Investigation of the Effect of 70 Potential Interferents on Measurement Results of Two Blood Glucose Monitoring Systems.

BACKGROUND: Reliable blood glucose (BG) measurements are important for people with diabetes to manage their therapy as well as in point-of-care testing (POCT) performed by health care professionals to monitor BG of patients or even to diagnose diabetes. Among other factors, endogenous and exogenous substances present in blood samples can impact the measurement results. To ensure and prove that blood glucose monitoring systems (BGMSs) are robust in terms of potential interferents, manufacturers have to perform extensive evaluations. METHOD: An interference screening test was performed for three reagent system lots of a POCT system and of a BGMS for self-monitoring of BG. A paired-difference approach based on ISO 15197:2013 and CLSI guideline EP07 was used with venous whole blood samples at two different glucose concentrations. Seventy potential interferents expected to be common in people with diabetes were evaluated. RESULTS: The interference effects were determined as normalized biases between test samples and corresponding control samples. For 69 of the 70 investigated potential interferents, both systems met the predefined acceptance criteria, with the normalized biases falling within ±10 mg/dL or ±10% at glucose concentrations ≤100 mg/dL or >100 mg/dL, respectively, for each of the three evaluated reagent system lots. CONCLUSIONS: The BGMS investigated in this study were found to be robust with respect to the 70 evaluated potential interferents. Interference effects were observed only for N-Acetyl-L-cysteine. Extensive evaluations of potential interfering factors can make an important contribution to ensure reliability of BGMS.

Evaluation of System Accuracy, Precision, Hematocrit Influence, and User Performance of Two Blood Glucose Monitoring Systems Based on ISO 15197:2013/EN ISO 15197:2015.

INTRODUCTION: Sufficiently high analytical quality of blood glucose monitoring systems (BGMS) is a prerequisite for efficient diabetes therapy. In this study we assessed system accuracy, measurement repeatability, intermediate measurement precision, user performance, and the influence of hematocrit on two CE-marked blood glucose monitoring systems. For one BGMS, measurement accuracy using venous samples was additionally investigated. METHODS: Study procedures were based on the International Organization of Standardization (ISO) 15197:2013/EN ISO 15197:2015 ("ISO 15197"). User performance included data from 100 subjects who used one test strip lot, whereas for all other analyses three different reagent system lots were used. For system accuracy assessment, 100 capillary samples were measured in duplicate with each of three reagent system lots per system, resulting in 600 results per system. RESULTS: CareSens S Fit and CareSens H Beat both fulfilled the ISO 15197 accuracy criteria with 97.5-100% of each test strip lot's results falling within ± 15 mg/dL or ± 15% of the results of the comparison method and 100% of results in consensus error grid (CEG) zone A for all three lots. User performance evaluation revealed sufficient accuracy in the hands of lay users although some handling errors were documented by study staff. Assessment of measurement repeatability and intermediate measurement precision is given by standard deviation (SD) (glucose levels < 100 mg/dL) and by coefficient of variation (CV) (glucose concentrations ≥ 100 mg/dL). SD was ≤ 4.1 mg/dL and CV ≤ 4.2% for measurement repeatability and SD was ≤ 2.2 mg/dL and CV ≤ 2.6% for intermediate measurement precision. In case of hematocrit influence, both BGMS complied with all three tested lots with the defined criteria. CONCLUSION: Both BGMS analyzed in this study fulfilled the required accuracy criteria of ISO 15197. They showed high precision, good performance in the hands of lay users, and the influence of hematocrit was acceptable in the labeled range.

Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy.

In diabetes prevention and care, invasiveness of glucose measurement impedes efficient therapy and hampers the identification of people at risk. Lack of calibration stability in non-invasive technology has confined the field to short-term proof of principle. Addressing this challenge, we demonstrate the first practical use of a Raman-based and portable non-invasive glucose monitoring device used for at least 15 days following calibration. In a home-based clinical study involving 160 subjects with diabetes, the largest of its kind to our knowledge, we find that the measurement accuracy is insensitive to age, sex, and skin color. A subset of subjects with type 2 diabetes highlights promising real-life results with 99.8% of measurements within A + B zones in the consensus error grid and a mean absolute relative difference of 14.3%. By overcoming the problem of calibration stability, we remove the lingering uncertainty about the practical use of non-invasive glucose monitoring, boding a new, non-invasive era in diabetes monitoring.

