System accuracy of blood glucose monitoring systems: impact of use by patients and ambient conditions

Optoacoustic classification of diabetes mellitus with the synthetic impacts via optimized neural networks

A highly accurate classification of diabetes mellitus (DM) with the synthetic impacts of several variables is first studied via optoacoustic technology in this work. For this purpose, an optoacoustic measurement apparatus of blood glucose is built, and the optoacoustic signals and peak-peak values for 625 cases of in vitro rabbit blood are obtained. The results show that although the single impact of five variables are obtained, the precise classification of DM is limited because of the synthetic impacts. Based on clinical standards, different levels of blood glucose corresponding to hypoglycaemia, normal, slight diabetes, moderate diabetes and severe diabetes are employed. Then, a wavelet neural network (WNN) is utilized to establish a classification model of DM severity. The classification accuracy is 94.4 % for the testing blood samples. To enhance the classification accuracy, particle swarm optimization (PSO) and quantum-behaved particle swarm optimization (QPSO) are successively utilized to optimize WNN, and accuracy is enhanced to 98.4 % and 100 %, respectively. It is demonstrated from comparison between several algorithms that optoacoustic technology united with the QPSO-optimized WNN algorithm can achieve precise classification of DM with synthetic impacts.

Quantitative measurement of blood glucose influenced by multiple factors via photoacoustic technique combined with optimized wavelet neural networks

In this work, the photoacoustic (PA) quantitative measurement of blood glucose concentration (BGC) influenced by multiple factors was firstly investigated. A set of PA detection system of blood glucose considering the comprehensive influence of five factors was established. The PA signals and peak-to-peak values (PPVs) of 625 rabbit whole blood were obtained under 625 influence combinations. Due to the accurate measurement of BGC limited by the overlap PA signals, wavelet neural network (WNN) was utilized to train the PPVs of blood glucose for 500 rabbit blood. The mean square error (MSE) of BGC for 125 testing blood was approximately 6.5782 mmol/L. To decrease the MSE, the parameters of WNN were optimized by particle swarm optimization (PSO), that is, PSO-WNN algorithm was employed. Under the optimal parameters, MSE of BGC was decreased to approximately 0.48005 mmol/L. To further improve the prediction accuracy of BGC, an improved nonlinear dynamic inertia weight (NDIW) strategy of PSO was proposed, and compared with other two kinds of dynamic inertia weight strategies. Under the optimal parameters, the MSE of BGC was decreased to approximately 0.2635 mmol/L. The comparison of nine algorithms demonstrate that the PA technique combined with PSO-WNN and the improved NDIW strategy is significant in the quantitative measurement of blood glucose influenced by multiple factors.

Nanomedicine-Based Strategies for Diabetes: Diagnostics, Monitoring, and Treatment

Traditional methods for diabetes management require constant and tedious glucose monitoring (GM) and insulin injections, impacting quality of life. The global diabetic population is expected to increase to 439 million, with approximately US$490 billion in healthcare expenditures by 2030, imposing a significant burden on healthcare systems worldwide. Recent advances in nanotechnology have emerged as promising alternative strategies for the management of diabetes. For example, implantable nanosensors are being developed for continuous GM, new nanoparticle (NP)-based imaging approaches that quantify subtle changes in β cell mass can facilitate early diagnosis, and nanotechnology-based insulin delivery methods are being explored as novel therapies. Here, we provide a holistic summary of this rapidly advancing field compiling all aspects pertaining to the management of diabetes.

Monitoring of Pediatric Type 1 Diabetes

Regular self-monitoring of blood glucose levels, and ketones when indicated, is an essential component of type 1 diabetes (T1D) management. Although fingerstick blood glucose monitoring has been the standard of care for decades, ongoing rapid technological developments have resulted in increasingly widespread use of continuous glucose monitoring (CGM). This article reviews recommendations for self-monitoring of glucose and ketones in pediatric T1D with particular emphasis on CGM and factors that impact the accuracy and real-world use of this technology.

Investigation of the Accuracy of 18 Marketed Blood Glucose Monitors

OBJECTIVE

Cleared blood glucose monitors (BGMs) for personal use may not always deliver levels of accuracy currently specified by international and U.S. regulatory bodies. This study's objective was to assess the accuracy of 18 such systems cleared by the U.S. Food and Drug Administration representing approximately 90% of commercially available systems used from 2013 to 2015.

