The application of novel investigative techniques has established that there is a high prevalence of disordered gastrointestinal motor function in patients with diabetes mellitus and has provided insights into its pathogenesis and clinical significance. Acute changes in the blood glucose concentration, even within the normal postprandial range, affect both gastrointestinal motor function and the perception of sensations arising from the gastrointestinal tract. Gastric emptying is slower during hyperglycaemia and accelerated during hypoglycaemia; the perception of gastric distension is greater during hyperglycaemia than euglycaemia. The pathways mediating the effects of the blood glucose concentration on gut motility and sensation are poorly defined. The rate of gastric emptying is an important determinant of postprandial blood glucose concentrations and there is increasing evidence that gastric emptying can be modulated therapeutically in order to optimize glycaemic control in patients with diabetes.

Gastrointestinal motor function in diabetes mellitus: Relationship to blood glucose concentrations: GI motor function in diabetes

where BMS is the between-blood sample mean square, EMS is the residual mean square, MMS is the betweenmethod mean square, k is the number of methods used to measure blood glucose (2 in this case), and n is the number of blood samples examined. The resulting ICC for the data in Table 2A is 0.97, which indicates a high level of agreement between the SMBG and laboratory measurements. One of our reservations with the ICC is that the size of the coefficient is influenced greatly by the amount of variability in the blood glucose measurements. The data in Table 2, B and C, illustrate how a reduction in the range of blood glucose values leads to a reduction in the ICC. (Note that these are extreme examples used only to illustrate what happens when a restricted range of blood values is examined; studies examining the performance of SMBG devices should include a representative range of blood glucose values.) The ICCs for the data in Table 2, B and C, are 0.83 and 0.01, respectively, despite the fact that the laboratory measurements are 20 U higher than the SMBG measurements in each example. The second problem with the ICC is that it provides little information about the clinical significance of the errors associated with SMBG. The issues of statistical and clinical significance have been discussed by various investigators in reference to the use of the Pearson r and regression analyses and apply equally to the use of the ICC (4-7). The crux of the argument against the use of the ICC to evaluate the clinical significance of any error in an SMBG system is that two SMBG measurements that deviate by the same amount from their true values may have very different clinical meanings depending on the true values. For example, a 50% underestimate of the true value of 2.8 mM blood glucose will not make any difference in terms of the treatment actions taken by a patient. Under these circumstances, the patient will take corrective action to raise blood glucose. However, a 50% underestimate when the true value is 16.8 mM will result in the patient not taking action to lower a clinically elevated blood glucose level. In view of these comments, we do not recommend the ICC as the primary method for evaluating the quality of the measurements from self-monitoring systems. Currently, the most useful method for evaluating the data from self-monitoring systems is the error-grid analysis graphic display technique developed by Cox et al. (4-6).

D Melessa Phillips

Papers

Additional Issues in Use of Intraclass Correlation