User Performance Evaluation and System Accuracy Assessment of Four Blood Glucose Monitoring Systems With Color Coding of Measurement Results.

BACKGROUND: Blood glucose monitoring systems (BGMSs) are a cornerstone in diabetes management. They have to provide sufficiently accurate results in the hands of lay users, particularly in insulin-treated patients. The aim of this study was user performance evaluation and system accuracy assessment of four BGMSs with color coding of results. METHODS: Study procedures were based on ISO 15197:2013. User performance evaluation included data from 100 participants, each of whom used every system with one reagent lot. Study personnel observed user techniques. For the system accuracy assessment, 100 capillary samples were obtained for measurement in duplicate with each of three reagent system lots per system, resulting in 600 results per system. RESULTS: All assessed BGMSs exhibited a sufficient level of accuracy, with small differences between them. In the user performance evaluation, study personnel observed the smallest total number of user errors with Contour Next (Ascensia), followed by Accu-Chek Instant (Roche), Medisafe Fit Smile (Terumo), and OneTouch Ultra Plus Reflect (LifeScan). Approximately 90% of participants stated that a consistent color scheme, eg, for low blood glucose (BG) values, should be used across all BGMSs. There was no clear preference among the four tested BGMSs regarding the specific way of displaying color coding. CONCLUSIONS: The four BGMSs assessed in this study showed only small differences in an overall sufficient level of accuracy. User handling errors, as observed by study personnel, differed between the systems.

Continuous Glucose Profiles in Healthy People With Fixed Meal Times and Under Everyday Life Conditions.

BACKGROUND: The increased use of continuous glucose monitoring (CGM) and automated insulin delivery systems raises the question about therapeutic targets for glucose profiles in people with diabetes. This study aimed to assess averaged pre- and postprandial glucose profiles in people without diabetes to provide guidance for normal glucose patterns in clinical practice. For that, number and timing of meal intake were predefined. MATERIAL AND METHODS: To assess glucose traces in 36 participants without diabetes (mean age = 23.7 ± 5.7 years), CGM was performed for up to 14 days, starting with a run-in phase (first 3 days, excluded from analysis) followed by 4 days with fixed meal times at 8:00 am, 1:00 pm, and 6:00 pm and the remaining 7 days spent under everyday life conditions. Data from two simultaneously worn CGM sensors were averaged and adjusted to capillary plasma-equivalent glucose values. Glucose data were evaluated through descriptive statistics. RESULTS: Median glucose concentration on days with fixed meal times and under everyday life conditions was 95.0 mg/dL (91.6-99.1 mg/dL, interquartile range) and 98.1 mg/dL (93.7-100.8 mg/dL), respectively. On days with fixed meal times, mean premeal glucose was 92.8 ± 9.4 mg/dL, and mean peak postmeal glucose was 143.3 ± 23.5 mg/dL. CONCLUSIONS: By defining the time of meal intake, a clear pattern of distinct postprandial glucose excursions in participants without diabetes could be demonstrated and analyzed. The presented glucose profiles might be helpful as an estimate for adequate clinical targets in people with diabetes.

Mean Absolute Relative Difference of Blood Glucose Monitoring Systems and Relationship to ISO 15197.