RESEARCH DESIGN AND METHODS

A total of 1,035 subjects were recruited to have a capillary blood glucose (BG) level measured on six different systems and a reference capillary sample prepared for plasma testing at a reference laboratory. Products were obtained from consumer outlets and tested in three triple-blinded studies. Each of the three participating clinical sites tested a different set of six systems for each of the three studies in a round-robin. In each study, on average, a BGM was tested on 115 subjects. A compliant BG result was defined as within 15% of a reference plasma value (for BG ≥100 mg/dL [5.55 mmol/L]) or within 15 mg/dL (0.83 mmol/L) (for BG <100 mg/dL [5.55 mmol/L]). The proportion of compliant readings in each study was compared against a predetermined accuracy standard similar to, but more lenient than, current regulatory standards. Other metrics of accuracy included the overall compliance proportion; the proportion of extreme outlier readings differing from the reference value by >20%; modified Bland-Altman analysis including average bias, coefficient of variation, and 95% limits of agreement; and proportion of readings with no clinical risk as determined by the Surveillance Error Grid.

RESULTS

The different accuracy metrics produced almost identical BGM rankings. Six of the 18 systems met the predetermined accuracy standard in all three studies, 5 systems met it in two studies, and 3 met it in one study. Four BGMs did not meet the accuracy standard in any of the three studies.

CONCLUSIONS

Cleared BGMs do not always meet the level of analytical accuracy currently required for regulatory clearance. This information could assist patients, professionals, and payers in choosing products and regulators in evaluating postclearance performance.

Managing diabetes at high altitude: personal experience with support from a Multidisciplinary Physical Activity and Diabetes Clinic

OBJECTIVE

Physical activity is important for well-being but can be challenging for people with diabetes. Data informing support of specialist activities such as climbing and high-altitude trekking are limited. A 42-year-old man with type 1 diabetes (duration 30 years) attended a Multidisciplinary Physical Activity and Diabetes Clinic planning to climb Mont Blanc during the summer and trek to Everest Base Camp in the autumn. His aims were to complete these adventures without his diabetes impacting on their success.

METHODS

We report the information provided that enabled him to safely facilitate his objectives, in particular, the requirement for frequent checking of blood glucose levels, the effects of altitude on insulin dose requirements, and recognition that acute mountain sickness may mimic the symptoms of hypoglycaemia and vice versa. Real-time continuous glucose monitoring was made available for his treks.

RESULTS

The effects of high altitude on blood glucose results and glycaemic variability while treated on multiple daily injections of insulin are reported. In addition, we present a first-person account of his experience and lessons learnt from managing diabetes at high altitude.

CONCLUSIONS

A dedicated Multidisciplinary Physical Activity and Diabetes Clinic delivering individualised, evidence-based, patient-focused advice on the effects of altitude on blood glucose levels, and provision of real-time continuous glucose monitoring enabled uneventful completion of a trek to Everest Base Camp in a person with type 1 diabetes.

Factory-Calibrated Continuous Glucose Sensors: The Science Behind the Technology

The use of commercially available continuous glucose monitors for diabetes management requires sensor calibrations, which until recently are exclusively performed by the patient. A new development is the implementation of factory calibration for subcutaneous glucose sensors, which eliminates the need for user calibrations and the associated blood glucose tests. Factory calibration means that the calibration process is part of the sensor manufacturing process and performed under controlled laboratory conditions. The ability to move from a user calibration to factory calibration is based on several technical requirements related to sensor stability and the robustness of the sensor manufacturing process. The main advantages of factory calibration over the conventional user calibration are: (a) more convenience for the user, since no more fingersticks are required for calibration and (b) elimination of use errors related to the execution of the calibration process, which can lead to sensor inaccuracies. The FreeStyle Libre^™ and FreeStyle Libre Pro^™ flash continuous glucose monitoring systems are the first commercially available sensor systems using factory-calibrated sensors. For these sensor systems, no user calibrations are required throughout the sensor wear duration.

Interferences and Limitations in Blood Glucose Self-Testing: An Overview of the Current Knowledge

In general, patients with diabetes performing self-monitoring of blood glucose (SMBG) can strongly rely on the accuracy of measurement results. However, various factors such as application errors, extreme environmental conditions, extreme hematocrit values, or medication interferences may potentially falsify blood glucose readings. Incorrect blood glucose readings may lead to treatment errors, for example, incorrect insulin dosing. Therefore, the diabetes team as well as the patients should be well informed about limitations in blood glucose testing. The aim of this publication is to review the current knowledge on limitations and interferences in blood glucose testing with the perspective of their clinical relevance.

Probable glucometer interference caused by topical iodine solution test site preparation

WHAT IS KNOWN AND OBJECTIVE

Use of disinfectants, such as alcohol prep pads, for test site preparation have demonstrated alterations in glucose readings. One case report details an overestimation of blood glucose (BG) readings when using Chemstrip bG and Visidex reagent test strips after cleaning test site with povidone-iodine swabs

CASE SUMMARY

We present a case of a clinically relevant probable drug-device interaction between topical iodine and a point-of-care glucometer in a 28 year old pregnant woman of Chinese descent. In this case, the use of 10% povidone-iodine solution on the testing site before lancing likely resulted in variable and inaccurate BG readings, which was not reproduced when the patient used hand washing instead of iodine.

