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Abstract

To assess the accuracy and precision of the five currently available blood glucose meters in Australia. Control solutions from manufacturers were used to determine the precision for each meter. Glucose levels in capillary blood samples from 49 patients attending a diabetes clinic were measured with each meter and with a laboratory reference method. The coefficient of variation was calculated to determine precision. Bias, Error Grid analysis, and Bland-Altman plots were used to determine accuracy. The CVs of most meters were acceptable at <5%. Bias ranged from 4.0 to 15.5% with only 1 meter satisfying the American Diabetes Association recommendation of <5% bias. Error Grid analysis showed that 94-100% of readings were clinically accurate, and that none of the differences from the reference method would lead to clinical errors. Bland-Altman plots showed that for two meters the magnitude of the difference between the meter and the reference method increased with increasing glucose values, but did not change significantly with glucose level for the other 3 meters. Currently available blood glucose meters show acceptable precision, and any errors (with respect to a laboratory method) are highly unlikely to lead to clinical errors. However, only the CareSens meter achieved a bias of less than 5%.

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... The accuracy of each glucometers was calculated according to different international accuracy standards. The summary of standards is shown in the Table 2 [9][10][11][12][13][14][15]. ...
... The error grid is a generally accepted method of assessing the clinical acceptability of a glucometer result as a function of its deviation from a laboratory reference standard. [9,10,[13][14][15][16][17][18][19][20][21]. ...
... To analyse the difference between the glucometer value and laboratory reference value, and thereby estimate the bias of the glucometer, the Bland-Altman technique was used [9,10,13,[22][23][24]. ...
Article
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In this study, we report on the accuracy, precision and clinical acceptability of the five blood glucose meters available in India. Glucose levels of 100 blood samples were measured with each meter, at IISc health centre laboratory under same conditions and the results were compared with laboratory reference standard. In order to calculate the coefficient of variation (CV), each sample was tested three times. None of the glucometer showed 100 % compliance on CV measure. In terms of accuracy, none of the glucometer satisfied the most stringent ADA-1994 standard. In general all the glucometers showed improved accuracy with respect to the most relaxed ISO 1597:2003 standard. The Clarke error grid analysis was performed to assess the clinical acceptability of the glucometers. All five glucometers had more than 90 % of test results in Zone A and B. Bland–Altman analysis indicates that all glucometers show a positive bias, indicating that the measured values tend to be higher than the laboratory reference standard.
... Recently, researchers have begun to use self-monitoring blood glucose meter (SMBG) to determine GI value of food202122, because they are convenient, inexpensive, little blood sample (<5 µl) and very short testing time (<30 s) required to give a result. Although studies have evaluated the accuracy and performance of SMBG for measuring blood glucose concentration in diabetic patients21222324, it may not applicable in the determination of glycemic responses (expressed as IAUC), GI values and thus rank GI value of food in healthy subjects. Therefore, the purpose of this study is to evaluate the performance of three different SMBGs to measure IAUC, and GI value of food in healthy subjects and compared the classifications of GI values obtained from SMBG and laboratory biochemical analyzer. ...
... It is likely that error variation increased as GI value of food is increased in three glucose meters. We further use recommended method to classify the results of GI value as high, medium and low GI [23]. AllTable 3. Incremental area under the curve of test foods and white bread as determined by FAA, OGM, BGM and AGM* * Means ± SEM. ...
... This explained that the GI value of food is related to the postprandial glucose responses of food [26,3031. Moreover, this result appears to be similar to the reported information that OGM tends to has greater glucose reading than AGM [23, 32]. Among three glucose meters, AGM gave the largest variance than FAA and two glucose meters (BGM and AGM). ...
Article
THE STUDY EVALUATED AND COMPARED THE DIFFERENCES OF GLUCOSE RESPONSES, INCREMENTAL AREA UNDER CURVE (IAUC), GLYCEMIC INDEX (GI) AND THE CLASSIFICATION OF GI VALUES BETWEEN MEASURED BY BIOCHEMICAL ANALYZER (FUJI AUTOMATIC BIOCHEMISTRY ANALYZER (FAA)) AND THREE GLUCOSE METERS: Accue Chek Advantage (AGM), BREEZE 2 (BGM), and Optimum Xceed (OGM). Ten healthy subjects were recruited for the study. The results showed OGM yield highest postprandial glucose responses of 119.6 +/- 1.5, followed by FAA, 118.4 +/- 1.2, BGM, 117.4 +/- 1.4 and AGM, 112.6 +/- 1.3 mg/dl respectively. FAA reached highest mean IAUC of 4156 +/- 208 mg x min/dl, followed by OGM (3835 +/- 270 mg x min/dl), BGM (3730 +/- 241 mg x min/dl) and AGM (3394 +/- 253 mg x min/dl). Among four methods, OGM produced highest mean GI value than FAA (87 +/- 5) than FAA, followed by BGM and AGM (77 +/- 1, 68 +/- 4 and 63 +/- 5, p<0.05). The results suggested that the AGM, BGM and OGM are more variable methods to determine IAUC, GI and rank GI value of food than FAA. The present result does not necessarily apply to other glucose meters. The performance of glucose meter to determine GI value of food should be evaluated and calibrated before use.
... Pairedsample t-test was used to compare the mean difference between reference values and glucometer values; then the percentage bias was calculated as follows: (glucometer reading-reference value) × 100 ÷ reference value [13]. This was compared to the American Diabetes Association (ADA) standard of a bias of < 5% being acceptable [14,15]. The agreement between the two measurements (that is, the glucometer and reference readings) at any given level was then examined using Bland-Altman plots [16]. ...
... zone C (results given by the glucometer would begin to lead to treatment decisions opposite to those based on reference blood glucose levels), zone D (results given by the glucometer lead to a failure to detect and treat errors) and zone E (glucometer-generated results fail to identify hypoglycaemia or hyperglycaemia. Values given by the glucometers are opposite to the reference values resulting in corresponding treatment decisions opposite to those needed)[15,17,18]. For perfect accuracy, 95% of values should be in zone A, 5% in zone B, and 0% in other zones. ...
Article
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Introduction: capillary glucose measurement using point-of-care glucometers is an essential part of diabetes care. We determined the technical accuracy, clinical accuracy and precision of commonly available glucometers against standard spectrophotometry in Cameroon. Methods: a sample of four glucometers was selected. In the 108 diabetic and non-diabetic participants, blood glucose values obtained by glucometers were compared to the reference laboratory method to determine their technical and clinical accuracies. Precision was determined by repeated measurements using standard solutions of different concentrations. Results: accu-Chek® Active, CodeFree™, Mylife™ Pura™ and OneTouch® Ultra® 2 values had correlation coefficients of 0.96, 0.87, 0.97 and 0.94 respectively with reference values, and biases of 18.7%, 29.1%, 16.1% and 13.8% respectively. All glucometers had ≥ 95% of values located within the confidence limits except OneTouch® Ultra®2. Accu-Chek® Active, CodeFree™, Mylife™ Pura™ and OneTouch® Ultra® 2 had 99%, 93.1%, 100% and 98.0% of values in Parke's zones A and B. The coefficients of variation of the glucometers were all below 5% at all standard concentrations, except for Accu-Chek® Active for glucose concentrations at100 and 200mg/dL. Conclusion: no glucometer met all the international recommendations for technical accuracy. Accu-Chek™ Active and Mylife™, Pura™ met the International Organization for Standardization 2013 recommendations for clinical accuracy based on Parke's consensus error grid analysis. All glucometers assessed except Accu-Chek® Active showed a satisfactory level of precision at all concentrations of standard solutions used.
... Since both type 1 and type 2 diabetes show a direct relationship between the degree of glucose control and the risk of systemic complications, many clinical organisations such as the American Diabetes Association (ADA) promote self-monitoring. 4 According to the current position statement of the ADA, SMBG is considered an important component of diabetes in controlling the risk of late renal, retinal and neurological complications. It is therefore recommended that all insulin-treated patients perform SMBG to (a) achieve and maintain glycaemic control, (b) prevent and detect hypoglycaemia, (c) avoid severe hypoglycaemia, and (d) adjust changes in lifestyle. ...
... 5 With the introduction of glucometers, there has been an ongoing, competition-driven development in both meter and strip technology, which has allowed for greater accuracy and reliability of results. 4 However, despite the advances in technology, there is significant variation among these monitoring devices, which has necessitated the development of performance guidelines by organisations such as the ADA and the International Standardization Organization (ISO). 3 The ISO guidelines recommend that the total analytical error of the Abstract Objective: To assess the accuracy and precision of five currently available blood glucose meters in South Africa ...
Article
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Objective: To assess the accuracy and precision of five currently available blood glucose meters in South AfricaBackground: Since the introduction of glucometers, there has been an ongoing, competition-driven development in both meter and strip technology, which has allowed for greater accuracy and reliability of results. Despite the advances in technology, there is significant variation amongst these glucometers necessitating a proper evaluation before use.Methods: Glucose levels in capillary blood samples from 115 patients attending the diabetic clinic at Tygerberg Hospital were measured with each meter, and compared with the laboratory reference method.Results: The coefficients of variation (CVs) (imprecision) of most meters were acceptable at less than 5%, with a bias ranging from 1.7 to 6.8%. None of the glucometers satisfied the American Diabetes Association (ADA) recommendation of less than 5% bias.Conclusions: The study highlights the need for an objective and independent comparison of all glucometers in South Africa, as the variability observed can impact on patient care.
... Glycemia course over a 120-day period was estimated based on CGM using a Guardian RT system (Medtronic Diabetes, Northridge, CA, USA) calibrated at least 4 times a day using capillary glucose measured with an Accu-Chek Go glucometer (Roche Diagnostics, Basel, Switzerland). Glucose concentrations measured with glucometers were rescaled to reflect the whole blood glucose concentrations as if they had been measured with the gold standard glucose analyzer YSI 2300 Stat Plus (Yellow Springs Instruments Inc., Yellow Springs, OH, USA) according to the linear regression reported by Cohen et al. [13]. Then the results were multiplied by 1.11, as recommended by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) [14], to reflect blood glucose (BG) concentrations in plasma. ...
