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.

Objective To determine the relation between exposure to glycaemia over time and the risk of macrovascular or microvascular complications in patients with type 2 diabetes. Design Prospective observational study. Setting 23 hospital based clinics in England, Scotland, and Northern Ireland. Participants 4585 white, Asian Indian, and Afro-Caribbean UKPDS patients, whether randomised or not to treatment, were included in analyses of incidence; of these, 3642 were included in analyses of relative risk. Outcome measures Primary predefined aggregate clinical outcomes: any end point or deaths related to diabetes and all cause mortality. Secondary aggregate outcomes: myocardial infarction, stroke, amputation (including death from peripheral vascular disease), and microvascular disease (predominantly retinal photocoagulation). Single end points: non-fatal heart failure and cataract extraction. Risk reduction associated with a 1% reduction in updated mean HbA 1c adjusted for possible confounders at diagnosis of diabetes. Results The incidence of clinical complications was significantly associated with glycaemia. Each 1% reduction in updated mean HbA 1c was associated with reductions in risk of 21% for any end point related to diabetes (95% confidence interval 17% to 24%, P < 0.0001), 21% for deaths related to diabetes (15% to 27%, P < 0.0001), 14% for myocardial infarction (8% to 21%, P < 0.0001), and 37% for microvascular complications (33% to 41%, P < 0.0001). No threshold of risk was observed for any end point. Conclusions In patients with type 2 diabetes the risk of diabetic complications was strongly associated with previous hyperglycaemia. Any reduction in HbA 1c is likely to reduce the risk of complications, with the lowest risk being in those with HbA 1c values in the normal range ( < 6.0%).

Each therapeutic agent, as monotherapy, increased 2- to 3-fold the proportion of patients who attained HbA1c below 7% compared with diet alone. However, the progressive deterioration of diabetes control was such that after 3 years approximately 50% of patients could attain this goal with monotherapy, and by 9 years this declined to approximately 25%. The majority of patients need multiple therapies to attain these glycemic target levels in the longer term.

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