In 1962, Clark and Lyons  developed the first glucose enzyme electrode that relied on a thin layer of glucose oxidase (GO) on an oxygen electrode with the sensor working by measuring the amount of oxygen the enzyme consumed. The first glucose meters were developed and marketed for self-monitoring of blood glucose for outpatients with diabetes. Glucose meters play an important role in the management and control of diabetes, particularly for those individuals requiring insulin. Over the years, meter usage has evolved to be used by individuals themselves for self-monitoring and by healthcare providers in a variety of clinical settings such as hospitals, emergency response units, nursing homes, physicians’ offices, and air ambulances. Glucose results derived from glucose meters are used by patients and healthcare professionals to make therapeutic decisions, so incorrect glucose results may have a negative impact on the patient outcomes.
The technology used by glucose meters has shown incremental improvements, such as ease of use, technical performance, and affordability, since the first handheld meter was commercially available in 1970s .
Over the years, their use, rightly or wrongly, has spread to hospitals and critical care units without confirming that they are “fit for purpose” for intended use, evidence of improved clinical benefit, and with limited understanding among healthcare professionals of their capability and limitations. Many healthcare professionals believe that the results from glucose meters parallel those produced by central laboratory analyzers and use them accordingly . The interchanging results between laboratory and glucose meters potentially lead to the misinterpretation of the patient’s glycemic status.
The glucose reference method is considered to be the isotope dilution technique using mass spectrometry . Point-of-care devices use direct reading biosensors that respond to active glucose molality, the amount of glucose per unit mass of water. The molality of glucose is identical in whole blood and plasma; however, when results are converted to a concentration so that they agree with laboratory methods, they become susceptible to water content, producing different results for plasma and whole blood.
This represents one of the key challenges of trying to develop a universal reference material that can be used to standardize all glucose meters. Even if the same sample type is used (e.g., whole blood or plasma), unacceptable differences have been obtained for both laboratory and point-of-care methods .
It has been recommended by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Scientific Division Working Group on Selective Electrodes and Point-of-Care Testing that a factor of 1.11 should be used to convert the concentration of capillary blood glucose to plasma glucose to reduce clinical misinterpretations when interchanging laboratory and point-of-care results [6, 7].
Blood glucose is monitored to manage diabetes treatment, including insulin dosage, use of oral antiglycemic agents, or measuring change in diet and/or lifestyle. The simulation models were developed by Boyd and Bruns to replicate the effects of glucose assay imprecision and bias on insulin dose to determine the desirable analytical performance for glucose monitoring . Using Monte Carlo simulation, they generated random true glucose values that were converted into observed glucose values. True glucose values across the range of 8.3–25.0mmol/L were arranged in increments coinciding with a sliding scale of insulin dose, which allowed the number of correct and incorrect insulin dosage decisions when increasing imprecision and bias were applied to the model.
With a total analytical error of 5%, 8%–23% incorrect insulin dosages were observed, which increased from 16% to 45% when imprecision increased to 10%. When the combination of imprecision and/or bias exceeded 10%, larger insulin dosage errors were found in >5% of occasions. To ensure correct insulin dosage in 95% of instances, bias and imprecision had to be <1%–2% depending on the average glucose and protocol used for insulin dosage. Although these dosage changes could not be directly linked with patient outcomes, they highlighted the importance of keeping imprecision and bias to a minimum and risks of using glucose methods that are imprecise.
Because the use of glucose meters becomes more widespread, questions are being asked about their accuracy and reliability in certain clinical situations, particularly those related to critical care. These concerns relate to the effectiveness of glucose meters in patient management or if they are being overused or used in situations that may result in the failure to achieve desired outcomes, inappropriate management, and ultimately increased cost of care.
Glucose meters are subject to numerous interferences including both endogenous and exogenous patient factors, such as pregnancy, medications, environmental factors, and operational factors.