Article
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Background Glycated hemoglobin A1c (HbA1c) has been used as an index of glycemic control in the management, guidance, and clinical trials of diabetic patients for the past 35 years. The aim of this study was to validate the HbA1c model in patients with type 1 and type 2 diabetes and to use it to support interpretation of HbA1c in different clinical situations. Methods The HbA1c model was identified in 30 patients (15 with type 1 diabetes and 15 with type 2 diabetes) by estimating the overall glycation rate constant (k), based on results of continuous glucose monitoring. The model was validated by assessing its ability to predict HbA1c changes in cultures of erythrocytes in vitro and to reproduce results of the A1C-Derived Average Glucose (ADAG) study. The model was used to simulate the influence of different glucose profiles on HbA1c. Results The mean k was equal to 1.296 ± 0.216 × 10−9 l mmol−1 s−1 with no difference between type 1 and type 2 diabetes. The mean coefficient of variation of k was equal to 16.7%. The model predicted HbA1c levels in vitro with a mean absolute difference less than 0.3% (3.3 mmol/mol). It reproduced the linear relationship of HbA1c and mean glucose levels established in the ADAG study. The simulation experiments demonstrated that during periods of unstable glycemic control, glycemic profiles with the same mean glucose might result in much different HbA1c levels. Conclusions Patients with type 1 and type 2 diabetes are characterized by the same mean value of k, but there is considerable interindividual variation in the relationship of HbA1c and mean glucose level. Results suggest that reciprocal changes in glycation rate and the life span of erythrocytes exist in a wide range of HbA1c values. Thus, for an average patient with diabetes, no modifications of parameters of the glycation model are required to obtain meaningful HbA1c predictions. Interpreting HbA1c as a measure of the mean glucose is fully justified only in the case of stable glycemia. The model and more frequent tests of HbA1c might be used to decrease ambiguity of interpreting HbA1c in terms of glycemic control.
... In particular, the portable glucometer is capable of measuring glucose levels in less than 5 sec by using a very small amount of capillary blood (less than 1 mL). Its accuracy and precision has been previously studied in comparison with 4 other latest device models (Accu-Check Go and Accu-Check Advantage manufactured by Roche; Optimum, Abbott; and GlucoMan PC, Menarini), which confirmed its precision and accuracy with a mini-mum bias level of <5% [17]. ...
Article
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Blood glucose testing (BGT) at the forearm minimizes the pain experienced during sampling of capillary blood. We compared the BGT results for forearm sampling with those for standard finger skin puncture and venous serum to evaluate the clinical validity of forearm BGT. BGT was performed on the finger (G(F)) and forearm (G(A)) with a portable glucometer in 555 subjects, including 61 diabetic patients, under fasting conditions. BGT with venous serum (G(V)) was followed within an hour in 514 subjects. Simple linear regression, intraclass correlation, and Passing-Bablok regression analyses were performed using the G(A)-G(F) and G(A)-G(V) data. G(A) showed an excellent linear relationship with both G(F) and G(V) with a Pearson correlation coefficient (r) of 0.97 (P<0.0001) in the patient group, which was similar to the findings in the normal group except for the lower r values. The mean bias between G(A) and G(F) and between G(A) and G(V) were within +/- 10 mg/dL in both groups. The intraclass correlation coefficients were slightly smaller than the corresponding r values, but they showed the same tendency in both groups. In the Passing-Bablok analyses, the 95% confidence intervals of the slope and intercept parameters were <+/-20% of unity and <+/-20 mg/dL, respectively, which were within the acceptable ranges. All 3 statistical analyses supported the satisfactory agreement of G(A) with G(F) or G(V). BGT at the forearm was highly consistent with the standard BGT, thereby confirming its applicability in clinical practice for self-testing under steady fasting conditions.
... Capillary glucose measurements (G) were generated by adding a 5% error (uniform distribution) to the plasma glucose value generated by the T1DM simulator. The selected 5% error was based on the American Diabetes Association recommendation of CV < 5% bias [36]. Finally, because subjects with T1DM introduce significant errors when counting carbohydrates, a 20% error (uniform distribution) was considered in the estimation of carbohydrates. ...
Article
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This paper presents an advanced insulin bolus advisor for people with diabetes on multiple daily injections or insulin pump therapy. The proposed system, which runs on a smartphone, keeps the simplicity of a standard bolus calculator while enhancing its performance by providing more adaptability and flexibility. This is achieved by means of applying a retrospective optimisation of the insulin bolus therapy using a novel combination of Run-To-Run (R2R) that uses intermittent continuous glucose monitoring data, and Case-Based Reasoning (CBR). The validity of the proposed approach has been proven by in-silico studies using the FDA-accepted UVa-Padova Type 1 Diabetes Simulator. Tests under more realistic in-silico scenarios are achieved by updating the simulator to emulate intra-subject insulin sensitivity variations and uncertainty in the capillarity measurements and carbohydrate intake. The CBR(R2R) algorithm performed well in simulations by significantly reducing the mean blood glucose, increasing the time in euglycemia and completely eliminating hypoglycaemia. Finally, compared to a R2R standalone version of the algorithm, the CBR(R2R) algorithm performed better in both adults and adolescent populations, proving the benefit of the utilisation of CBR. In particular, the mean blood glucose improved from 166 39 to 150 16 in the adult populations (p = 0:03) and from 167 25 to 162 23 in the adolescent population (p = 0:06). In addition, CBR(R2R) was able to completely eliminate hypoglycaemia, while the R2R alone was not able to do it in the adolescent population.
... Sensor error is simulated to be normally distributed with a standard deviation of 5%, and max error of ± 4 standard deviations, with a saturated max of ± 20%. The latest generation of glucose meters are more advanced with greater accuracy [Chan et al., 2009;Cohen et al., 2006]. Hence, the error simulated is typical of today's devices or slightly larger. ...
... are mean 0 iid error terms. There have been multiple studies about potential biases in FS k (Brunner et al. (1998);Cohen et al. (2006); Khan et al. (2006); Kristensen et al. (2008)). Overall, the results of these studies seem inconclusive (Mahoney and Ellison (2007)). ...
Article
Real-time monitoring of blood glucose density is essential for managing diabetes. Continuous glucose monitoring (CGM) systems have been developed to help address this need. Many CGM systems are built around an electrochemical biosensor that may be inserted into the subcutaneous tissue of an individual and allows for nearly continuous monitoring of an electrical current generated by glucose molecules near the sensor site. This electrical current is correlated with blood glucose density and, in principle, provides a means for real-time monitoring of blood glucose density. One of the major challenges in CGM is developing algorithms for converting sensor measurements into accurate estimates of blood glucose density in real time. In this paper, we describe fundamental statistical problems that arise in developing CGM algorithms. We propose statistical algorithms based on Kalman filtering, nonparametric empirical Bayes methods, and ideas from sequential change-point detection, and apply them to a very rich CGM dataset. The performance of our methods compares favorably to that of an existing widely used CGM algorithm. A simulation study sheds light on other interesting and important aspects of the problem. More broadly, this paper highlights an important application that has received little attention in the statistics literature and our results suggest that the appropriate application of statistical methodology may lead to significant contributions in diabetes technology research.
... For example, it has been reported that laboratory glucose levels are overestimated when the hematocrit values are < 35% [19][20][21]. It has been reported that CVs should be < 5% for all tests, because the lower the CV values, the more precise the blood glucose estimates [22][23][24]. This CV level is recommended by the ADA, which allows only 5% variability in glucometer readings when compared to laboratory values. ...
Conference Paper
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Background Glucometers have become a fundamental tool in measuring and monitoring glucose level, both in healthcare institutions and home care. The accuracy of glucometers affects the quality of management of diabetic patients and is associated with the occurrence of over-treating or under-treating accidents due to inaccurate readings. This study assessed the accuracy of five commercially available glucometers by reference to laboratory venous plasma glucose (PG) measurement. Methods A cross-sectional study was conducted among patients with diabetes attending King Abdulaziz Medical City laboratory. All participants underwent venipuncture regarding laboratory PG, simultaneously with capillary blood sampling, on which capillary glucose (CG) was measured using the glucometers AccuCheck®, OneTouch®, Freestyle Optium Neo®, Contour Next®, and Contour Next One® in random order. All glucometers were adequately calibrated and verified according to American Diabetes Association guidelines before use. Bias was calculated for each glucometer as the difference between CG and PG (ΔCG-PG). One-sample t-test was used to analyze mean ΔCG-PG by reference to zero for each of the glucometers. Bland–Altman analysis was undertaken by plotting ΔCG-PG against PG. Proportional bias was investigated by analyzing the relationship between ΔCG-PG and PG using linear regression. Results A total of 203 patients were included, with mean PG 155.22 (SD 64.88) mg/dL. The coefficient of variation of the meters ranged from 37.79% to 41.80%. Mean CGs ranged from 153.01 (SD 57.82) to 163.00 (SD 64.52) depending on the glucometer. Three meters showed negative bias. Mean difference was 2.20 for AccuCheck, -2.26 for One Touch, 0.90 for Freestyle, -2.08 for Contour Next, and -7.78 for Contour Next One. Bias percentage ranged from -5.01 to 1.42. Bland–Altman plots showed proportional bias (an increase in the magnitude of the error as the test result increases). Proportional bias was supported by the significant linear regression analysis for all glucometers. Conclusion Of all glucometers, Freestyle Optium Neo showed the minimal mean bias, while Contour Next One showed the highest proportional bias. However, all of the glucometers were within 5% difference. High blood glucose readings above 200 mg/dL should be confirmed by venous measurement.
... 4,6 (4) Concentration of all other types of hemoglobin except HbA and HbA1c is negligible. (5) RBCs are eliminated in chronological order (''the oldest'' RBCs are eliminated first). 16 (6) Influence of hemoglobin loss from RBCs on HbA1c is negligible in vivo and nonexistent in vitro. ...