BACKGROUND: The analytical quality of a blood glucose monitoring system (BGMS) is often assessed according to the requirements described in the international standard ISO 15197. However, the mean absolute relative difference (MARD) is sometimes used as well. This analysis aims at providing empirical data from BGMS evaluation studies conducted according to ISO 15197 and at providing an estimation of how MARD and percentage of measurement results within ISO accuracy limits are related. METHODS: Results of 77 system accuracy evaluations conducted according to ISO 15197 were used to calculate MARD between BGMS and a laboratory comparison method's results (glucose oxidase or hexokinase method). Additionally, bias and 95%-limits of agreement (LoA) using the Bland and Altman method were calculated. RESULTS: MARD results ranged from 2.3% to 20.5%. The lowest MARD of a test strip lot that showed <95% of results within ISO limits was 6.1%. The distribution of MARD results shows that only 3.6% of test strip lots with a MARD equal to or below 7% showed <95% of results within ISO limits (2.2% of all test strip lots). Bias of test strip lots that showed ≥95% of results within the limits ranged from -10.3% to +7.4%. The half-width of the 95%-LoA of test strip lots that showed ≥95% of results within the limits ranged from 4.8% to 24.0%. CONCLUSION: There is a threshold MARD that may allow an estimate whether ISO 15197 requirements are fulfilled, but this statement cannot be made with certainty.

Impact of Two Different Reference Measurement Procedures on Apparent System Accuracy of 18 CE-Marked Current-Generation Blood Glucose Monitoring Systems.

BACKGROUND: Measurement accuracy has been assessed for many different blood glucose monitoring systems (BGMS) over the years by different study groups. However, the choice of the comparison measurement procedure may impact the apparent level of accuracy found in such studies. MATERIALS AND METHODS: Measurement accuracy of 18 different BGMS was assessed in a setting based on ISO 15197 using two different comparison methods in parallel: a glucose oxidase (GOD)-based and a hexokinase (HK)-based method. Accuracy limits of ISO 15197 were applied, and additional analyses were performed, including bias, linear regression, and mean absolute relative difference (MARD) to assess the impact of possible differences between comparison methods on the apparent level of accuracy. RESULTS: While ≈80% of BGMS met the accuracy criteria of ISO 15197 when compared with the respective manufacturers' reference measurement procedure, only two-thirds did so against both comparison methods. The mean relative bias ranged from -6.6% to +5.7% for the analysis against the GOD-based method and from -11.1% to +1.3% for the analysis against the HK-based method, whereas MARD results ranged from 3.7% to 9.8% and from 2.3% to 10.5%, respectively. Results of regression analysis showed slopes between 0.85 and 1.08 (GOD-based method) and between 0.81 and 1.01 (HK-based method). CONCLUSIONS: The results of this study indicate that there are systematic differences between the reference measurement procedures used for BGMS calibration as well as for system accuracy assessment. Because of the potential impact on therapy of patients with diabetes resulting from these differences, further steps toward harmonization of the measurement procedures' results are important.

Choice of Continuous Glucose Monitoring Systems May Affect Metrics: Clinically Relevant Differences in Times in Ranges.

BACKGROUND: Continuous glucose monitoring-derived parameters are becoming increasingly important in the treatment of people with diabetes. The aim of this study was to assess whether these parameters, as calculated from different continuous glucose monitoring systems worn in parallel, are comparable. In addition, clinical relevance of differences was investigated. METHODS: A total of 24 subjects wore a FreeStyle Libre (A) and a Dexcom G5 (B) sensor in parallel for 7 days. Mean glucose, coefficient of variation, glucose management indicator and time spent in different glucose ranges were calculated for each system. Pairwise differences between the two different continuous glucose monitoring systems were computed for these metrics. RESULTS: On average, the two CGM systems indicated an identical time in range (67.9±10.2 vs. 67.9±11.5%) and a similar coefficient of variation; both categorized as unstable (38.1±5.9 vs. 36.0±4.8%). In contrast, the mean time spent below and above range, as well as the individual times spent below, in and above range differed substantially. System A indicated about twice the time spent below range than system B (7.7±7.2 vs. 3.8±2.7%, p=0.003). This could have led to different therapy recommendations in approximately half of the subjects. DISCUSSION: The differences in metrics found between the two continuous glucose monitoring systems may result in different therapy recommendations. In order to make adequate clinical decisions, measurement performance of CGM systems should be standardized and all available information, including the HbA1c, should be utilized.

