High concordance between expert anaesthetists' actions and advice of decision support system in achieving oxygen delivery targets in high-risk surgery patients.

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.

Do patients with advanced breast cancer benefit from chemotherapy?

This study aimed to assess the proportion of patients with advanced breast cancer who report benefit from first-line palliative chemotherapy using a simple global measure of wellbeing and to identify factors predicting benefit. A consecutive series of women with advanced breast cancer undergoing first-line palliative chemotherapy was evaluated. The main outcome measure was patient report of overall wellbeing assessed at post-treatment interview. Physical, psychological and functional status were assessed using the Rotterdam Symptom Checklist (RSCL) on three occasions (pretreatment, at the start of the third cycle and post treatment). It was planned that treatment would be discontinued after six cycles (i.e. 18-24 weeks). One hundred and sixty patients started treatment, of whom 155 were assessable for quality of life. After treatment, 41 (26%) patients reported they felt better, 29 (19%) felt the same and 34 (22%) felt worse than they did before treatment. The other 51 (33%) patients either died or stopped attending the hospital before the post-treatment interview and were assigned as treatment 'failures'. Patients who reported feeling better after treatment had improvements in psychological distress (P < 0.0001), pain (P = 0.01), lack of energy (P = 0.02) and tiredness (P = 0.02), as well as improvement in functional status (P = 0.07). Feeling better was also correlated with disease response (P = 0.03). Feeling worse after treatment or treatment 'failure' was predicted by the pretreatment presence of a dry mouth (P = 0.003) and high levels of psychological distress (P = 0.03). Pretreatment lack of energy (P = 0.01), dry mouth (P = 0.02), presence of liver metastases (P = 0.03) and breathlessness (P = 0.03) predicted treatment 'failures'. The results of this study suggest that first-line palliative chemotherapy for advanced breast cancer confers benefit on a substantial proportion of patients, with about one-quarter feeling better after treatment and nearly a half feeling better or the same some 4-6 months after the start of treatment. Factors identified in this study may assist clinicians in deciding which patients should not be offered treatment, because of high risk of feeling worse or treatment 'failure'. This work now needs to be validated on a further cohort of women receiving chemotherapy for advanced breast cancer.

Validation of an algorithm for oral anticoagulant dosing and appointment scheduling.

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.

Burnout and psychiatric disorder among cancer clinicians.

The prevalence and causes of 'burnout' and psychiatric disorder among senior oncologists and palliative care specialists have been measured in a national questionnaire-based survey. All consultant non-surgical oncologists in the UK were asked to participate. Sources of work-related stress and satisfaction were measured using study-specific questions which were aggregated into factors. Psychiatric disorder was estimated using the 12-item General Health Questionnaire. The three components of 'burnout'--emotional exhaustion, depersonalisation and low personal accomplishment--were assessed using the Maslach Burnout Inventory. Three hundred and ninety-three out of 476 (83%) consultants returned their questionnaires. The estimated prevalence of psychiatric disorder in cancer clinicians was 28%, and this is similar to the rate among British junior house officers. The study group had equivalent levels of emotional exhaustion and low personal accomplishment to those found in American doctors and nurses, but lower levels of depersonalisation. Among cancer clinicians, 'burnout' was more prevalent among clinical oncologists than among medical oncologists and palliative care specialists. Psychiatric disorder was independently associated with the stress of feeling overloaded (P < 0.0001), dealing with treatment toxicity/errors (P < 0.004) and deriving little satisfaction from professional status/esteem (P = 0.002). 'Burnout' was also related to these factors, and in addition was associated with high stress and low satisfaction from dealing with patients, and with low satisfaction from having adequate resources (each at a level of P < or = 0.002). Clinicians who felt insufficiently trained in communication and management skills had significantly higher levels of distress than those who felt sufficiently trained. If 'burnout' and psychiatric disorder among cancer clinicians are to be reduced, increased resources will be required to lessen overload and to improve training in communication and management skills.

From guidelines to decision support in the management of asthma.

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.

Computer system for assisting with clinical interpretation of tumour marker data.

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.

Decision support for patient management in oncology.

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.

A system for compartmental modelling and simulation.

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.

A data model for intensive care.

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.

Uptake and processing of glycoproteins by isolated rat hepatic endothelial and Kupffer cells.

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.

Uptake and processing of glycoproteins by rat hepatic mannose receptor.

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)

Stochastic model of human granulocyte-macrophage progenitor cell proliferation and differentiation. I. Setting up the model.

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.

Stochastic model of human granulocyte-macrophage progenitor cell proliferation and differentiation. II. Validation of the model.

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.

Validation of simple and complex models in physiology and medicine.

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.