Article
The objectives were as follows: (1) estimating mean value of the overall hemoglobin glycation rate constant (k); (2) analyzing inter-individual variability of k; (3) verifying ability of the hemoglobin A1c (HbA1c) formation model to predict changes of HbA1c during red blood cells cultivation in vitro and to reproduce the clinical data. The mean k estimated in a group of 10 non-diabetic subjects was equal to 1.257 ± 0.114 × 10(-9) L mmol(-1) s(-1). The mean k was not affected by a way of estimation of glycemia. The mean k differed less than 20% from values reported earlier and it was almost identical to the mean values calculated on basis of the selected published data. Analysis of variability of k suggests that inter-individual heterogeneity of HbA1c formation is limited or rare. The HbA1c mathematical model was able to predict changes of HbA1c in vitro resulting from different glucose levels and to reproduce a linear relationship of HbA1c and average glucose obtained in the A1C-Derived Average Glucose Study. This study demonstrates that the glycation model with the same k value might be used in majority of individuals as a tool supporting interpretation of HbA1c in different clinical situations.
... In terms of intra-assay precision testing, the coefficient of variation of 3 different plasma glucose samples were 3.6%, 3.3%, and 6.1%, which are considered within the acceptable limit and are comparable with the previous studies which reported the coefficient of variation ranged from 6% to 15% (17,18) . ...
Article
Background: Point of care testing using glucose meters that measure capillary blood are the most popular and widely used method for the routine monitoring of blood glucose level. TRUEresult is one of such commonly used blood glucose measuring tools with high accuracy and precision profile according to the manufacturer’s data. Objective: To evaluate the performance of TRUEresult in real life practice by examining the agreement between capillary and venous glucose result using TRUEresult and a laboratory plasma glucose. Material and Method: The present study is a cross sectional analytical study. All the data were collected from the patients whose blood samples were drawn for the measurement of plasma glucose at the outpatient department of Srinagarind Hospital, Khon Kaen University, Thailand. TRUEresult blood glucose monitoring system was used to perform blood glucose measurement in whole blood samples from capillary and veins. This was compared with plasma glucose result from the automated analyzer in the central laboratory, which was considered as reference method at Srinagarind Hospital. Results: The ISO 15197:2013 criteria was used to determine technical accuracy of the TRUEresult tool. Blood glucose levels in whole blood sample from capillary and veins, as measured using the TRUEresult, were 88.24% and 92.16% of the acceptable bias limits. This is below the minimal acceptable criteria. When Parkes error grid analysis was used to define the significance in clinical decision, all the errors of blood glucose levels measured using the TRUEresult were within zone A and zone B, meaning that the errors have no or little influence on clinical decision. Conclusion: The blood glucose levels in whole blood from capillary and veins measured using TRUEresult blood glucose monitoring was within acceptable accuracy limit. The observed error had no or little influence on clinical decision.
... 29 and blood glucose concentration ([BGlu]) (mmol/L) (Accu-Chek analyzer; Roche, Mannheim, Germany) (CV = 2.6%-3.6%) 30 from fingertip capillary samples following each quarter. To provide an assessment of hydration changes, body mass (in minimal clothing following wiping of sweat from the body) and water consumption were monitored prior to and immediately following the simulation test using calibrated electronic scales with a precision of 0.05 kg (BWB-600; Tanita Corporation). ...
Article
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Purpose: The aims of this study were to: (1) provide a comprehensive physiological profile of simulated basketball activity and (2) identify temporal changes in player responses in controlled settings. Methods: State-level male basketball players (n = 10) completed 4 × 10 min simulated quarters of basketball activity using a reliable and valid court-based test. A range of physiological (ratings of perceived exertion, blood lactate concentration ([BLa-]), blood glucose concentration ([BGlu]), heart rate (HR), and hydration) and physical (performance and fatigue indicators for sprint, circuit, and jump activity) measures were collected across testing. Results: Significantly reduced [BLa-] (6.19 ± 2.30 vs. 4.57 ± 2.33 mmol/L; p = 0.016) and [BGlu] (6.91 ± 1.57 vs. 5.25 ± 0.81 mmol/L; p = 0.009) were evident in the second half. A mean HR of 180.1 ± 5.7 beats/min (90.8% ± 4.0% HRmax) was observed, with a significant increase in vigorous activity (77%-95% HRmax) (11.31 ± 6.91 vs. 13.50 ± 6.75 min; p = 0.024) and moderate decrease in near-maximal activity (>95% HRmax) (7.24 ± 7.45 vs. 5.01 ± 7.20 min) in the second half. Small increases in performance times accompanied by a significantly lower circuit decrement (11.67% ± 5.55% vs. 7.30% ± 2.16%; p = 0.032) were apparent in the second half. Conclusion: These data indicate basketball activity imposes higher physiological demands than previously thought and temporal changes in responses might be due to adapted pacing strategies as well as fatigue-mediated mechanisms.
... En concordancia con este hallazgo, otros autores han observado asimismo un mejor rendimiento de ciertos dispositivos en rangos de hiperglucemia 4,21 , aunque también se ha reportado una mayor exactitud en situaciones de normoglucemia 3 o, por el contrario, un incremento en la diferencia entre GC y GP al aumentar los niveles de glucemia 22 . En la actualidad, se acepta que la exactitud de un glucómetro presenta variaciones a lo largo del rango de valores glucémicos 2 , y en este sentido, se ha planteado el establecimiento de unos estándares de calidad diferenciados para valores clínicamente relevantes (como pudieran ser los rangos de hipoglucemia, de normoglucemia y de hiperglucemia) que faciliten una correcta toma de decisiones clínicas 23 . ...
Article
Introducción: Los glucómetros demuestran habitualmente una gran exactitud, y en la práctica, la glucemia capilar y la glucemia plasmática (GP) son utilizadas indistintamente. Sin embargo, numerosas variables pueden afectar la validez de estos aparatos. El objetivo de este estudio fue conocer la exactitud y la concordancia de 3 glucómetros utilizados en las consultas de un EAP. Material y métodos: De 59 participantes se obtuvieron una muestra de sangre venosa y una gota de sangre capilar, que fue analizada en 3 glucómetros: 2 FreeStyle® Optium (OP1 y OP2) y un Accu-Chek® Aviva. El valor de referencia fue la GP y fueron analizados asimismo el hematocrito y los niveles plasmáticos de urea, bilirrubina, ácido úrico y triglicéridos. Se utilizaron la regresión de Passing-Bablok para la exactitud, y el coeficiente de correlación intraclase y el método Bland-Altman para la concordancia. Se ha considerado el estándar actual (American Diabetes Association) de un error tolerado de ±5%. Resultados: La diferencia de medias±desviación estándar (mg/dL) y el error sistemático fueron: 5,8±7 y 5,8% (OP1); 6,2±8 y 5,9% (OP2); 8,3±8 y 6,3% (Accu-Chek®). El par más concordante fue OP1/OP2, con un coeficiente de correlación intraclase = 0,97, sesgo = −0,4 mg/dL y una amplitud de los límites de acuerdo al 95% = 28,6 mg/dL. Se observaron los mayores grados de exactitud y de concordancia en rangos glucémicos elevados (GP≥126 mg/dL). Conclusiones: Aunque mostraron una diferencia de medias clínicamente aceptable respecto a la GP, los 3 glucómetros incumplieron el estándar actual de la American Diabetes Association. Es recomendable la realización periódica de controles de calidad de estos dispositivos. 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 = −0.4 mg/dL, and a width of the 95% limits of agreement of 28.6 mg/dL. The highest levels of accuracy and reliability were observed in high glucose ranges (PG≥126 mg/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.
... Finger prick FBG was measured by the Accu Chek Advantage Blood Glucose Monitor (Roche Diagnostics of New Zealand). Accuracy and precision of this instrument was tested in other studies [40,41]. Successive drops of blood were taken for measuring TC at that moment. ...
... The use of point-of-care (POC) testing for lipid and glucose levels is also a potential limitation, when compared to measurements obtained through conventional laboratory testing. However, the machines used to obtain POC testing have been validated against current laboratory-based methods [42,43]. ...
Article
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BACKGROUND: A consequence of the widespread uptake of anti-retroviral therapy (ART) is that the older South African population will experience an increase in life expectancy, increasing their risk for cardiometabolic diseases (CMD), and its risk factors. The long-term interactions between HIV infection, treatment, and CMD remain to be elucidated in the African population. The HAALSI cohort was established to investigate the impact of these interactions on CMD morbidity and mortality among middle-aged and older adults. METHODS: We recruited randomly selected adults aged 40 or older residing in the rural Agincourt sub-district in Mpumalanga Province. In-person interviews were conducted to collect baseline household and socioeconomic data, self-reported health, anthropometric measures, blood pressure, high-sensitivity C-reactive protein (hsCRP), HbA1c, HIV-status, and point-of-care glucose and lipid levels. RESULTS: Five thousand fifty nine persons (46.4% male) were enrolled with a mean age of 61.7 ± 13.06 years. Waist-to-hip ratio was high for men and women (0.92 ± 0.08 vs. 0.89 ± 0.08), with 70% of women and 44% of men being overweight or obese. Blood pressure was similar for men and women with a combined hypertension prevalence of 58.4% and statistically significant increases were observed with increasing age. High total cholesterol prevalence in women was twice that observed for men (8.5 vs. 4.1%). The prevalence of self-reported CMD conditions was higher among women, except for myocardial infarction, and women had a statistically significantly higher prevalence of angina (10.82 vs. 6.97%) using Rose Criteria. The HIV- persons were significantly more likely to have hypertension, diabetes, or be overweight or obese than HIV+ persons. Approximately 56% of the cohort had at least 2 measured or self-reported clinical co-morbidities, with HIV+ persons having a consistently lower prevalence of co-morbidities compared to those without HIV. Absolute 10-year risk cardiovascular risk scores ranged from 7.7-9.7% for women and from 12.5-15.3% for men, depending on the risk score equations used. CONCLUSIONS: This cohort has high CMD risk based on both traditional risk factors and novel markers like hsCRP. Longitudinal follow-up of the cohort will allow us to determine the long-term impact of increased lifespan in a population with both high HIV infection and CMD risk. KEYWORDS: Aging; Antiretrovirals; Cardiometabolic; Cardiovascular; Diabetes; HIV; Hypertension
... However, studies from some other countries have yielded more encouraging results. In an Australian study where 5 glucometers were assessed all except one glucometer managed to get a <5% coefficient variation in both high and low concentration control solutions and all glucometers achieved ISO standard although only one managed to achieve ADA recommendation of 5% bias [10]. According to Clarke Error Grid analysis results, all the glucometers showed adequate clinical accuracy with all measurements from all meters lying in zones A or B. All 3 glucometers that were tested in the study in New Zealand managed to achieve <5% coefficient variation in both high and low concentration control solutions, fulfilled the ISO recommendation and was clinically accurate according to Clarke Error grid analysis [11]. ...