Evaluation of Meal Carbohydrate Counting Errors in Patients with Type 1 Diabetes.

AIM: Correct estimation of meal carbohydrate content is a prerequisite for successful intensified insulin therapy in patients with diabetes. In this survey, the counting error in adult patients with type 1 diabetes was investigated. METHODS: Seventy-four patients with type 1 diabetes estimated the carbohydrate content of 24 standardized test meals. The test meals were categorized into 1 of 3 groups with different carbohydrate content: low, medium, and high. Estimation results were compared with the meals' actual carbohydrate content as determined by calculation based on weighing. A subgroup of the participants estimated the test meals for a second (n=35) and a third time (n=22) with a mean period of 11 months between the estimations. RESULTS: During the first estimation, the carbohydrate content was underestimated by -28% (-50, 0) of the actual carbohydrate content. Particularly meals with high mean carbohydrate content were underestimated by -34% (-56, -13). Median counting error improved significantly when estimations were performed for a second time (p<0.001). CONCLUSIONS: Participants generally underestimated the carbohydrate content of the test meals, especially in meals with higher carbohydrate content. Repetition of estimation resulted in significant improvements in estimation accuracy and is important for the maintenance of correct carbohydrate estimations. The ability to estimate the carbohydrate content of a meal should be checked and trained regularly in patients with diabetes.

Time in Specific Glucose Ranges, Glucose Management Indicator, and Glycemic Variability: Impact of Continuous Glucose Monitoring (CGM) System Model and Sensor on CGM Metrics.

BACKGROUND: International consensus recommends a set of continuous glucose monitoring (CGM) metrics to assess quality of diabetes therapy. The impact of individual CGM sensors on these metrics has not been thoroughly studied yet. This post hoc analysis aimed at comparing time in specific glucose ranges, coefficient of variation (CV) of glucose concentrations, and glucose management indicator (GMI) between different CGM systems and different sensors of the same system. METHOD: A total of 20 subjects each wore two Dexcom G5 (G5) sensors and two FreeStyle Libre (FL) sensors for 14 days in parallel. Times in ranges, GMI, and CV were calculated for each 14-day sensor experiment, with up to four sensor experiments per subject. Pairwise differences between different sensors of the same CGM system as well as between sensors of different CGM system were calculated for these metrics. RESULTS: Pairwise differences between sensors of the same model showed larger differences and larger variability for FL than for G5, with some subjects showing considerable differences between the two sensors. When pairwise differences between sensors of different CGM models were calculated, substantial differences were found in some subjects (75th percentiles of differences of time spent <70 mg/dL: 5.0%, time spent >180 mg/dL: 9.2%, and GMI: 0.42%). CONCLUSION: Relevant differences in CGM metrics between different models of CGM systems, and between different sensors of the same model, worn by the same study subjects were found. Such differences should be taken into consideration when these metrics are used in the treatment of diabetes.

Proof of Concept for a New Raman-Based Prototype for Noninvasive Glucose Monitoring.

BACKGROUND: Noninvasive glucose monitoring (NIGM) in diabetes is a long-sought-for technology. Among the many attempts Raman spectroscopy was considered as the most promising because of its glucose specificity. In this study, a recently developed prototype (GlucoBeam, RSP Systems A/S, Denmark) was tested in patients with type 1 diabetes to establish calibration models and to demonstrate proof of concept for this device in real use. METHODS: The NIGM table-top prototype was used by 15 adult subjects with type 1 diabetes for up to 25 days at home and in an in-clinic setting. On each day, the subjects performed at least six measurement units throughout the day. Each measurement unit comprised two capillary blood glucose measurements, two scans with an intermittent scanning continuous glucose monitoring (CGM) system, and two NIGM measurements using the thenar of the subject's right hand. RESULTS: Calibration models were established using data from 19 to 24 days. The remaining 3-8 days were used for independent validation. The mean absolute relative difference of the NIGM prototype was 23.6% ± 13.1% for the outpatient days, 28.2% ± 9.9% for the in-clinic day, and 26.3% ± 10.8% for the complete study. Consensus error grid analysis of the NIGM prototype for the complete study showed 93.6% of values in clinically acceptable zones A and B. CONCLUSIONS: This proof of concept study demonstrated a practical realization of a Raman-based NIGM device, with performance on par with early-generation CGM systems. The findings will assist in further performance improvements of the device.

