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By regarding the circulation from the perspective of the venous return, continuous therapeutic control of the mean arterial blood pressure, cardiac output and tissue oxygen flow can be seen to be the consequence of a series of equations based on conventionally measured variables. This approach permits a graphical solution to circulation guidance, open or closed loop control and goal directed therapy of broad general applicability. [ABSTRACT FROM AUTHOR]

Background: Goal-directed therapy has a secure place in perioperative care. Algorithms are based on Starling's law of the heart, notwithstanding that this does not numerically define volume or heart performance variables. These have been developed based on a Guytonian view of the circulation and are implemented in a computerized decision support system (Navigator™). We studied the feasibility and performance of the graphical display of the system in an intervention and a control group of patients undergoing major abdominal surgery., Methods: Patients were randomized to either graphically (intervention) or numerically (control) guided administration of therapy. Goals were set and treatments and concordance with guidance noted, where applicable. Anaesthesia was provided by one of three experienced anaesthetists well acquainted with Navigator™. The primary objective was to determine whether the use of graphical display decision support more efficiently enables the achievement of oxygen delivery targets. This was quantitated as percentage time in the target zone and averaged standardized distance from the target centre., Results: The mean percentage time in the target zone was 36.7% for control and 36.5% for intervention. The averaged standardized difference was 1.5 in control and 1.6 in intervention. There was no significant difference in fluid balances. There was a high level of concordance between decision support recommendation and anaesthetist action (84.3%)., Conclusions: In experienced hands, the addition of a graphical display for haemodynamic guidance resulted in a similar time in target and averaged standardized difference. The haemodynamic guidance system should be explored in a comparative study to anaesthesia management without guidance.

Computer clinical decision-support systems require validation before clinical use. This study compared recommendations on warfarin dosage adjustment and timing of the next appointment made by an algorithm with those made by experienced and inexperienced clinicians. Data abstracted from the records of 125 patients seen regularly in the anticoagulant clinic were used. The algorithm recommended dose changes and next appointment for cases with INRs between 1.8 to 4.2 (therapeutic range 2.0-3.0) and between 2.3 to 5.3 (therapeutic range 3.0-4.5). Beyond these values the algorithm referred the cases to "see doctor'. Compared to experienced clinicians, the algorithm was better at "recognising' difficult patients than inexperienced clinicians (kappa = 0.43 and 0.32 respectively). There was no statistically significant difference between all decision makers in dosage recommendations for the non-difficult cases, but there was much more variation amongst the inexperienced clinicians. The interval recommendations were statistically different between and within the different decision-makers. The inexperienced clinicians tended to give relatively longer intervals for a given dose change. In conclusion, the algorithm performs better than inexperienced clinicians and as well as experienced clinicians for the non-difficult cases.

Asthma is a common chronic disease of the lungs caused by inflammation of the airways affecting 6-7% of the population. Asthma is becoming commoner and there is evidence of under-diagnosis and poor management. Guidelines have been developed aimed at improving quality of care and in reducing social costs of asthma. The paper discusses an approach to implementing guidelines through decision-support system in primary care, based on methods developed in the AIM GAMES-II project. We also describe a prototype system that has been developed and a programme of clinical evaluation.

Objective: To design and evaluate a computer advisory system for the treatment of gestational trophoblastic tumour., Design: A comparison of clinicians' treatment decisions with those of the computer system. Two datasets were used: one to calibrate the system and one to independently evaluate it., Setting: Department of medical oncology., Patients: Computerised records of 290 patients with low risk gestational trophoblastic tumour for whom the advisory system could predict the adequacy of treatment. The calibration set comprised patients admitted during 1979-86(227) and the test set patients during 1986-89(63)., Main Outcome Measures: The system's accuracy in predicting need to change treatment compared with clinicians' actions. The mean time faster that the system was in predicting the need to change treatment., Results: On the calibration dataset the system was 94% (164/174) accurate in predicting patients whose treatment was adequate, recommending change when none occurred in only 10 (6%) patients. In patients whose treatment was changed the system recommended change earlier than clinicians in 39/53 cases (74%), with a mean time advantage of 14.9 (SE 2.02) days. On the test dataset the system had an accuracy of 91% (31/34) in predicting treatment adequacy and a false positive rate of 9% (3/34). The system recommended change earlier than clinicians in 22/29 cases (76%), with a mean time advantage of 12.5 (2.22) days., Conclusions: The computer advisory system could improve patient management by reducing the time spent receiving ineffective treatment. This has implications for both patient time and clinical costs.

In this paper a novel approach to the development of the architecture of a knowledge-based decision support system for the management of patients with cancer of the breast is described. Its initial design and subsequent realization in a prototype version was facilitated by examining closely the overall clinical task and identifying its associated activities and related knowledge. Implementation in KEE highlights the value of rigorous conceptual modelling that leads to a design able to assess treatment response and disease progression as well as providing specific therapy advice. The approach is general and may be applied to the development of decision support systems for other areas of cancer and medicine.

The paper describes a software package for modelling and simulating compartmental systems based upon a generalisation of the equations of compartmental systems. The aim is a versatile package which can be used for rapid model development. Its use is first illustrated in a number of simple classical examples. The power of the software--and more generally the methodology--is demonstrated by showing its application in developing a model-based system for insulin planning for diabetic patients. The software has been written in Pascal and runs on IBM PC and compatible computers.