Article
Aims: Life threatening macrovascular and microvascular complications of diabetes can be minimized by effective glycaemic control. Self monitoring of blood glucose with glucometers is recognized as a cost effective strategy to improve glycaemic control. However accuracy and precision of glucometers will determine the effectiveness of this strategy. We aimed to evaluate accuracy and precision of commonly used glucometers in Sri Lanka. Materials and methods: An observational study was conducted in a tertiary care setting including patients with diabetes and healthy volunteers. Eight commonly used glucometers were used. Blood glucose was measured in 50 participants (16 healthy volunteers, 34 patients with diabetes) in finger prick capillary blood using glucometers and venous blood using standard laboratory methods, and were compared to determine accuracy. Repeated measurements from same glucometer with a single finger prick were made and compared to determine precision. Results: Only one glucometer showed insignificant difference to venous plasma glucose values. Only one glucometer met ADA recommended bias of <5%. None of the glucometers fell within the ISO recommendations for accuracy. Conclusion: Majority of commonly used glucometers in Sri Lanka do not meet the ADA recommendations and ISO standards for accuracy and precision. However their variations are unlikely to make significant adverse impact on patient management.
... In the majority of cases, SMBG time series are collected by the patient and then analyzed and interpreted by the physician during periodic visits, e.g., every two/four months, after which the individual's therapeutic plan is revised accordingly [42]. Regarding the performance of a glucose meter, Cohen et al. revealed that the commercial version of glucometers such as CareSens and Accu-Chek are two of the most precise meters with a measurement error of 4.0 and 6.5%, respectively [43]. ...
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Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a personalized healthcare monitoring system by utilizing a BLE-based sensor device, real-time data processing, and machine learning-based algorithms to help diabetic patients to better self-manage their chronic condition. BLEs were used to gather users’ vital signs data such as blood pressure, heart rate, weight, and blood glucose (BG) from sensor nodes to smartphones, while real-time data processing was utilized to manage the large amount of continuously generated sensor data. The proposed real-time data processing utilized Apache Kafka as a streaming platform and MongoDB to store the sensor data from the patient. The results show that commercial versions of the BLE-based sensors and the proposed real-time data processing are sufficiently efficient to monitor the vital signs data of diabetic patients. Furthermore, machine learning–based classification methods were tested on a diabetes dataset and showed that a Multilayer Perceptron can provide early prediction of diabetes given the user’s sensor data as input. The results also reveal that Long Short-Term Memory can accurately predict the future BG level based on the current sensor data. In addition, the proposed diabetes classification and BG prediction could be combined with personalized diet and physical activity suggestions in order to improve the health quality of patients and to avoid critical conditions in the future.
... To minimise misdiagnosis, blood samples, which showed a GC below 2.2 mM, were retested in the clinical laboratory. Moreover, variance in reliability of POC glucose meters is depending on variability in instrument analytical performance [17] and interaction between users and POC glucose meters [8]. ...
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Conclusion: Safety of limiting the monitoring to 12 h still has to be carefully evaluated in the presence of SGA or LGA newborns; however, our results suggest that 12 h is enough for late preterm newborns (> 34 weeks) and maternal diabetes. What is Known: • Newborns are at relatively high risk for developing hypoglycaemia and such hypoglycaemia is associated with adverse neurodevelopmental outcomes. • Proper glucose monitoring and prompt treatment in case of neonatal hypoglycaemia are necessary. What is New: • Glucose monitoring 12 h after birth is proficient for most newborns at risk. • Maternal diabetes leads to the highest risk of early neonatal hypoglycaemia and newborns with more than one risk factor are at increased risk of hypoglycaemia.
... At the moment, the blood glucose level measurements are performed by glucometers [4,5]. This method requires making a finger puncture for every measurement. ...
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This paper is devoted to research influence of creatinine and triglycerides on THz optical properties of blood for diabetes care purposes.
... La mayor parte de estos equipos tienen lectura amperométrica, detectando cambios eléctricos que son proporcionales a la cantidad de glucosa presente en la muestra y que se basan en las mismas reacciones químicas que los equipos de laboratorio tradicionales (glucosa-hexoquinasa o glucosa-oxidasa), siendo lineales en rangos entre 10 y 600 mg/dL de glucosa. Múltiples estudios han demostrado que los glucómetros tienen buen desempeño analítico para el control ambulatorio, tanto en precisión como en exactitud 4,5 . Se recomienda que todo paciente que vaya a utilizar un glucómetro en su domicilio, reciba entrenamiento y supervisión por parte de un profesional respecto al uso apropiado del equipo, manteniendo vías de comunicación expedita para eventuales consultas. ...
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los exámenes realizados al lado de la cama del enfermo f'Point of care testing, POCT") tienen como mayor ventaja la rapidez en la entrega de resultados y la simplicidad de uso, siendo su principal aplicación el autocontrol de la glicemia en pacientes diabéticos. El uso de estos equipos a nivel hospitalario introduce exigencias a las instituciones de salud, las cuales deben monitorizar todos ¡os aspectos del proceso, incluyendo la capacitación de los usuarios, el adecuado control de calidad, el desarrollo de procedimientos escritos para su uso e inclusive la participación en encuestas de control de calidad externo, evitando la generación de errores y colaborando así con la seguridad del paciente.
... Furthermore, we used glucometers not only for point of care glucose values, but also for study values during our hyperinsulinemic-euglycemic clamp. Literature has shown that glucometer readings are directly affected by hematocrit levels (32)(33)(34). Compared with glucose analyzers, a lower hematocrit yields a higher plasma glucose level and vice versa (32). ...
Article
To institute intensive insulin therapy protocol in an acute pediatric burn unit and study the mechanisms underlying its benefits. Prospective, randomized study. An acute pediatric burn unit in a tertiary teaching hospital. Children, 4-18 yrs old, with total body surface area burned > or =40% and who arrived within 1 wk after injury were enrolled in the study. Patients were randomized to one of two groups. Intensive insulin therapy maintained blood glucose levels between 80 and 110 mg/dL. Conventional insulin therapy maintained blood glucose < or =215 mg/dL. Twenty patients were included in the data analysis consisting of resting energy expenditure, whole body and liver insulin sensitivity, and skeletal muscle mitochondrial function. Studies were performed at 7 days postburn (pretreatment) and at 21 days postburn (posttreatment). Resting energy expenditure significantly increased posttreatment (1476 +/- 124 to 1925 +/- 291 kcal/m(2) x day; p = .02) in conventional insulin therapy as compared with a decline in intensive insulin therapy. Glucose infusion rate was identical between groups before treatment (6.0 +/- 0.8 conventional insulin therapy vs. 6.8 +/- 0.9 mg/kg x min intensive insulin therapy; p = .5). Intensive insulin therapy displayed a significantly higher glucose clamp infusion rate posttreatment (9.1 +/- 1.3 intensive insulin therapy versus 4.8 +/- 0.6 mg/kg x min conventional insulin therapy, p = .005). Suppression of hepatic glucose release was significantly greater in the intensive insulin therapy after treatment compared with conventional insulin therapy (5.0 +/- 0.9 vs. 2.5 +/- 0.6 mg/kg x min; intensive insulin therapy vs. conventional insulin therapy; p = .03). States 3 and 4 mitochondrial oxidation of palmitate significantly improved in intensive insulin therapy (0.9 +/- 0.1 to 1.7 +/- 0.1 microm O(2)/CS/mg protein/min for state 3, p = .004; and 0.7 +/- 0.1 to 1.3 +/- 0.1 microm O(2)/CS/mg protein/min for state 4, p < .002), whereas conventional insulin therapy remained at the same level of activity (0.9 +/- 0.1 to 0.8 +/- 0.1 microm O(2)/CS/mg protein/min for state 3, p = .4; 0.6 +/- 0.03 to 0.7 +/- 0.1 microm O(2)/CS/mg protein/min, p = .6). Controlling blood glucose levels < or =120 mg/dL using an intensive insulin therapy protocol improves insulin sensitivity and mitochondrial oxidative capacity while decreasing resting energy expenditure in severely burned children.
... The use of the CardioChek PA device for lipid measurement likely underestimates cardiovascular risk in our population. Per recent published validity assessments, the CardioChek PA seems to underestimate LDL, HDL, and total cholesterol, while being inaccurate by unbiased in its triglyceride measurements [30].This contrasts with prior studies which validated the CardioChek PA against laboratory-based methods [31,32]. Unfortunately, there is no venous draw validation for lipid values in the HAALSI data set. ...
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Dyslipidemia is a primary driver for chronic cardiovascular conditions and there is no comprehensive literature about its management in South Africa. The objective of this study was to assess the prevalence, awareness, treatment, and control of dyslipidemia in rural South Africa and how they are impacted by different behaviors and non-modifiable factors. To fulfill this objective we recruited for this cohort study adults aged ≥40 years residing in the Agincourt sub-district of Mpumalanga Province. Data collection included socioeconomic and clinical data, anthropometric measures, blood pressure (BP), HIV-status, point-of-care glucose and lipid levels. Framingham CVD Risk Score was ascribed to patients based upon categories for 10 year cardiovascular risk of low (<3%), moderate (≥3% and <15%), high (≥15% and <30%), and very high (≥30%).LDL cholesterol control by risk category was defined according to South African Guidelines. Multivariable logistic regression models were built to identify factors that were significantly associated with dyslipidemia and awareness of dyslipidemia From 5,059 respondents a total of 4247 subjects (83.9%) had their cholesterol levels measured and were included in our analysis. Overall, 67.3% (2860) of these met criteria for dyslipidemia, only 30 (1.05%) were aware of their condition, and only 21 subjects (0.73%) were on treatment. The majority have abnormalities in triglycerides (59.3%). As cardiovascular risk increased the rates of lipid control according to LDL level dropped. Multivariate logistic regression analyses showed that being overweight was predictive of dyslipidemia (OR 1.76; 95%CI 1.51–2.05, p<0.001) and dyslipidemia awareness (OR 2.58; 95%CI 1.19–5.58; p = 0.017). In conclusion, the very low awareness and treatment of dyslipidemia in this cohort indicate a greater need for systematic screening and education within the population and demonstrate that there are multiple opportunities to allay this burden.