Skin Reaction Report Form: Development and Design of a Standardized Report Form for Skin Reactions Due to Medical Devices for Diabetes Management.

BACKGROUND: Skin reactions due to medical devices for diabetes management have become a common problem in diabetes technology. There is a varying degree in how detailed skin reactions are described in scientific literature and diabetes practice, and no uniform structured documentation is given. Whereas most articles only describe findings, some others already document final diagnoses, such as contact dermatitis. Furthermore, inconsistent wordings for comparable issues were used. METHODS: A more detailed and standardized documentation, possibly facilitated by a generally accepted guideline for structured descriptions, of skin reactions could be helpful to enable better differentiations between the described skin reactions. Therefore, a report form to assess skin reactions due to medical devices in diabetes therapy was developed and will be presented in this article. RESULTS: The one-page report form is divided into four categories and a separate instruction paper. Beside general information the form includes the location, size, severity and duration of skin appearances, the grading of itching, and suspected diagnoses. CONCLUSION: A consistent use of the form in daily practice and clinical trials could facilitate a fast and standardized documentation and help to evaluate the occurrence and severity of different skin reactions due to medical devices in diabetes management.

System accuracy evaluation of 18 CE-marked current-generation blood glucose monitoring systems based on EN ISO 15197:2015.

OBJECTIVE: Accuracy of 18 current-generation blood glucose monitoring systems (BGMS) available in Europe was evaluated applying criteria adapted from EN ISO 15197:2015 with one reagent system lot. BGMS were selected based on market research data. RESEARCH DESIGN AND METHODS: The BGMS ABRA, Accu-Chek Guide, AURUM, CareSens Dual, CERA-CHEK 1CODE, ContourNext One, eBsensor, FreeStyle Freedom Lite, GL50 evo, GlucoCheck GOLD, GlucoMen areo 2K, GluNEO, MyStar DoseCoach, OneTouch Verio Flex, Pic GlucoTest, Rightest GM700S, TRUEyou, and WaveSense JAZZ Wireless were tested using capillary blood from 100 different subjects and assessing the percentage of results within ±15 mg/dL (0.83 mmol/L) or 15% of comparison method results for BG concentrations below or above 100 mg/dL (5.55 mmol/L), respectively. In addition, the minimal deviation from comparison method results within which ≥95% of results of the respective BGMS were found was calculated. RESULTS: In total, 14 BGMS had ≥95% of results within ±15 mg/dL (0.83 mmol/L) or ±15% and 3 BGMS had ≥95% of results within ±10 mg/dL (0.55 mmol/L) or ±10% of the results obtained with the comparison method. The smallest deviation from comparison method results within which ≥95% of results were found was ±7.7 mg/dL (0.43 mmol/L) or ±7.7%; the highest deviation was ±19.7 mg/dL (1.09 mmol/L) or ±19.7%. CONCLUSIONS: This accuracy evaluation shows that not all CE-labeled BGMS fulfill accuracy requirements of ISO 15197 reliably and that there is considerable variation even among BGMS fulfilling these criteria. This safety-related information should be taken into account by patients and healthcare professionals when making therapy decisions. TRIAL REGISTRATION NUMBER: NCT03737188.

Measurement accuracy of two professional-use systems for point-of-care testing of blood glucose.

