PubMed Health⌕ Search

Biomedical subjects

E R Carson

Publications and source records attributed to E R Carson.

At least 55 records · Page 3Linked to original sources
PubMed1976

Dynamic decision models for clinical diagnosis.

A unified approach to clinical decision-making is presented. This combines partially observable Markovian decision processes (Markov or semi-Markov) with cause-effect models as a probabilistic representation of the diagnostic process. Pattern recognition techniques are used in a first stage of system state identification. This new class of dynamic models has a direct application to medical diagnosis and treatment and specific physiological examples are emphasised. The methodology is given for combining the patient state of health, the clinician's state of knowledge of the cause-effect representation from the observation space (measurements), feature selection using pattern recognition techniques and, finally, the treatment decisions with which to restore the patient to a more desirable state of health. A cost functional for the decision process has then to be optimised according to some pre-assigned objective function (social return from the patient state of health or treatment cost for the patient), when the process has an infinite time horizon.

Computers↗
PubMed1976

An improved mathematical model of human thyroid hormone regulation.

1. A mathematical model has been constructed of human thyroid hormone regulation by the anterior pituitary gland, which takes account of most of the currently available experimental data. 2. Successful simulation of data on the stimulation of thyrotrophin (TSH) secretion by thyrotrophin releasing hormone (TRH) was achieved assuming that the TSH secretion rate is proportional to the logarithm of the concurrent blood TRH level. 3. Data on the regulation of triiodothyronine (T3) secretion by TSH and the inhibition of TSH secretion by thyroid hormones in contrast could not be simulated on the assumption of instantaneous proportional responses. A mixture of proportional and integral control--the latter taking account of the past history of plasma levels of the regulatory hormone--appeared to be operating at both levels. 4. The pituitary gland appears to be more sensitive to a given fractional change in TRH secretion rate than to the same fractional change in T3 plasma concentration.

Humans↗
PubMed1975

Hepatic albumin and urea synthesis: The mathematical modelling of the dynamics of [14C]carbonate-derived guanidine-labelled arginine in the isolated perfused rat liver.

A mathematical model was constructed to define the dynamics of incorporation of radioactivity into urea carbon and the guanidine carbon of arginine in plasma albumin after the rapid intraportal-venous administration of Na214CO3 in the isolated perfused rat liver. 2. The model was formulated in terms of compartmental analysis and additional experiments were designed to provide further information on subsystem dynamics and to discriminate between alternative model structures. 3. Evidence for the rapid-time-constant of labelling of intracellular arginine was provided by precursor-product analysis of precursor [14C]carboante and product [14C]urea in the perfusate. 4. Compartmental analysis of the dynamics of newly synthesized urea was based on the fate of exogenous [13C]urea, endogenous [14C]urea and the accumulation of [12C]urea in perfusate water, confirming the early completion of urea carbon labelling, the absence of continuing synthesis of labelled urea, and the presence of a small intrahepatic urea-delay pool. 5. Analysis of the perfusate dynamics of endogenously synthesized and exogenously administered [6-14C]arginine indicated that although the capacity for extrahepatic formation of [14C]-urea exists, little or no arginine formed within the intrahepatic urea cycle was transported out of the liver. However, the presence of a rapidly turning-over intrahepatic arginine pool was confirmed. 6. On the basis of these subsystem analyses it was possible to offer feasible estimations for the parameters of the mathematical model. However, it was not possible to stimulate the form and magnitude of the dynamics of newly synthesized labelled urea and albumin which were simultaneously observed after administration of [14C]carbonate on the basis of a preliminary model which postulated that both products were derived from a single hepatic pool of [16-14C]arginine. On the other hand these observed dynamics could be satisfied to a two-compartment arginine model, which also provided an explanation for discrepancies observed between albumin synthesis measured radioisotopically and immunologically. This was based on a relative overestimation of [14C]urea specific radioactivity resulting from the rapid dynamics of [14C]carbonate and the [14C]urea subsystem relative to the labelled albumin subsystem. The effects of arginine compartmentalization could be minimized in the model by minor slowing of the rate of [14C]carbonate turnover or by constant infusion of [14C]carbonate, both of which permitted valid determination of albumin-synthesis rates.

Animals↗
PubMed1975

Efficiency of utilization of urea nitrogen for albumin synthesis by chronically uraemic and normal man.

1. The relation between endogenous urea metabolism and albumin synthesis has been studied in ten patients with chronic renal failure and in four normal subjects, after single intravenous injections of [14-C]urea,[15-N]urea and 125-I-labelled albumin. 2. The rate of urea synthesis was determined from the dynamics of plasma [14-C]urea specific radioactivity and the rate of urea metabolism was estimated from the relative rates of urea synthesis and urea appearance in urine and body water. Deconvolution analysis of plasma [15N]albumin enrichmevt and 125-i-labelled albumin radioactivity yielded the cumulative incorporation of 15-N into total exchangeable albumin and enabled calculation of the absolute rate of urema nitrogen utilization for albumin synthesis. 3. Although the mean absolute rate of urea degradation in uraemic patients (3-7 mmol/h) was higher than in normal subjects (2-3 mmol/h) there was no significant positive correlation between urea degradation and plasma urea concentration. 4. In uraemic subjects, there was a significant positive correlation between urea synthetic rate and urea degration rate. 5. The rate of utilization of urea nitrogen for albumin synthesis was low, but was very much higher in uraemic subjects (mean 83-8 mumol/h) compared with normal subjects (mean 6-4 mumol/h), as was the provision by urea of the nitrogen required for albumin synthesis in uraemic subjects (2-37%) compared with normal subjects (0-13%). 6. The efficiency of utilization of urea nitrogen for albumin synthesis was higher in the uraemic patients (1-3%) than the normal subjects (0-2%), and was higher in those patients with chronic renal failure who received a 30 g protein diet than those on 70 g of protein. A significant negative correlation was noted between efficiency of urea nitrogen utilization and the rate of synthesis of albumin. 7. These studies suggest the presence of a mechanism for the conservation of urea nitrogen in chronic renal failure which is unrelated to the extent of urea degradation, and which can only be partly explained by the higher proportion of intraluminal gut nitrogen derived from urea.