... The use of point-of-care (POC) testing for lipid and glucose levels is also a potential limitation, when compared to measurements obtained through conventional laboratory testing. However, the machines used to obtain POC testing have been validated against current laboratory-based methods [42,43]. ...
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BackgroundA consequence of the widespread uptake of anti-retroviral therapy (ART) is that the older South African population will experience an increase in life expectancy, increasing their risk for cardiometabolic diseases (CMD), and its risk factors. The long-term interactions between HIV infection, treatment, and CMD remain to be elucidated in the African population. The HAALSI cohort was established to investigate the impact of these interactions on CMD morbidity and mortality among middle-aged and older adults. Methods We recruited randomly selected adults aged 40 or older residing in the rural Agincourt sub-district in Mpumalanga Province. In-person interviews were conducted to collect baseline household and socioeconomic data, self-reported health, anthropometric measures, blood pressure, high-sensitivity C-reactive protein (hsCRP), HbA1c, HIV-status, and point-of-care glucose and lipid levels. ResultsFive thousand fifty nine persons (46.4% male) were enrolled with a mean age of 61.7 ± 13.06 years. Waist-to-hip ratio was high for men and women (0.92 ± 0.08 vs. 0.89 ± 0.08), with 70% of women and 44% of men being overweight or obese. Blood pressure was similar for men and women with a combined hypertension prevalence of 58.4% and statistically significant increases were observed with increasing age. High total cholesterol prevalence in women was twice that observed for men (8.5 vs. 4.1%). The prevalence of self-reported CMD conditions was higher among women, except for myocardial infarction, and women had a statistically significantly higher prevalence of angina (10.82 vs. 6.97%) using Rose Criteria. The HIV− persons were significantly more likely to have hypertension, diabetes, or be overweight or obese than HIV+ persons. Approximately 56% of the cohort had at least 2 measured or self-reported clinical co-morbidities, with HIV+ persons having a consistently lower prevalence of co-morbidities compared to those without HIV. Absolute 10-year risk cardiovascular risk scores ranged from 7.7–9.7% for women and from 12.5–15.3% for men, depending on the risk score equations used. Conclusions This cohort has high CMD risk based on both traditional risk factors and novel markers like hsCRP. Longitudinal follow-up of the cohort will allow us to determine the long-term impact of increased lifespan in a population with both high HIV infection and CMD risk.
... Moreover, all our glucometer readings were reproducible with coefficients of variation (CV) of two replicates less than 5%, an observation that agrees with the manufacturer's specifications. An evaluation of five glucometers in Australia showed a CV less than 5% when 49 diabetic individuals were tested [35]. ...
Article
The potential of glucometry in in-vitro starch digestion was investigated for developing a rapid procedure to understand kinetics of digestion. A hand-held glucometer, intended for testing of plasma glucose levels, was used for the assay of glucose released by the combined action of a-amylase and amyloglucosidase on a range of starch substrates. The glucometer was sensitive to glucose concentrations in water, and its readings were independent of pH (7.7 and 3.9) and temperature (37°C and 25°C) of the glucose solution, but dependent on lactose and maltose concentrations. Neither fructose nor sucrose affected the readings. Digested starch calculated from the glucometer was not significantly (p. 0.05) different from that calculated from spectrophotometry. Particle size of substrate, sample formulation, grain genotype, and processing affected the glucometer readings as expected from how these factors influence starch digestibility. Corrections are required when samples containing lactose and maltose prior to in-vitro digestion analysis are studied. The developed rapid procedure can be used to collect large numbers of data points per sample per analysis for better understanding the kinetics of starch digestion, and increased confidence level in modelling the digestogram. The glucose detection method is robust and could be adapted for non-laboratory use. Single-point data can also be extracted from digestograms for comparative analysis.
Article
Fast and reliable glycemic control is of tremendous importance in intensive care units. Point-of-care devices used in professional care have to be precise and of low variability, and their connectivity has to outrange the abilities of home-care equivalents. In particular, the meter's efficiency should be tested not only with spiked blood samples from healthy donors but also with blood from intensive care unit patients because of their special matrix conditions as low hematocrit, oxygen pressure variability, or medication. Four types of network-ready glucose meters were tested. Data, obtained from native or maltose/xylose-spiked intensive care patients' blood, were compared (oxygen, hematocrit, glucose, and maltose and xylose dependencies) with those from a YSI 2300 STAT Plus™ glucose and lactate analyzer (YSI Life Sciences, Yellow Springs, OH). According to ISO 15197 (2003) acceptance of glucose meter results was determined. Quality control results were investigated considering a new calculation type in German guidelines. Three of the meters fulfill the overall acceptance criterions. Two of the meters achieved accuracies above 93% in all oxygen, hematocrit, and glucose subgroups. Maltose generates deviations leading to accuracies from 71.1% to 100%, and xylose causes accuracies of 33.3% to 100%. State of the art for manufacturing small network point-of-care testing glucose meters has reached a new level of precision, but the devices still have to be handled with care, and in particular the staff of an intensive care unit still needs knowledge about possible interferences.
Article
Forty-three women were recruited into a 1-year randomised controlled trial to test the feasibility of a structured behavioural intervention to increase physical activity after gestational diabetes. Increases in achievement of physical activity targets were not attained. Recruitment and subject retention were identified as major challenges.
Article
This study compared finger-prick testing of fasting blood glucose, total cholesterol, and glycated hemoglobin (HbA1c) with venous blood method in the screening of Jamaican adolescents in a school setting. Subjects, aged 14 to 18 years, were selected from grades 9 to 12, in 10 randomly selected high schools on the island. Capillary whole blood was tested for fasting blood glucose using the Accu-Chek Advantage Blood Glucose Monitor (Roche Diagnostics, Auckland, New Zealand). The Accutrend GCT Cholesterol Monitor (Roche Diagnostics, Mannheim, Germany) was used for measuring total cholesterol. HbA1c was tested using the NycoCard (Axis-Shield, Oslo, Norway). Finger-prick testing was compared to venous blood using standard laboratory procedures for all 3 tests. A total of 59 students participated, whose mean age was 15.6 (1.2) years. Mean fasting blood glucose finger-prick values (92.88 ± 11.97 mg/dL) was not significantly different (P > 0.05) from venous values (95.24 [10.27] mg/dL). Mean venous value of total cholesterol (157.9 [30.0] mg/dL) was significantly higher (P < 0.01) than finger-prick (145.8 [21.6] mg/dL). Mean venous HbA1c (5.40% [0.81%]) was significantly lower (P < 0.01) than finger-prick (6.08% [1.5%]). Percentage bias between the 2 methods met the reference standards for fasting blood glucose and total cholesterol but not for HbA1c. Bland-Altman tests of agreement between the 2 methods indicated good agreement for all 3 tests. Finger-prick testing of fasting blood glucose compared favorably with venous testing and may be used for screening this population. The Bland Altman tests indicated that finger-prick testing of fasting blood glucose, total cholesterol, and HbA1c may be used for the screening of adolescents in a high school setting.
Article
Current methods for lactose measurement in dairy products are time consuming and tedious and may require expensive equipment and skilled technicians. The aim of this research was to develop a novel and rapid method for the routine measurement of lactose in dairy products. The proposed method is based on the rapid hydrolysis of lactose using β-galactosidase and subsequently measuring glucose using a blood glucose meter. Blood glucose meters were developed after decades of research and clinical trials and are used extensively worldwide by individuals with diabetes to monitor their blood glucose levels. The method was developed and validated in a series of experiments. In the first experiment, temperature and time required for the near-complete hydrolysis of lactose were determined. Subsequently, the influence of glucose meters and their test strip lots were evaluated. We found that meters were not significantly different. However, the test strip lots were significantly different from each other. In the second experiment, the proposed method was validated using different concentrations of lactose solutions (1.9-6.5%) and compared with a HPLC-based reference method. In the third experiment, the proposed method was used to determine the lactose content of raw milk. The proposed method shows potential for rapid, routine, and low-cost measurement of lactose in milk and other dairy products.
Article
Background: Self-mmonitoring of blood glucose (SSMBG) is important for all patients with diabetes, as it provides valuable feedback on the effects of diet, exercise, and medications. To maximize the potential benefits of SMBG, clinicians must have confidence in the accuracy of their patients' glucose meters.Objective: The aim of this article is to review several issues related to glucose meter accuracy and ways that accuracy can be enhanced.Methods: A MeDLINE search of English-language articles using the terms SMBG, glucose meter,and accuracy as an initial screen was performed. After articles describing the use of outdated technologies or vague methodologies were excluded, appropriate articles that analyzed various aspects regarding meter accuracy were selected.Results: Glucose meter accuracy studies are complicated by issues related to the reference method, the sample being assayed, nd he ay n which accuracy s reported. error rid analysis ives linicians a means to valuate the clinical importance of meter error. Modern glucose meters have many technological improvements and enhanced clinical accuracy; however, the accuracy of readings depends not only on the instrument but also on patient technique and other aspects of the overall testing process.Conclusions: SMBG has proven to be a valuable tool for the management of diabetes whether it is used to guide insulin dosing, provide feedback on the effect of meals, or detect hypoglycemia. Accuracy of SMBG can be optimized by patient education and continued improvements in meter technology.