Background The professional-use systems HemoCue® Glucose 201+ (HC201+) and HemoCue® Glucose 201 RT (HC201RT) are widely used for point-of-care testing (POCT) of blood glucose (BG). HC201RT utilizes unit-use microcuvettes which can be stored at room temperature, whereas HC201+ microcuvettes have to be stored at <8 °C. In this study, system accuracy of HC201+ and HC201RT was evaluated using capillary and venous blood samples. Methods For each system, two reagent system lots were evaluated within a period of 2 years based on testing procedures of ISO 15197:2013, a standard applicable for self-monitoring of blood glucose (SMBG) systems. For each reagent system lot, the investigation was performed by using 100 capillary and 95 to 99 venous blood samples. Comparison measurements were performed with a hexokinase laboratory method. Accuracy criteria of ISO 15197:2013 and POCT12-A3 were applied. In addition, bias was analyzed according to Bland and Altman, and error grid analysis was performed. Results When measuring capillary samples, both systems fulfilled accuracy requirements of ISO 15197:2013 and POCT12-A3 with the investigated reagent system lots. When measuring venous samples, only HC201+ fulfilled these requirements. Bias between HC201+ and reference measurements was more consistent over venous and capillary samples and microcuvette lots than for HC201RT. Error grid analysis showed that clinical actions might have been different depending on which system was used. Conclusions In this study, HC201+ showed a high level of accuracy irrespective of the sample type (capillary or venous). In contrast, HC201RT measurement results were markedly affected by the type of sample.

Proof of Concept Study to Assess the Influence of Oxygen Partial Pressure in Capillary Blood on SMBG Measurements.

BACKGROUND: Measurement results provided by blood glucose monitoring systems (BGMS) can be affected by various influencing factors. For some BGMS using glucose oxidase (GOx)-based test strips, one of these factors is the oxygen partial pressure (pO2) of the applied blood sample. Because assessing the potential influence of pO2 when measuring capillary blood samples is not straight-forward, we performed a proof of concept study. METHOD: Influence of pO2 was investigated for two GOx-based BGMS (BGMS A and B). Measurement results of the GOx-based BGMS were compared with measurement results from a pO2-independent BGMS (BGMS C). A total of 119 samples from 60 subjects were measured, twice with BGMS C, then 6 times each with BGMS A and BGMS B or vice versa, and again twice with BGMS C. Immediately afterward, pO2 was determined. Linear regression analysis based on relative differences between results from BGMS A or BGMS B and results from BGMS C was performed to estimate the degree of pO2 influence. RESULTS: The relative bias between the lowest and highest pO2 values differed by 14.3% for BGMS A, indicating a pO2 influence that might be clinically relevant, and by 9.7% for BGMS B, indicating that pO2 influence may be too small to be reliably detected because of the BGMS' imprecision. CONCLUSIONS: This proof of concept study showed that with the procedures used, a potentially clinically relevant influence of pO2 in capillary blood samples on GOx-based BGMS could be detected. Further larger-scale studies are needed to verify this influence.

Accuracy of five systems for self-monitoring of blood glucose in the hands of adult lay-users and professionals applying ISO 15197:2013 accuracy criteria and potential insulin dosing errors.

OBJECTIVE: In this study, accuracy in the hands of intended users was evaluated for five self-monitoring of blood glucose (SMBG) systems based on ISO 15197:2013, and possibly related insulin dosing errors were calculated. In addition, accuracy was assessed in the hands of study personnel. METHODS: For each system (Accu-Chek 1 Aviva Connect [A], Contour 2 Next One [B], FreeStyle Freedom Lite 3 [C], GlucoMen 4 areo [D] and OneTouch Verio 5 [E]) one test strip lot was evaluated as required by ISO 15197:2013, clause 8. Number and percentage of SMBG measurements within ±15 mg/dl and ±15% of the comparison measurements at glucose concentrations <100 mg/dl and ≥100 mg/dl, respectively, were calculated. In addition, data is presented in surveillance error grids, and insulin dosing errors were modeled. The study was registered at ClinicalTrials.gov (NCT03033849). RESULTS: Four systems (A, B, C, D) fulfilled the tested reagent system lot ISO 15197:2013 accuracy criteria with the tested reagent system lot with at least 95% (lay-users) and 99.5% (study personnel) of results within the defined limits. Measurements with all five systems were within the clinically acceptable zones of the consensus error grid and the surveillance error grid. Median modeled insulin dosing errors were between -0.8 and +0.6 units for measurements performed by lay-users and between -0.7 and +0.8 units for study personnel. Frequent lay-user errors were not checking the test strips' expiry date, applying blood incorrectly and handling the device incorrectly. CONCLUSION: In this study, the systems showed slight differences in the number of results within ISO 15197:2013 accuracy limits. Inaccurate SMBG measurements can result in insulin dosing errors and adversely affect glycemic control.

