Search

Self-monitoring of blood glucose provides information about blood glucose control. The data become useful information and knowledge through careful analysis for patterns that are appropriate or can be corrected. Some analyses can be performed on newer blood glucose meters, but most often, this needs to be done on a computer, tablet, or smartphone. There are a few established methods of presenting the data that make analysis easier. In this article, we discuss four types of data presentations and the methods for utilizing them., (© 2013 Diabetes Technology Society.)

Regulatory interest has focused on the accuracy of blood glucose monitoring systems. Currently, almost all systems meet the International Organization for Standardization (ISO) 15197 clinical standard (≥95% of the values within 20% of the reference for values above 75 mg/dl and within 15 mg/dl below that level). Should the systems have to meet one of the extended ISO standards of 15%, 10%, or even 5%? There is a wide variety of people with diabetes doing glucose monitoring, and the majority do not need better accuracy. Indeed, when selecting an insulin dose, the inaccuracy of the glucose reading has little effect compared with the inaccuracy in counting carbohydrates and the variability in insulin absorption. It might be far better to evaluate the accuracy in a standard method and provide the accuracy values on a standard label. Patients and health care providers could then select the monitoring system that best meets their needs., (© 2010 Diabetes Technology Society.)

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., (Copyright 2009 Diabetes Technology Society.)

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 new EGs 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 measurement of BG for patients with type 1 and type 2 diabetes.

This decade will bring major changes to the therapy of diabetes. New drugs are likely to include monomeric insulins, fatty-acid-oxidation inhibitors, insulin-secretion inducers, and nutrition modifiers. Likely new devices include improved insulin pens, less invasive methods of insulin administration, and noninvasive blood glucose monitoring. The use of computers will integrate this care, and artificial intelligence will provide new approaches to all of health care. An integrated system for using these new technologies, such as staged diabetes management, will ensure an orderly, cost-effective transition in therapy by the entire health-care community.

Two patients with insulinomas had unusual glucose and insulin-secretory dynamics in response to prolonged fasting. In patient 1, low insulin values persisted throughout three separate supervised fasts without a steady rise in the insulin-glucose ratio. In patient 2, a rising insulin-glucose ratio during a fast returned to normal after a documented catecholamine surge following a transient hypoglycemic episode. While patient 1 had clearly elevated proinsulin values of 52% to 57%, patient 2 had a near-normal value of 23%. The diagnosis of an insulinoma can usually be made by obtaining simultaneous glucose and insulin values during a prolonged supervised fast. Rarely, however, anomalous results may be obtained during supervised fasts of patients with insulinoma, and a broader range of diagnostic tests will be required to establish the correct diagnosis.