To compare the performance of the four latest models of glucose meters in capillary blood glucose monitoring during pregnancy. 208 pregnant women with gestational diabetes were recruited. Each subject had simultaneous capillary glucose monitoring by two study glucose meters and venous plasma glucose assay. The performance of four glucose meters was compared using error grid analysis (EGA) and the agreement between the meter readings and plasma glucose by Bland-Altman plot analysis. Elite, Advantage II and CareSens had more than 90% of readings in the acceptable target range of EGA. CareSens had the lowest mean bias by Bland-Altman analysis while Advantage II had the highest proportion of readings within 5% difference from plasma glucose. Readings from all glucose meters except Optium were not influenced by the change in maternal hematocrit levels. The performance of four study glucose meters appeared very similar.
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Control of blood glucose (BG) in an acceptable range is a major therapy target for diabetes patients in both the hospital and outpatient environments. This review focuses on the state of point-of-care (POC) glucose monitoring and the accuracy of the measurement devices. The accuracy of the POC glucose monitor depends on device methodology and other factors, including sample source and collection and patient characteristics. Patient parameters capable of influencing measurements include variations in pH, blood oxygen, hematocrit, changes in microcirculation, and vasopressor therapy. These elements alone or when combined can significantly impact BG measurement accuracy with POC glucose monitoring devices (POCGMDs). In general, currently available POCGMDs exhibit the greatest accuracy within the range of physiological glucose levels but become less reliable at the lower and higher ranges of BG levels. This issue raises serious safety concerns and the importance of understanding the limitations of POCGMDs. This review will discuss potential interferences and shortcomings of the current POCGMDs and stress when these may impact the reliability of POCGMDs for clinical decision-making.
Article
Individuals with type 1 diabetes require frequent adjustment of their insulin dose to maintain as near to normal glycaemia as possible. This process is not only burdensome but also, for many, difficult to achieve. As a result, control algorithms to facilitate insulin dosage have been proposed, but have not been completely successful in normalizing glycaemia. Here we present a novel run-to-run control algorithm to adjust the meal-related insulin dose using only post-prandial blood glucose measurements. For each meal independently, the insulin dose is adjusted based on the performance measure for the same meal the previous day. A robustness analysis is performed which considers the sources of uncertainty typically encountered in clinical use. This shows that the system remains stable even with large uncertainty. Copyright © 2006 John Wiley & Sons, Ltd.
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The objective of this study was to understand the level of performance of blood glucose monitors as assessed in the published literature. Medline from January 2000 to October 2009 and reference lists of included articles were searched to identify eligible studies. Key information was abstracted from eligible studies: blood glucose meters tested, blood sample, meter operators, setting, sample of people (number, diabetes type, age, sex, and race), duration of diabetes, years using a glucose meter, insulin use, recommendations followed, performance evaluation measures, and specific factors affecting the accuracy evaluation of blood glucose monitors. Thirty-one articles were included in this review. Articles were categorized as review articles of blood glucose accuracy (6 articles), original studies that reported the performance of blood glucose meters in laboratory settings (14 articles) or clinical settings (9 articles), and simulation studies (2 articles). A variety of performance evaluation measures were used in the studies. The authors did not identify any studies that demonstrated a difference in clinical outcomes. Examples of analytical tools used in the description of accuracy (e.g., correlation coefficient, linear regression equations, and International Organization for Standardization standards) and how these traditional measures can complicate the achievement of target blood glucose levels for the patient were presented. The benefits of using error grid analysis to quantify the clinical accuracy of patient-determined blood glucose values were discussed. When examining blood glucose monitor performance in the real world, it is important to consider if an improvement in analytical accuracy would lead to improved clinical outcomes for patients. There are several examples of how analytical tools used in the description of self-monitoring of blood glucose accuracy could be irrelevant to treatment decisions.
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Advances in telemedicine technologies have offered clinicians greater levels of real-time guidance and technical assistance for diagnoses, monitoring, operations or interventions from colleagues based in remote locations. The topic includes the use of videoconferencing, mentorship during surgical procedures, or machine-to-machine communication to process data from one location by programmes running in another. This edited book presents a variety of technologies with applications in telemedicine, originating from the fields of biomedical sensors, wireless sensor networking, computer-aided diagnosis methods, signal and image processing and analysis, automation and control, virtual and augmented reality, multivariate analysis, and data acquisition devices. The Internet of Medical Things (IoMT), surgical robots, telemonitoring, and teleoperation systems are also explored, as well as the associated security and privacy concerns in this field. Topics covered include critical factors in the development, implementation and evaluation of telemedicine; surgical tele-mentoring; technologies in medical information processing; recent advances of signal/image processing techniques in healthcare; a real-time ECG processing platform for telemedicine applications; data mining in telemedicine; social work and tele-mental health services for rural and remote communities; applying telemedicine to social work practice and education; advanced telemedicine systems for remote healthcare monitoring; the impact of tone-mapping operators and viewing devices on visual quality of experience of colour and grey-scale HDR images; modelling the relationships between changes in EEG features and subjective quality of HDR images; IoMT and healthcare delivery in chronic diseases; and transform domain robust watermarking method using Riesz wavelet transform for medical data security and privacy. Demographic shifts in populations trigger opportunities for innovations in e-Health, m-Health, precision and personalized medicine, robotics, sensing, the Internet of Things, cloud computing, Big Data, Software Defined Networks, and network function virtualization. The integration of these technologies is however associated with many technological, ethical, legal, and social issues. This book series aims to disseminate recent advances in the e-Health Technology field to help improve healthcare and wellbeing.
The objective of this study was to develop a safe, robust and effective protocol for the clinical control of Type 1 diabetes using conventional self-monitoring blood glucose (SMBG) measurements, and multiple daily injection (MDI) with insulin analogues. A virtual patient method is used to develop an in silico simulation tool for Type 1 diabetes using data from a Type 1 diabetes patient cohort (n=40) . The tool is used to test two prandial insulin protocols, an adaptive protocol (AC) and a conventional intensive insulin therapy (IIT) protocol (CC) against results from a representative control cohort as a function of SMBG frequency. With the prandial protocols, optimal and suboptimal basal insulin replacement using a clinically validated, forced-titration regimen is also evaluated. A Monte Carlo (MC) analysis using variability and error distributions derived from the clinical and physiological literature is used to test efficacy and robustness. MC analysis is performed for over 1 400 000 simulated patient hours. All results are compared with control data from which the virtual patients were derived. In conditions of suboptimal basal insulin replacement, the AC protocol significantly decreases HbA1c for SMBG frequencies ⩾6/day compared with controls and the CC protocol. With optimal basal insulin, mild and severe hypoglycaemia is reduced by 86–100% over controls for all SMBG frequencies. Control with the CC protocol and suboptimal basal insulin replacement saturates at an SMBG frequency of 6/day. The forced-titration regimen requires a minimum SMBG frequency of 6/day to prevent increased hypoglycaemia. Overaggressive basal dose titration with the CC protocol at lower SMBG frequencies is likely caused by uncorrected postprandial hyperglycaemia from the previous night. From the MC analysis, a defined peak in control is achieved at an SMBG frequency of 8/day. However, 90% of the cohort meets American Diabetes Association recommended HbA1c with just 2 measurements a day. A further 7.5% requires 4 measurements a day and only 2.5% (1 patient) required 6 measurements a day. In safety, the AC protocol is the most robust to applied MC error. Over all SMBG frequencies, the median for severe hypoglycaemia increases from 0 to 0.12% and for mild hypoglycaemia by 0–5.19% compared with the unrealistic no error simulation. While statistically significant, these figures are still very low and the distributions are well below those of the controls group. An adaptive control protocol for Type 1 diabetes is tested in silico under conditions of realistic variability and error. The adaptive (AC) protocol is effective and safe compared with conventional IIT (CC) and controls. As the fear of hypoglycaemia is a large psychological barrier to appropriate glycaemic control, adaptive model-based protocols may represent the next evolution of IIT to deliver increased glycaemic control with increased safety over conventional methods, while still utilizing the most commonly used forms of intervention (SMBG and MDI). The use of MC methods to evaluate them provides a relevant robustness test that is not considered in the no error analyses of most other studies. Copyright
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Aim: We aimed to evaluate Accu Chek Compact Plus blood glucometer by comparing its accuracy and precision with laboratory reference system. Methods: Original Olympus Glucose reagent served as a reference method. The difference between Olympus and Accu Chek glucose concentrations was tested by paired t-test. Glucometer accuracy was evaluated using: bias (%), Passing-Bablock regression, Bland-Altman and Clarke Error Grid analysis. Intra-assay glucometer precision was examined by 10 consecutive measurements at three glucose levels. Results: The average bias of Accu Chek was -6.6%; Passing-Bablock analysis revealed that there was no significant deviation from linearity; as of Bland-Altman analysis more than 95% of our values lied between mean ± 1.96 SD. The results of the Clarke Error Grid analysis were 100% in zone A of the error grid. Conclusions: Accu Chek Compact Plus blood glucometer has a good accuracy and precision and may be used interchangeably with our laboratory referent-system for daily glucose monitoring.
Article
Objective To assess the reliability of the portable blood glucose meters most used in a Health Area.MethodsA diagnostic test analysis was conducted in the Zone VIII Health Centre, Albacete Health Area. A total of 50 diabetic patients with different treatments, and who came to the Centre to perform an analytical control, were included in the study. Capillary blood samples were measured on the seven glucometers to study. The results were compared with venous blood tested in the reference laboratory of the Albacete General University Hospital. For the descriptive analysis, means and percentages were used, and the Student's t test for paired data and standard deviation for analytical comparisons of the means, with 95% confidence intervals and P < .05.ResultsOf the 50 subjects who were included in the study, 48% were female, and the mean age was 59 years. The glucose readings ranged from 23 mg/dL to 292 mg/dL and with haematocrits between 36.4% and 53.8%. The mean differences between the results from the reference laboratory and the different glucometers were as follows: Contour Link® 6.30; Accu-Chek® Aviva 10.20; Glucocard® 10.32; Optium Xceed® 12.24; FreeStyle Freedom® 13.62; One Touch Ultra 2® 18.16; Breeze 2® –8.08.Conclusions Glucometers generally give reasonable results compared to those measured in venous blood, and are highly reliable for the self-monitoring diabetic patient.