Evaluation of Analytical Performance of Three Blood Glucose Monitoring Systems: System Accuracy, Measurement Repeatability, and Intermediate Measurement Precision.

INTRODUCTION: Blood glucose monitoring systems (BGMS) should provide sufficient analytical quality to allow adequate therapy for diabetes patients. Besides system accuracy, measurement precision is an important aspect of a BGMS' analytical quality. METHODS: Based on ISO 15197:2013/EN ISO 15197:2015, system accuracy, measurement repeatability, and intermediate measurement precision were assessed. ISO 15197:2013 system accuracy criteria require that ⩾95% of individual BGMS' test strip lot results shall fall within ±15 mg/dl or ±15% of corresponding comparison method results (at glucose concentrations <100 mg/dl and ⩾100 mg/dl, respectively), and that ⩾99% of results fall within consensus error grid (CEG) zones A and B. Measurement repeatability was assessed using venous blood samples, whereas intermediate measurement precision was assessed using control solution samples. Standard deviation (SD) and coefficient of variation (CV) were calculated for glucose concentrations <100 mg/dl and ⩾100 mg/dl, respectively. Precision acceptance criteria are not specified by ISO 15197:2013. RESULTS: All three BGMS fulfilled system accuracy criteria with 96% to 98% of individual test strip lot's results falling within the acceptable accuracy limits. All measurement results fell within CEG zones A and B. For measurement repeatability, SD was ⩽3.3 mg/dl, and CV was ⩽3.9% for the investigated BGMS. Assessment of intermediate measurement precision showed SD ⩽1.3 mg/dl and CV ⩽3.0%. CONCLUSION: All three BGMS fulfilled system accuracy criteria of ISO 15197:2013. In absence of acceptance criteria, precision results were found to be consistent with the manufacturer's labeling of the investigated devices.

Assessment of System Accuracy, Intermediate Measurement Precision, and Measurement Repeatability of a Blood Glucose Monitoring System Based on ISO 15197.

BACKGROUND: Analytical quality of blood glucose monitoring systems (BGMS) is an important aspect for many diabetes patients. Sufficiently high analytical quality is required for adequate diabetes therapy. METHODS: In this study, system accuracy and measurement precision of a BGMS were assessed based on ISO 15197:2013. For system accuracy, this standard requires a specific glucose distribution and at least 95% of results obtained with the BGMS in capillary blood to fall within ±15 mg/dl or ±15% (at glucose concentrations <100 mg/dl or ≥100 mg/dl, respectively) of corresponding comparison method results, and at least 99% of results to be found within clinically acceptable consensus error grid (CEG) zones A and B. Based on ISO 15197:2013, intermediate measurement precision, using control solution, and measurement repeatability, using venous blood samples, were analyzed by calculation of standard deviations (SDs) and coefficients of variation (CV) at glucose concentrations <100 mg/dl or ≥100 mg/dl, respectively, although ISO 15197:2013 does not specify acceptance criteria. RESULTS: The BGMS fulfilled system accuracy requirements with ≥99% of results within ±15 mg/dl or ±15% of the comparison method results, and 100% of results in CEG zones A and B. Intermediate measurement precision analysis showed SD ≤2.2 mg/dl and CV ≤2.3%. Analysis of measurement repeatability showed SD ≤2.1 mg/dl and CV ≤2.4%. CONCLUSION: System accuracy requirements of ISO 15197:2013 were fulfilled by the BGMS. As ISO 15197:2013 does not specify precision requirements, precision analysis results were compared with those reported for other BGMS in the literature and found to be similar.