mathematical modelling or the use of computer algorithms, this system adopts one derived from artificial intelligence, seeking to incorporate the dynamics of glucose and insulin in a manner which reflects their clinical importance. The resultant logical model (qualitative algebra) defines the relationships between changes in insulin dose and site and time of injection and glycaemic response. In this manner the computer-based system, implemented in Prolog, can be used to provide advice concerning insulin therapy by means of making qualitative predictions of patient outcome of blood glucose profile resulting from alternative insulin regimens.

Blood Glucose↗