Article
Capillary blood sampling on the forearm reduces pain caused by skin puncture. The present study compared the blood glucose test results performed at different sampling sites of the forearm, finger, and vein to evaluate clinical validity of this alternative site blood sampling technique. Subjects numbered 555 including 61 diabetic patients participated to measure the glucose concentration on the finger () and the forearm () with a portable glucometer under overnight fasting state. Then, the venous glucose concentration () was measured in 514 subjects in less than 1 hour. The test results were analyzed by simple linear regression, intraclass correlation, and Passing-Bablok regression techniques. was highly correlated with or showing the correlation coefficients (r) of approximately 0.97 (P
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Objective: The self-monitoring of blood glucose plays a critical role in management of diabetes mellitus. Although laboratory comparisons of glucose meter accuracy are often acceptable, clinical comparisons show frequent inaccuracies. In this paper, we evaluate the accuracy of self-monitoring blood glucose meters using glucose meter and serum comparisons from a large Canadian laboratory. Methods: This study was performed using secondary data obtained from the Laboratory Information System of Calgary Services, the sole provider of laboratory testing to Calgary and surrounding areas. We examined anonymous quality assurance data for glucose meter comparisons performed on home glucose meters between January 1, 2010, and April 30, 2013. Results: A total of 39 542 comparisons were recorded on 18 540 different subjects. Overall, 6.7% of differences were greater than the current International Standards Organization standard of 15%, and 3.7% exceeded the Canadian guideline of 20%. Conclusions: Glucose meter checks were infrequently performed (on average, once per 1.6 years). A significant subset of meter results was inaccurate.
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Self-monitoring of blood glucose (SMBG) and point-of-care testing are widely used in the management of diabetic outpatients. However, SMBG records are sometimes inaccurate, and may differ from glucose values measured in the hospital. Therefore, the aim of our study was to evaluate the effects of patient education regarding glucometer use on blood glucose levels and to compare the glucose values obtained by six different types of glucometers currently used in Korea. Fifty-six diabetic patients participated in the present study. Each patient visited the hospital in a fasting state. Fasting plasma glucose (FPG) levels in capillary blood samples were measured by doctors and by the patients themselves before and after patient education sessions. Then, glucose levels were measured with each of the six glucometers by doctors and by the patients themselves. The differences between FPG and glucose values measured using glucometers were compared, and their relationships with HbA1c were also assessed. There were no significant differences between glucose levels measured by patients regardless of glucometer education. We obtained similar results for differences between glucose levels measured by patients and doctors. Patient HbA1c levels were not correlated with differences in measurements between glucometers and FPG. Measurements of glucose levels by the six different glucometers did not differ significantly. Our study indicates that education about SMBG, including glucometer handling, is important to increase SMBG accuracy, but that errors in SMBG records are trivial for glucometer users and that the different glucometers used in Korea demonstrate similar accuracy.
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Introduction: Glucose meters are used routinely in hospital wards to manage blood glucose levels in patients requiring frequent monitoring of blood glucose. Objective: Our institution has 50 POC instruments utilized by diverse population of all ages and medical conditions. The primary objective of our study was to investigate whether all these CareSens glucose meters (I-sense Inc, Seoul, South Korea) results in hospitalized patients during routine clinical care jointly satisfy the specified quality specifications, as defined by Clinical and Laboratory Standards Institute (CLSI) guideline POCT12-A3. Materials and Methods: The records of hospitalized patients who underwent simultaneous measures of glucose levels with both glucose meters and a central laboratory analyser between January and June 2013 were retrospectively analysed. We also performed a prospective evaluation of the accuracy of the CareSens glucose Strip. Results: Glucose concentrations measured in 840 patients ranged from 1.66 to 31.72 mmol/L The Bland–Altman difference plot between the auto analyser and all the 50 CareSens glucosemeters revealed a mean bias of -2.2%, with analytical biases for the two methods varying from −31.1% to 26.8%. Eighty four percent of the glucose meter's glucose values were within ± 12.5% for values 5.54 mmol/L of the comparative laboratory glucose values and 93% of the results were within 20% of the reference for glucose >4.2 mmol/L and 65% of the results were within 0.8 mmol/L for glucose
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Introduction And Objective: Most of important variables measured in medicine are in numerical forms or continuous in nature. New instruments and tests are constantly being developed for the purpose of measuring various variables, with the aim of providing cheaper, non-invasive, more convenient and safe methods. When a new method of measurement or instrument is invented, the quality of the instrument has to be assessed. Agreement and reliability are both important parameters in determining the quality of an instrument. This article will discuss some issues related to methods comparison study in medicine for the benefit of medical professional and researcher. Method: This is a narrative review and this article review the most common statistical methods used to assess agreement and reliability of medical instruments that measure the same continuous outcome. The two methods discussed in detail were the Bland-Altman Limits of Agreement, and Intra-class Correlation Coefficient (ICC). This article also discussed some issues related to method comparison studies including the application of inappropriate statistical methods, multiple statistical methods, and the strengths and weaknesses of each method. The importance of appropriate statistical method in the analysis of agreement and reliability in medicine is also highlighted in this article. Conclusion: There is no single perfect method to assess agreement and reliability; however researchers should be aware of the inappropriate methods that they should avoid when analysing data in method comparison studies. Inappropriate analysis will lead to invalid conclusions and thus validated instrument might not be accurate or reliable. Consequently this will affect the quality of care given to a patient.
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Objective: The self-monitoring of blood glucose plays a critical role in management of diabetes mellitus. Although laboratory comparisons of glucose meter accuracy are often acceptable, clinical comparisons show frequent inaccuracies. In this paper, we evaluate the accuracy of self-monitoring blood glucose meters using glucose meter and serum comparisons from a large Canadian laboratory. Methods: This study was performed using secondary data obtained from the Laboratory Information System of Calgary Services, the sole provider of laboratory testing to Calgary and surrounding areas. We examined anonymous quality assurance data for glucose meter comparisons performed on home glucose meters between January 1, 2010, and April 30, 2013. Results: A total of 39 542 comparisons were recorded on 18 540 different subjects. Overall, 6.7% of differences were greater than the current International Standards Organization standard of 15%, and 3.7% exceeded the Canadian guideline of 20%. Conclusions: Glucose meter checks were infrequently performed (on average, once per 1.6 years). A significant subset of meter results was inaccurate.
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In vitro starch digestibility assays are more reproducible and less expensive than in vivo assays and are therefore important tools which assist breeding cereal cultivars with desirable starch digestibility. However, current in vitro starch digestibility assays often use non‐mammalian digestive enzymes combined with the glucose oxidase peroxidase colourimetric (GOC) method of glucose detection which requires multiple steps. A new, simple, in vitro rice starch digestibility assay was developed by trialling several combinations of mammalian digestive enzymes and comparing blood glucose meter based glucose detection methods with the classic GOC method. The glucometer based detection methods had wider glucose concentration detection windows with good reproducibility compared with the GOC method. Digestion with a rat intestinal acetone powder (RIAP) alone was comparable (R²>0.99) with digestion using a combination of α‐amylase, pepsin, pancreatin and RIAP. The optimised in vitro starch digestibility assay correctly estimated the digestibility of rice samples which differed by in vivo glycaemic index (GI). This rapid accurate assay only requires a small quantity of sample (15 mg) and can meet the high‐throughput phenotyping requirement of breeding programs in order to develop healthy cereal grains such as low GI rice.
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El objetivo de este estudio fue determinar la utilidad de glucómetros en relación al método de laboratorio estándar (MEL) en muestras sanguíneas: saludables, diabéticas, eritrociticas y anémicas. Los glucómetros (GM) evaluados fueron ACCU CHEK Active en sus dos procedimientos (ACCU I y ACCU II), ONE TOUCH Ultra (ONETu) y TRUEread fácil (TRUEf). Se utilizó el análisis de varianza ANOVA, p<0.005. De 54 muestras saludables con hematocrito 49±4, ONETu no expuso diferencia significativa con MEL, ACCU I, ACCU II y TRUEf expusieron diferencias significativas, siendo TRUEf el que reveló mayor diferencia con valores sobreestimados en más de 30 mg/dL. De 60 muestras diabéticas con hematocrito 48±8, no hubo diferencias significativas entre los GM y MEL, sin embargo se detectaron resultados incongruentes de 2 a 3 veces sobreestimados (13%) y de 2 a 3 veces infravalorados (12%) con los GM ONETu y TRUEf; ACCU I y ACCU II expusieron incongruencias leves. De 54 muestras eritrociticas con hematocrito 66±6, se detectaron valores infravalorados en 20 mg/dL con ONETu y TRUEf (10%), ACCU I (18%); ACCU II reporto valores sobreestimados entre 15-25 mg/dL (40%) con diferencia estadística significativa. De 40 muestras anémicas con hematocrito 29±9, se reportó valores sobreestimados, 20% (ONETu), 35% (TRUEf), 45% (ACCU II) y 55% (ACCU I), con una diferencia mayor a 20 mg/dL. Los GM evaluados presentan diferentes grados de interferencia por muestras diabéticas, anémicas y eritrociticas, en el caso de muestras eritrociticas se observan valores infravalorados, en muestras anémicas valores sobrevalorados, estos datos deben ser considerados para un mejor uso de los GM.
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Examinations performed beside the bed of patients ("Point-of-care testing, POCT") provide immediate results and are simple to perform. The most common of these tests is the self control of blood glucose levels in diabetic patients. The use of these devices at the hospital level, introduces a new set of requirements to health institutions, which should monitor all aspects of the process, including training of final users, proper quality control, development of written procedures for use and even participation in surveys of external quality control, avoiding the generation of errors and guaranteeing patient safety.
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Although the scientific literature contains numerous reports of the statistical accuracy of systems for self-monitoring of blood glucose (SMBG), most of these studies determine accuracy in ways that may not be clinically useful. We have developed an error grid analysis (EGA), which describes the clinical accuracy of SMBG systems over the entire range of blood glucose values, taking into account 1) the absolute value of the system-generated glucose value, 2) the absolute value of the reference blood glucose value, 3) the relative difference between these two values, and 4) the clinical significance of this difference. The EGA of accuracy of five different reflectance meters (Eyetone, Dextrometer, Glucometer I, Glucometer II, Memory Glucometer II), a visually interpretable glucose reagent strip (Glucostix), and filter-paper spot glucose determinations is presented. In addition, reanalyses of a laboratory comparison of three reflectance meters (Accucheck II, Glucometer II, Glucoscan 9000) and of two previously published studies comparing the accuracy of five different reflectance meters with EGA is described. EGA provides the practitioner and the researcher with a clinically meaningful method for evaluating the accuracy of blood glucose values generated with various monitoring systems and for analyzing the clinical implications of previously published data.
