Summary.The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from Varying degrees of/3-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient r-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and /3-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (R~=0.88, p<0.0001), the fasting insulin concentration (P~ = 0.81, p < 0.0001), and the hyperglycaemic clamp, (Rs=0.69,p< 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient/3-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (R~ = 0.61, p< 0.01) and with the estimate from the intravenous glucose tolerance test (R~ = 0.64, p < 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for/3-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.

Key PointsIn clinical practice, the level of arterial oxygenation can be measured either directly by blood gas sampling to measure partial pressure (PaO2) and percentage saturation (SaO2) or indirectly by pulse oximetry (SpO2).This review addresses the strengths and weaknesses of each of these tests and gives advice on their clinical use.The haemoglobin–oxygen dissociation curve describing the relationship between oxygen partial pressure and saturation can be modelled mathematically and routinely obtained clinical data support the accuracy of a historical equation used to describe this relationship.Educational AimsTo understand how oxygen is delivered to the tissues.To understand the relationships between oxygen saturation, partial pressure, content and tissue delivery.The clinical relevance of the haemoglobin–oxygen dissociation curve will be reviewed and we will show how a mathematical model of the curve, derived in the 1960s from limited laboratory data, accurately describes the relationship between oxygen saturation and partial pressure in a large number of routinely obtained clinical samples.To understand the role of pulse oximetry in clinical practice.To understand the differences between arterial, capillary and venous blood gas samples and the role of their measurement in clinical practice.The delivery of oxygen by arterial blood to the tissues of the body has a number of critical determinants including blood oxygen concentration (content), saturation (SO2) and partial pressure, haemoglobin concentration and cardiac output, including its distribution. The haemoglobin–oxygen dissociation curve, a graphical representation of the relationship between oxygen satur­ation and oxygen partial pressure helps us to understand some of the principles underpinning this process. Historically this curve was derived from very limited data based on blood samples from small numbers of healthy subjects which were manipulated in vitro and ultimately determined by equations such as those described by Severinghaus in 1979. In a study of 3524 clinical specimens, we found that this equation estimated the SO2 in blood from patients with normal pH and SO2 >70% with remarkable accuracy and, to our knowledge, this is the first large-scale validation of this equation using clinical samples. Oxygen saturation by pulse oximetry (SpO2) is nowadays the standard clinical method for assessing arterial oxygen saturation, providing a convenient, pain-free means of continuously assessing oxygenation, provided the interpreting clinician is aware of important limitations. The use of pulse oximetry reduces the need for arterial blood gas analysis (SaO2) as many patients who are not at risk of hypercapnic respiratory failure or metabolic acidosis and have acceptable SpO2 do not necessarily require blood gas analysis. While arterial sampling remains the gold-standard method of assessing ventilation and oxygenation, in those patients in whom blood gas analysis is indicated, arterialised capillary samples also have a valuable role in patient care. Th...

Summary. Continuous infusion of glucose with model assessment (CIGMA) is a new method of assessing glucose tolerance, insulin resistance and r-cell function. It consists of a continuous glucose infusion 5mg glucose/kg ideal body weight per min for 60 min, with measurement of plasma glucose and insulin concentrations. These are similar to postprandial levels, change slowly, and depend on the dynamic interaction between the insulin produced and its effect on glucose turnover. The concentrations can be interpreted using a mathematical model of glucose and insulin homeostasis to assess insulin resistance and r-cell function. In 23 subjects (12 normal and 11 with Type 2 (non-insulin-dependent diabetes) the insulin resistance measured by CIGMA correlated with that measured independently by euglycaemic clamp (Rs = 0.87, p < 0.0001). With normal insulin resistance defined as 1, the median resistance in normal subjects was 1.35 by CIGMA and 1.39 by clamp, and in diabetic patients 4.0 by CIGMA and 3.96 by clamp. In 21 subjects (10 normal and 11 Type2 diabetic) the r-cell function measured by CIGMA correlated with steady-state plasma insulin levels during hyperglycaemic clamp at 10 mmol/1 (Rs = 0.64, p< 0.002). The CIGMA coefficient of variability was 21% for resistance and 19% for r-cell function. CIGMA is a simple, non-labour-intensive method for assessing insulin resistance and r-cell function in normal and Type 2 diabetic subjects who do not have glycosuria during the test.Key words: Insulin resistance, fl-cell function, mathematical model, glucose infusion, Type 2 diabetes, plasma insulin, plasma glucose.Patients with Type 2 diabetes are usually characterised by the severity of their hyperglycaemia, as assessed by glucose tolerance tests or by fasting plasma glucose measurements. The methods available for assessing the extent to which both/q-cell function and insulin resistance contribute to this hyperglycaemia are not suitable for routine use, and in most diabetic subjects pathophysiology is not assessed. If insulin resistance and deficient/q-cell function could be readily differentiated, it might be possible to predict an individual patient's response to diet, sulphonylurea or insulin therapy.The feed-back loop between the glucose stimulation of/3-cell secretion and insulin regulation of glucose turnover in the liver, muscle and fat, plays a major r6le in the regulation of fuel supply [1]. Although this is basically a very simple homeostatic system, the interactions are sufficiently complex that the glucose and insulin responses to clinical tests are not easy to assess. Thus, interpretations of the r61es of insulin resistance and r-cell deficiency in maturity-onset diabetic subjects vary [2,3]. With the aid of mathematical models, the effects of different combinations of insulin resistance and/q-cell deficiency can be predicted [4,5].We have investigated a new method which aims to give a near-physiological stimulus and to interpret the endogenous insulin and glucose responses. A standard, constant, low-dose glucose ...

Low IGFBP-2 is associated with multiple cardiovascular risk factors similarly to IGFBP-1. Such associations were not apparent for IGFBP-3. Lack of marked prandial regulation of IGFBP-2, in contradistinction to IGFBP-1, may make IGFBP-2 a more robust biomarker for identification of insulin-resistant individuals at high cardiovascular risk in epidemiological studies.