Glucose meters: professional recommendations
Glucose meters should be evaluated under objective quality specifications, which may be based on clinical needs, professional recommendations, and regulatory requirements. Currently, there is no consensus for the analytical performance of glucose meters. Despite the numerous attempts by regulatory and professional organizations such as the Food and Drug Administration (FDA), Centers for Disease Control and Prevention, and American Diabetes Association (ADA), no universally accepted standards for glucose testing exist. Having no universally accepted quality specifications for glucose meters makes it difficult to compare the many published studies available.
The ADA has recommended that glucose meters agree with laboratory methods to within ±15% at all concentrations. The future goal of the ADA is that this is reduced to ±5% across all glucose concentrations .
The International Standards Organisation (ISO) is revising its criteria (ISO 15197) that currently state that 95% of the individual glucose results shall fall within ±0.83mmol/L (15 mg/dL) of the results of the manufacturer’s measurement procedure at glucose concentrations <4.2mmol/L (<75 mg/dL) and within ±20% at glucose concentrations ≥4.2mmol/L (≥75 mg/dL) . Using ISO 15197 performance criteria, a patient with a glucose concentration of 6.1mmol/L could be reported by the meter from 5.0 to 7.2 mmol/L, which could make the patient diabetic or non-diabetic. According to the generally accepted guidelines, diabetes can be diagnosed in the presence of a fasting venous plasma glucose of ≥7.0mmol/L or if the 2h postglucose load (75 g) is ≥11.1mmol/L . Although capillary blood glucose testing is not recommended for diagnosis of diabetes, it is possible that such result variations may lead to inappropriate management justifying why meters should not be used to diagnose diabetes.
The FDA and DIN EN ISO 17511 require that the measurement results of laboratory methods must be traceable to a reference material. In addition, it is recommended that the test results of blood glucose monitoring systems should be traced to the definitive reference method and the primary reference material. The Directive 98/79/EC on in vitro diagnostic medical devices also requires the calibration of in vitro diagnostic medical devices to be traceable to a reference method and/or to a reference material of higher metrological order . In addition, the JCTLM highlights that a suitable reference system consists of not only applying the definitive reference method and the reference material but also operating an accredited reference measurement laboratory .
A blood glucose monitoring system is only able to comply with the highest requirements for analytical quality if the glucose values measured using that system are traceable to the highest standard through an unbroken chain of comparative measurements. Isotope diluted gas chromatography/mass spectrometry (ID-GC/MS) is the internationally recognized definitive reference method for determining the mass concentration of glucose. NIST 917, the primary reference material of the highest metrological order, is used to calibrate the primary reference method .
This is followed by the hexokinase method as the secondary reference method. This method is recognized as a standard method. The hexokinase reference method is calibrated and monitored using calibrators and controls, whereby the target values are assigned by the ID-GC/MS method. It follows that blood glucose monitoring systems calibrated to predicated devices, such as the YSI glucose analyzer, do not guarantee trueness of measurement results.
It is a reasonable assumption to make that the performance requirements of glucose meters will be dependent on the intended clinical use of the meter. To date, no meter can match the analytical performance of laboratory methods. It is therefore not unreasonable to state that if a glucose meter does not match laboratory performance, it should not be used for diagnosis, yet there is considerable reliance on these meters for the management of diabetes globally. It is therefore important that meters are used for the purpose for which they are intended. Although the industry has the responsibility to continue improving the performance of meters, scientists and diabetes health professionals must take up the responsibility of ensuring that glucose meters used in clinical environments are “fit for purpose”. Often, the purchase of glucose meters is left to procurement officers who do not have the clinical or scientific skills to determine if the meter will fit the clinical use it is intended for.
It is also fair to assume that the reason professional societies have been challenged when attempting to set performance requirements of glucose meters is because they are used in a wide variety of clinical settings that have different performance requirements. It could be argued that devices should be categorized in relation to clinical use as having a minimum (clinically useable) and an optimal (guideline acceptable) performance requirement. A similar approach was suggested by Apple  for troponin testing and could equally be applied to glucose testing. Many devices may not achieve optimal requirement, but if they achieve minimum requirements, they could be safely used with care. Tables 1–3 summarize the basic information, interferences/operating restrictions, and important operational information that should be considered when selecting a new glucose meter.