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To evaluate the clinical and analytical accuracy of home blood glucose meters. Six blood glucose meters--Reflolux S (Boehringer Mannheim, Mannheim, Germany), One Touch II (LifeScan, Milpitas, CA), Glucocard Memory (Menarini, Florence, Italy), Precision QID (Medisense, Cambridge, U.K.), HaemoCue (HaemoCue, Angelholm, Sweden), and Accutrend alpha (Boehringer Mannheim, Mannheim, Germany)--were compared with a reference method (Beckman Glucose Analyzer II) under controlled conditions (glucose clamp technique). Validation of the blood glucose meters was accomplished by clinically oriented approaches (error grid analysis), statistical approaches (variance components analysis), and by the criteria of the American Diabetes Association (ADA), which recommend a target variability of < 5%. A total of 1,794 blood glucose monitor readings and 299 reference values ranging from 2.2 to 18.2 mmol/l were analyzed (705 readings < 3.89 mmol/l, 839 readings between 3.89 and 9.99 mmol/l, and 250 readings > 9.99 mmol/l). According to error grid analysis, only Reflolux S and Glucocard M had 100% of estimations within the clinically acceptable zones A and B. Assessment of analytical accuracy revealed substantial differences between the glucose meters after separation of the data into defined glycemic ranges. None of the devices met the ADA criteria. To evaluate accuracy of blood glucose meters, error grid analysis, as well as statistical models, are helpful means and should be performed together. Analytical performance of currently available home blood glucose meters differs substantially within defined glycemic ranges.
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Newer glucose meters are easier to use, but direct comparisons with older instruments are lacking. We wished to compare analytical performances of four new and four previous generation meters. On average, 248 glucose measurements were performed with two of each brand of meter on capillary blood samples from diabetic patients attending our outpatient clinic. Two to three different lots of strips were used. All measurements were performed by one experienced technician, using blood from the same sample for the meters and the comparison method (Beckman Analyzer 2). Results were evaluated by analysis of clinical relevance using the percentage of values within a maximum deviation of 5% from the reference value, by the method of residuals, by error grid analysis, and by the CVs for measurements in series. Altogether, 1987 blood glucose values were obtained with meters compared with the reference values. By error grid analysis, the newer devices gave more accurate results without significant differences within the group (zone A, 98-98.5%). Except for the One Touch II (zone A, 98.5%), the other older devices were less exact (zone A, 87-92.5%), which was also true for all other evaluation procedures. New generation blood glucose meters are not only smaller and more aesthetically appealing but are more accurate compared with previous generation devices except the One Touch II. The performance of the newer meters improved but did not meet the goals of the latest American Diabetes Association recommendations in the hands of an experienced operator.
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To assess and compare the technical accuracy of portable glucose meters during the last decade. One-thousand preprandial (pre) and postprandial (post) capillary whole-blood glucose values measured with meters owned mainly by diabetic patients were compared with a single laboratory method yearly from 1989 to 1999. A total of 21,950 capillary measurements and their corresponding laboratory reference values were analyzed at our clinic. The lowest mean absolute difference was found in 1989 (pre: 2 +/- 22 mg/dl, post: 9 +/- 31 mg/dl) (mean +/- SD). The highest mean absolute difference was observed in 1993 (pre: 31 +/- 33 mg/dl) and 1996 (post: 50 +/- 35 mg/dl). The highest mean relative deviation was observed in 1990 (pre: 16.4%) and 1996 (post: 20.6%). The highest percentage of readings that were within a 5% deviation limit were observed in 1998 (pre: 44.5%) and in 1997 (post: 36.7%). Based on blood glucose levels within +/-5 and +/-10% of laboratory values, the technical accuracy of meters was similar for 1989 and 1999 (P = 0.27 and 0.52, respectively). The percentage of pre values in zone A of Clarke's error grid analysis was >90% in 1989, 1997, 1998, and 1999. The analytical performance of glucose meters decreased between 1990 and 1996 but was restored between 1997 and 1999. Nevertheless, our data suggest that the technical accuracy of glucose meters has not significantly improved during the last decade. Complementary studies taking into account the preanalytical improvements of the recent meters, as well as their calibration method, appear necessary.
Article
A new generation of blood glucose meters is now available for use by people with diabetes and health professionals, but little independent evaluation data is available. Previous models are prone to a variety of errors. We compared the accuracy, precision and features of the six latest meters available in Australia as of 1996. Meters studied were the Mini-Accutrend and Advantage (Boehringer Mannheim), Precision QID and Companion 2 (MediSense), Glucometer Elite (Bayer) and Lynx (National Diagnostic Products). We measured the blood glucose levels of 50 people with diabetes with these meters, and compared them to a reference method (YSI glucose analyser). Error grid analysis confirmed that accuracy of all meters was sufficient for their intended use as patient monitors. Precision was assessed using 25 samples from control solutions provided for each meter, and the coefficient of variation calculated. Improvements in strip and meter technology in some models have increased ease of use and reduced the likelihood of user error. This study, when considered with individual preferences for various features and price should assist patients in choosing a new blood glucose meter.
Article
When comparing a new method of measurement with a standard method, one of the things we want to know is whether the difference between the measurements by the two methods is related to the magnitude of the measurement. A plot of the difference against the standard measurement is sometimes suggested, but this will always appear to show a relation between difference and magnitude when there is none. A plot of the difference against the average of the standard and new measurements is unlikely to mislead in this way. We show this theoretically and by a practical example.
Article
In a quality review of glucose monitors, we measured the inaccuracy and imprecision of 26 systems. In each case, measurements on at least 50 capillary specimens from diabetic patients were compared with results from capillary blood that had been deproteinized and assayed with hexokinase. We also tested the monitors with commercial control solutions. In patients' specimens having a mean blood glucose concentration of about 9 mmol/l, the bias of the 26 monitors ranged from -5.1 to +20.1% (median=+7.5%). Imprecision of the monitors with blood specimens gave coefficients of variation (CV) ranging from 4.5% to 22.8% (median=8.7%) at the mean glucose concentration. A control solution for the monitors gave a glucose concentration of 7.6-13.6 mmol /l (median=9.2 mmol/l) with CV that varied from 1.7 to 19.8% (median=4.7%). While the means and CV's of the control were significantly correlated with bias and imprecision of the blood specimens, much of the variance remained unexplained (for bias, r(2)=0.17; for imprecision, r(2)=0.43). We conclude that a common basis for calibration could remove a significant component of variation and that control solutions may give a false impression of analytical performance.
Article
Glucometry is an essential part of diabetes treatment, but so far, no standard quality control procedure verifying blood glucose meter results is available. In this study, we evaluated the analytical performance of eight glucose meters: GX and Esprit (Bayer Diagn.), MediSense Card Sensor, ExacTech (MediSense) with strips Selfcare (Cambridge Diagn), One Touch Basic, One Touch II, One Touch Profile (Lifescan) and Glucotrend (Boehringer Mannheim/Roche). The evaluation included within-run imprecision, linearity, comparison with the laboratory method and calculation of differences between individual glucometers. Within-run imprecision ranged from 1.5% to 4.5%, linearity assessed as the correlation between measured and calculated glucose concentrations yielded r(2) values from 0.97 to 0.981. Analytical bias of glucose concentration values obtained by the glucometry amounted from 0.14% to 16.9% of values measured by the laboratory method. Bias higher than 5% was found for One Touch Basic, II and Profile meters (however, glucose concentrations in plasma obtained by the laboratory method One Touch meters showed analytical bias from 3.0% to 8.8%). The regression analysis yielded slope values from 0.77 to 1.09 and r(2) values from 0.86 to 0.98. The best correlations with the laboratory method were found for One Touch Basic, II Profile, Glucotrend and Esprit meters. The calculated differences between the individual glucose meters can constitute 0.02-1.49 mmol/l (0.96-26.9%) at glucose concentration 5.55 mmol/l, and 0.16-4.16 mmol/l (0.96-24.96%) at glucose concentration 16.67 mmol/l. Error grid analyses have shown that Glucometers One Touch Basic and One Touch Profile yielded all results in zone A (acceptable). The remaining glucometers yielded 1-7% of results in zones B (insignificant errors), C or D (lack of detection and treatment). All studied glucometers had both small deviation from laboratory reference values (<10%) and high concurrence with results obtained by the laboratory method.
Article
The study was designed to assess the technical performance of three common glucometers (Glucometer Elite, Accutrend Alpha, One Touch Basic) marketed in Nigeria. This is with a view to assessing their suitability for use in this environment and to provide an informed opinion on the selection option. Venous blood, capillary blood, serum and plasma were assayed during the study. Precision, accuracy, linearity and effect of haemolysis and haematocrit were carried out on each glucometer. Simultaneous analysis using the laboratory reference method was also carried out where necessary. Intra-assay precision was between 1.4% (Glucometer Elite)-11% (One Touch Basic) while the interassay precision was best for the Accutrend Alpha with a CV of 1.9%. All three glucometers correlated excellently with laboratory values and the %deviation from laboratory values was 0.2-10.5%. The Glucometer Elite was the most portable and used the least volume of blood (5 ul). One Touch Basic Glucometer was the least affected by haemolysis. Haematocrit values less than 50% did not have any effect on the three glucometer readings. The technical performance of these three glucometers were found to be acceptable and are recommended for use by diabetic patients, emergency and intensive care units and antenatal clinics, subject to periodic assessment and calibration.
Evaluating clinical accuracy of systems for self-monitoring of blood glucose Comparing methods of measurement: why plotting difference against standard method is misleading
  • W L Clarke
  • D Cox
  • L A Gonder
  • Fredrick
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  • Goldstein D.E.
  • Little R.R.
  • Lorenz R.A.