The paper describes a model of clinical management data in a typical general intensive care unit, intended as a generic database specification for advanced intensive care computer systems. The data model was developed as part of the INFORM project. The INFORM project is summarised and the relevance of the data model to the objectives of the project are discussed. An object oriented extension to the entity relationship diagram methodology is presented. The methodology is illustrated with reference to some specific aspects of the data model including: the principle clinical entities; classification of patient state related data and the homogeneous patient group system. It is suggested that such a model will contribute to the better understanding of the data in the system, to the better design of future intensive care computer systems and to the setting of standards for medical data.

Mannose-(Man) and N-acetylglucosamine- (GlcNAc)-terminated glycoproteins are cleared from blood by carbohydrate-specific receptors present on both hepatic endothelial and Kupffer cells. It is not known whether the same receptors are present on each cell type or the relative contributions to glycoprotein metabolism made by Kupffer and endothelial cells. Here we report experiments where data from glycoprotein metabolism by purified populations of isolated rat hepatic endothelial and Kupffer cells have been analyzed by mathematical modelling and parameter estimation. Kupffer cells had significantly higher binding rate constants (k'21) than endothelial cells for agalactoorosomucoid (AGOR) and hyaluronidase, but lower k12 ('off-rate') indicating that Kupffer cells had higher affinities for Man/GlcNAc-terminated glycoproteins than endothelial receptors. Furthermore, although endothelial cells had similar affinities (k'21 and k12) for AGOR and hyaluronidase, the 'off-rate' of Kupffer cells was significantly greater for AGOR than for hyaluronidase, indicating that Kupffer cell receptors have lower affinity for AGOR. Internalization and ligand catabolic rates also differed between the two cell types. The data indicate that Kupffer and endothelial cells appear to have different Man/GlcNAc receptors and that the destination of a glycoprotein and its subsequent processing is determined by the structure of a glycoprotein's oligosaccharide.

The problem of assessing the value of mathematical models in physiology and medicine is considered. The role of validation within the modeling process is clearly defined. An appropriate vocabulary and validation procedures to be adopted are outlined for simple and complex models, with these two classes defined operationally on the basis of theoretical identifiability. Some examples illustrating these validation procedures are briefly discussed. It is shown that simple and complex models each have a role both in physiology and clinical application when properly validated.

A mathematical model is constructed for the proliferation and differentiation of granulocyte-macrophage progenitor cells in response to the specific proliferation/differentiation stimulus granulocyte-macrophage colony stimulating activity (gm-CSA). The major objective of this model was to test an earlier conceptual model in which we proposed that clone size potential and sensitivity to gm-CSA are functional properties of granulocyte-macrophage progenitor cells, properties that gradually change as the cells differentiate down the granulocyte-monocyte pathway. Another aim was to provide a tool for further analysis of the regulation of granulopoiesis and granulocyte-macrophage progenitor cell proliferation and differentiation. To formulate and then test the mathematical model, available experimental data were divided, one part being used to construct the model, and the other, the results of different and independent experiments, being used for model validation. This report describes the mathematical model and the estimation of model parameters using in vitro experimental results on the relationship between clone number and gm-CSA concentration and on the clone size distributions obtained under conditions of maximal stimulation by gm-CSA. The accompanying article shows how the model was then tested using data from three other types of experiment.

In the accompanying paper we constructed a model for the proliferation and differentiation of granulocyte-macrophage progenitor cells in response to the specific proliferation/differentiation stimulus granulocyte-macrophage colony-stimulating activity (gm-CSA). Here we have tested the model without altering the model parameters, which were estimated on the basis of two types of experiment (clone number versus gm-CSA dose-response curves and clone size distributions with maximal gm-CSA) by using these parameters to simulate additional independent experiments. These included data from separation experiments in which progenitor cells were separated on a basis of their density and were then tested for their sensitivity to gm-CSA and their proliferative capacity. In addition, other sets of experimental data (e.g., mean clone size versus time and colony versus gm-CSA dose-response curves and colony-to-cluster ratios) were also examined to detect whether the mathematical model provides an adequate representation of the data. The model gave a successful simulation of all experimental data.

A linear compartmental model has been developed for the in vivo metabolism of glycoproteins. The model is applied to the interpretation of dynamic data from the rat on agalactoorosomucoid (AGOR), an N-acetylglucosamine (GlcNAc-)-terminated glycoprotein, and three neoglycoproteins terminating in mannose [mannose36-bovine serum albumin (Man-BSA)] or glucose [maltose29-BSA (Mal29-BSA) and maltose8-BSA (Mal8-BSA)]. All of these proteins are taken up by the Man/GlcNAc receptor on hepatic sinusoidal cells. The rate of uptake was found to be determined by sugar type (Man-BSA, 0.78 min-1 greater than Mal29-BSA, 0.13 min-1), sugar density (Mal29-BSA greater than Mal8-BSA), and the geometry of the sugar display (AGOR, 0.51 min-1 greater than Mal29-BSA). Intracellular transport from the cell membrane to the lysosomes was slower for Man-BSA (approximately 3 min) than for the other ligands (approximately 0 min), suggesting that receptor-ligand uncoupling was slower for Man-BSA for which the receptor had the highest affinity or that extralysosomal catabolism of the other ligands occurred. Catabolism was also determined by the carbohydrate moiety of the ligand; it was greater for Mal29-BSA and Mal8-BSA (greater than or equal to 0.8 min-1) than for Man-BSA (0.27 min-1), and AGOR, with a complex oligosaccharide, was most resistant to degradation (0.14 min-1). An understanding of these structural features of glycoproteins that influence hepatic uptake, transport, and catabolism will be of value in drug targeting and for enzyme replacement in lysosomal storage disorders.(ABSTRACT TRUNCATED AT 250 WORDS)