WHAT IS NEW AND CONCLUSION

Our report expands on this prior knowledge by demonstrating that such an alteration associated with iodine can occur with modern electrochemical glucometers. In patients that have aberrant or variable BG readings, providers should investigate for improper testing technique.

[Accuracy and reliability between glucose meters: A study under normal clinical practice conditions]

INTRODUCTION

The glucose meters usually show a high accuracy, and in clinical practice, capillary and plasma glucose (PG) are used interchangeably. However, many variables can affect the validity of these devices. The aim of this study was to determine the accuracy and reliability of 3 glucose meters that are currently used in a primary care centre.

MATERIAL AND METHODS

A sample of venous blood and a drop of capillary blood were obtained from 59 participants. The drop was analysed in 3 glucose meters: 2 FreeStyle^® Optium (OP1 and OP2), and one Accu-Chek^® Aviva. The PG acted as the reference value, and the haematocrit and plasma levels of urea, bilirubin, uric acid and triglycerides were also analysed. We used the Passing-Bablok regression for accuracy and the intraclass correlation coefficient and the Bland-Altman method for reliability. The current American Diabetes Association standard of a total error of±5% was applied.

RESULTS

Differences in mean±standard deviation (mg/dL) and the systematic error were 5.8±7 and 5.8% (OP1); 6.2±8 and 5.9% (OP2); 8.3±8 and 6.3% (Accu-Chek^®). The OP1/OP2 pair showed the highest level of reliability, with an intraclass correlation coefficient=0.97, bias=-0.4mg/dL, and a width of the 95% limits of agreement of 28.6mg/dL. The highest levels of accuracy and reliability were observed in high glucose ranges (PG≥126mg/dL).

CONCLUSIONS

Despite their clinically acceptable mean difference compared to the PG, the 3 glucose meters did not fulfill the current American Diabetes Association standard. The regular performance of quality control tests of these devices is recommended.

Accuracy Evaluation of Four Blood Glucose Monitoring Systems in Unaltered Blood Samples in the Low Glycemic Range and Blood Samples in the Concentration Range Defined by ISO 15197

INTRODUCTION

Systems for self-monitoring of blood glucose (SMBG) are expected to be accurate enough to provide reliable measurement results. Especially in the low glycemic range, adequate therapeutic decisions based on reliable results can alleviate complications associated with hypoglycemia.

MATERIALS AND METHODS

The accuracy of four SMBG systems (system 1 was the ACCU-CHEK(®) Aviva [Roche Diagnostics GmbH, Mannheim, Germany], system 2 was the Contour(®) XT [Bayer Consumer Care AG, Basel, Switzerland], system 3 was the GlucoCheck XL [aktivmed GmbH, Augsberg, Germany], and system 4 was the GlucoMen(®) LX PLUS [A. Menarini Diagnostics S.r.l., Florence, Italy]) with three test-strip lots each was evaluated by calculating mean absolute relative differences (MARDs). Two datasets were evaluated: (1) 100 samples with blood glucose concentrations <70 mg/dL and (2) 100 samples distributed following International Organization for Standardization (ISO) standard 15197. Each sample was measured twice with each test-strip lot of each SMBG system. Comparison measurement results were obtained with a glucose oxidase method and a hexokinase method, both traceable according to ISO 17511. Analysis of variance of the MARD between the SMBG system and the comparison method was performed.

RESULTS

MARD values ranged from 4.4% to 13.4% (<70 mg/dL) and 4.8% to 8.9% (ISO 15197-distributed) and differed significantly, with systems 1 and 2 showing lower MARDs than systems 3 and 4. MARD values deviated by up to 2.5% (corresponding to a relative deviation of approximately 40%) between the two comparison methods.

CONCLUSIONS

The investigated SMBG systems showed a significant variation of accuracy (measured by MARD), especially with higher MARD values in the low glycemic range. The selected comparison method had an impact on the MARD and therefore on the apparent accuracy of the SMBG systems. Sufficient measurement accuracy in the low glycemic range is required to enable users to react adequately to hypoglycemia.

Managing diabetes with nanomedicine: challenges and opportunities

Nanotechnology-based approaches hold substantial potential for improving the care of patients with diabetes. Nanoparticles are being developed as imaging contrast agents to assist in the early diagnosis of type 1 diabetes. Glucose nanosensors are being incorporated in implantable devices that enable more accurate and patient-friendly real-time tracking of blood glucose levels, and are also providing the basis for glucose-responsive nanoparticles that better mimic the body's physiological needs for insulin. Finally, nanotechnology is being used in non-invasive approaches to insulin delivery and to engineer more effective vaccine, cell and gene therapies for type 1 diabetes. Here, we analyse the current state of these approaches and discuss key issues for their translation to clinical practice.