Carbon Radioisotopes↗
PubMedDate not supplied

INFORM: development of information management and decision support systems for High Dependency Environments.

The long-term aim in the INFORM Project is to develop, evaluate and implement a new generation of Information Systems for hospital High Dependency Environments (HDE-Intensive Care Units, Neonatal Units, Burns Units. Operating and Recovery Rooms, and other specialised areas). The distinguishing feature of the HDE is the very large amount of data that is collected through monitors and paper records about the state of critically ill patients; this has made the role of the staff a technical one in addition to a caring one. The INFORM System will integrate Decision Support with on-line, off-line and observed patient data and, in addition, will incorporate and integrate unit management features. In the Exploratory Phase of the Project, functional requirements have been set out. These are based on four components: conceptual model of the HDE; evaluation of existing HDE Information Systems; development of a novel software architecture using a Knowledge-Based Systems (KBS) methodology, and based on a critical review of KBS applied to the HDE: monitoring of appropriate leading-edge technological developments. The conceptual model has two components: a patient-related information model, and a department-related cost model. The patient-related model is identifying key and difficult areas of decision making. A key aspect of INFORM is integration of clinical Decision Support for these areas into the Information System through a layered software architecture. The lower layers are concerned with monitoring and alarming and the higher levels with patient assessment and therapy planning. The functionality and interconnection of these layers are being determined.

Decision Support Systems, Management↗
PubMedDate not supplied

Information technology and computer-based decision support in diabetic management.

This paper describes the application of computer-based techniques within an intelligent, knowledge-based framework to the management of diabetes. The objectives are to structure data collection and storage so that the relevant patient-specific data are collected and made accessible as needed, and to provide clinical decision support on either a day-by-day or longer timescale as appropriate; these objectives relating to both hospital clinic and general practice. For longer-term management, a prototype rule set (greater than 500 rules) has been developed (coded in Sigma PROLOG), validated and tested on patient data. The data collection programs (written in SCULPTOR) to feed the ruleset have been tested in the hospital clinic and compared with the resident data collection system for usability, and impact on the running of the clinic. Links between the data collection programs and the ruleset program have been written and tested. The computer system will also incorporate a module, combining knowledge-based advisory system and glucose/insulin model as patient simulator, that can be tested as a potential decision aid for adjusting insulin dosage on a daily basis.

Data Collection↗
PubMedDate not supplied

Computer-assisted diabetic management: a complex approach.

This paper describes the architecture of, and the main reasoning methods involved in, a computer system developed to assist in diabetic management. The system integrates (i) a database module used for blood glucose monitoring, (ii) an interpreter module used to analyse the adequacy of diet and insulin treatment for diabetics, and (iii) an advisory module suggesting alterations in diet and/or insulin regimen in order to improve glycaemic control. The analysis of blood glucose profiles and hypoglycaemic episodes, as well as the suggestions for altered diet and insulin therapy, are based on qualitative and quantitative models of insulin effect and carbohydrate absorption using meal-time related glucose balance and distance from the preselected target (DFT) glucose values as focal concepts in the reasoning process. During the sequence of consultations with the system, a dynamic model of carbohydrate metabolism is gradually adjusted in order to constitute an appropriate simulation for the specific patient. This model is used to confirm the suggestions made by the ADVISOR program and to assist the health care professional in selecting the best control action by predicting the blood glucose profiles resulting from alternative control policies.

Algorithms↗
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↗
PubMedDate not supplied

An integrated approach for the computer-assisted treatment of diabetic patients on insulin.

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-dependent diabetic patient. The system also produces a 24-h 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 morning short-acting insulin by 2 units'. The quantitative simulator module contains two different mathematical models. The first is a non-linear model in differential equation form which consists of a one-compartment glucose model linked to a model with free and bound insulin compartments. This physiological model is solved by a general-purpose simulation engine. The second is a linear systems model which uses a transfer function to describe the insulin input/blood glucose response relationship for individual diabetic patients. Results of a preliminary medical validation are presented.

Blood Glucose↗
PubMedDate not supplied

Validation of a metabolic prototype to assist in the treatment of insulin-dependent diabetes mellitus.

This paper describes the principles and prototyping of a computer system to assist in the treatment of patients with insulin-dependent (type 1) diabetes mellitus. The system adopts a mixed approach involving rule-based qualitative algebra and a dynamic mathematical model to define the relationships between insulin dosage, diet and glycaemic response. The rule-based system (KBS), implemented in PROLOG, can be used to generate qualitative therapeutic advice. These suggestions are quantified and rank-ordered by the use of a mathematical model of glucose-insulin interaction in type 1 diabetes mellitus, with parameters adjusted for individual patients. In this paper an overview of the integrated prototype, linking the KBS and model, is provided and a case study used to demonstrate the principles of the system in operation. The results of verification and validation work performed on the KBS are described.

Blood Glucose↗