OBJECTIVE -The objectives of this study were 1) to construct new error grids (EGs) for blood glucose (BG) self-monitoring by using the expertise of a large panel of clinicians and 2) to use the new EGs to evaluate the accuracy of BG measurements made by patients. RESEARCH DESIGN AND METHODS -To construct newEGs for type 1 and type 2 diabetic patients, a total of 100 experts of diabetes were asked to assign any error in BG measurement to 1 of 5 risk categories. We used these EGs to evaluate the accuracy of self-monitoring of blood glucose (SMBG) levels in 152 diabetic patients. The SMBG data were used to compare the new type 1 diabetes EG with a traditional EG.RESULTS -Both the type 1 and type 2 diabetes EGs divide the risk plane into 8 concentric zones with no discontinuities. The new EGs are similar to each other, but they differ from the traditional EG in several significant ways. When used to evaluate a data set of measurements made by a sample of patients experienced in SMBG, the new type 1 diabetes EG rated 98.6% of their measurements as clinically acceptable, compared with 95% for the traditional EG. CONCLUSIONS -The consensus EGs furnish a new tool for evaluating errors in the mea E m e r g i n g T r e a t m e n t s a n d T e c h n o l o g i e s 1144DIABETES CARE, VOLUME 23, NUMBER 8, AUGUST 2000 New error grid for blood glucose 152 patients who routinely monitor their own BG. The study was performed in a diabetes clinic with patients using their own meters. The distribution of errors in our sample is considered in light of both EGs and the latest recommendations of the American Diabetes Association (ADA). RESEARCH DESIGN AND METHODS Consensus EGWe surveyed 100 physicians at the 1994 ADA Annual Meeting to construct an unbiased tool to analyze the clinical significance of SMBG measurement errors. All of the respondents were clinicians who treated diabetic patients. Pursuant to constructing an EG in the fashion of Clarke et al. (6), each doctor was asked to assign any plausible error in BG measurement to 1 of 5 risk categories. The risk categories, in order of increasing severity, were defined as follows: A: no effect on clinical action; B: altered clinical action or little or no effect on clinical outcome; C: altered clinical action-likely to effect clinical outcome; D: altered clinical action-could have significant medical risk; and E: altered clinical action-could have dangerous consequences.The above definitions were intended to correspond to the definitions of the risk zones in the Clarke EG while allowing the respondents maximal freedom to set their own boundaries. For example, zone A of the Clarke EG is defined as Ͻ20% deviation or having both reference and measured BGs Ͻ70 mg/dl. In addition, the UVA authors (6) stated that "values falling within this range are clinically accurate in that they would lead to clinically correct treatment decisions." Our definition of zone A asks each respondent to define his or her own range of "clinically accurate measurements," which is clarified as having "no effe...

Glucose monitoring has become an integral part of diabetes care but has some limitations in accuracy. Accuracy may be limited due to strip manufacturing variances, strip storage, and aging. They may also be due to limitations on the environment such as temperature or altitude or to patient factors such as improper coding, incorrect hand washing, altered hematocrit, or naturally occurring interfering substances. Finally, exogenous interfering substances may contribute errors to the system evaluation of blood glucose.In this review, I discuss the measurement of error in blood glucose, the sources of error, and their mechanism and potential solutions to improve accuracy in the hands of the patient. I also discuss the clinical measurement of system accuracy and methods of judging the suitability of clinical trials and finally some methods of overcoming the inaccuracies. I have included comments about additional information or education that could be done today by manufacturers in the appropriate sections. Areas that require additional work are discussed in the final section.

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Current clinical guidelines for diabetes care encourage self-monitoring of blood glucose (SMBG) to improve glycemic control. Specific protocols remain variable, however, particularly among non-insulin-using patients. This is due in part to efficacy studies that neglect to consider (1) the performance of monitoring equipment under real-world conditions, (2) whether or how patients have been taught to take action on test results, and (3) the physiological, behavioral, and social circumstances in which SMBG is carried out. As such, a multidisciplinary group of specialists, including several endocrinologists, a health psychologist, a diabetes nurse practitioner, and a patient advocate (the Panel), discuss within this review article how the potential of SMBG might be fully realized in today's healthcare environment. The resulting recommendations cover technological, clinical, behavioral, and research considerations with the aim of achieving short- and long-term benefits, ranging from fewer hypoglycemic episodes to lower complication-related costs. The panel also made suggestions for designing future studies that increase the ability to discern optimal models of SMBG utilization for individuals with diabetes who may, or may not, use insulin.

Neuroblastoma cells were used to determine the effect of high carbohydrate and polyol levels on myo-inositol metabolism. The presence of elevated concentrations of glucose or sorbitol caused a significant decrease in both inositol accumulation and incorporation into phospholipid. These conditions, however, did not alter the accumulation of the other phospholipid head groups or the growth rate and water content of the cells. Two weeks of growth in either of the modified conditions was necessary to obtain a maximal effect on inositol incorporation. In contrast, growth in elevated concentrations of fructose, mannitol, or dulcitol had no effect on inositol metabolism. The reduced inositol accumulation and incorporation into lipids seen with glucose or sorbitol supplementation resulted in a decrease in the total phosphatidylinositol content of the cell without changing the levels of the other phospholipids. Kinetic analysis of cells grown in the presence of elevated glucose indicated that V'max for inositol uptake was significantly decreased with little change in the K'm. These data suggest that glucose decreases myo-inositol uptake in this system by noncompetitive inhibition. Cells grown in the presence of increased glucose also had elevated levels of intracellular sorbitol and decreased levels of myo-inositol. These results suggest that the high levels of glucose and sorbitol which exist in poorly regulated diabetes may be at least partially responsible for diabetic neuropathy via a reduction in the cellular content of myo-inositol and phosphatidylinositol. This system may be a useful model to determine the effect of reduced inositol phospholipid levels on neural cell function.