Glucose meters: interferences
The type of interferences a glucose meter may exhibit is affected by the test strip technology and the detection method employed by the glucose meters.
Currently, the main enzymes used by glucose test strips are glucose oxidase (GOD) or glucose dehydrogenase (GDH). Both enzymes are coupled to a cofactor, such as flavin adenine dinucleotide (FAD), nicotinamide adenine dinucleotide (NAD), or pyrrolo-quinoline quinine (PQQ).
The glucose test strips have the respective enzyme dehydrated on the strip, and when blood is added to the strip, it rehydrates and reacts with the enzyme producing a product that can be detected by the meter. If the enzyme used is GO, glucose is oxidized to gluconic acid and hydrogen peroxide, whereas strips with GDH-PQQ enzyme oxidize glucose to gluconolactone and converts NAD to NADH [10, 16, 17]. Glucose concentration is detected either colorimetrically or amperometrically by the glucose meter.
To better understand why it is important to ensure that the meter being used is fit for purpose, one needs to understand what factors may influence the quality of glucose measurement obtained in different clinical situations. If these potential interferences are not taken into account, misleading results can be obtained leading to incorrect medications being administered, potentially resulting in hypoglycemia, coma, or even death. Table 2 outlines the potential interferences that need to be considered when selecting glucose devices for use in general medicine (hospital general medicine wards, general practice, and community health), intensive care unit, pediatric ward, and patient self-monitoring. When selecting a device for a particular clinical situation, it is important to consider what interferences will be common in the targeted patient population. This would assist in selecting the most appropriate device that best suits the intended population and clinical use.
Educating the user
The performance of glucose meters cannot be discussed without mentioning the importance of education for users of devices. How a meter is used has a significant influence on the accuracy of the result produced by the blood glucose meters. Patients often are not given appropriate education on how to use the system (meter, strip, and capillary collection) and teach themselves. This can result in a poor understanding of correct procedures when using meters such as washing hands, not using correct coding chip or following the manufacturer’s instructions, using expired test strips, and exposing strips to light and moisture [9, 10, 17, 18]. The studies exploring the effects of not correctly coding have shown that approximately 16% of patients in a typical endocrinology practice have miscoded their meters, leading to average errors of −37% to +29% . A study looking at the effect of washing hands before taking a capillary sample for glucose testing showed that if hands were not washed with water, erroneous glucose results were obtained. This effect was not nullified if hand washing was substituted with an alcohol swab. Also worrying was that a careful check of all instruction manuals for glucose devices in Japan failed to find recommendations for hand washing with water before testing for glucose .
This paper attempts to highlight that when selecting a glucose meter one needs to take into account what the clinical use of that meter will be and this will determine desirable analytical requirements and what potential interfering factors need to be considered. It is important to always remember that whether the glucose meter is for home use or for use in an intensive care unit, education is paramount in obtaining the best results possible. While education can address many pre-analytical issues that affect the quality of results, standardization and strip performance will require significant collaboration from both the manufacturers and clinical laboratory scientists to achieve the desired patient outcomes. The IFCC through its Point-of-Care Task Force and Working Group on Glucose Point-of-Care Testing comprised of both scientists and industry representatives are actively working toward these issues.
Conflict of interest statement
Authors’ conflict of interest disclosure: The authors stated that there are no conflicts of interest regarding the publication of this article.
Research funding: None declared.
Employment or leadership: Dr. George Koumantakis is representative of the manufacturers (Roche Diagnostics) among the WG and his presence did not influence the content of this paper.
Honorarium: None declared.
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About the article
Published Online: 2013-02-12
Published in Print: 2013-05-01