Abstract
Background
Diabetes mellitus is a metabolic disease that is characterized by hyperglycemia. Blood glucose (BG) is helpful for the diagnosis and treatment of diabetes and an important part of the management of diabetes. Point‐of‐care testing (POCT) is generally used by patients themselves or medical personnel to monitor BG. The objective of this article was to evaluate the accuracy and consistency of POCT on venous blood samples and compare it with the central laboratory system to determine the reliability of POCT measurement results as diagnostic criteria.
Method
A total of 162 venous whole blood samples were pooled in this study, which included different concentrations and were determined by three POCT systems randomly. The results were compared with the central laboratory system, which uses the Glucose GOD‐PAP method (HITACHI 7600‐120). The accuracy was evaluated by the International Organization for Standardization (ISO) 15197:2013.
Result
Bland‐Altman and Passing‐Bablok regression analysis showed three POCT systems that were comparable with the reference method (0.65, 95% CI: −0.57 to 1.86, Y = −0.11 + 0.95X for ACCU‐CHEK®Performa; 0.40, 95% CI: −1.3 to 2.1, Y = 0.036 + 0.96X for ACCU‐CHEK®Active; 0.70, 95% CI: −0.44 to 1.83, Y = −0.073 + 0.95X for OneTouch ®UltraVue). According to ISO 15197:2013, all POCT systems showed 100% of the results within 0.83 mmol/l (15 mg/dl) at BG concentrations <5.55 mmol/l (100 mg/dl); 92%, 89.2%, and 95.7% of the measurement results within 15% at BG concentrations ≥5.55 mmol/l (100 mg/dl) for ACCU‐CHEK®Performa, ACCU‐CHEK®Active, and OneTouch®UltraVue, respectively.
Conclusions
The POCT system cannot replace the central laboratory system as a provider of a standard result in clinical diagnosis. It can only be used as a screening test.
Keywords: accuracy, blood glucose, clinical laboratory, point‐of‐care testing
Introduction
Point‐of‐care testing (POCT) is a technique that is used outside of the laboratory, and at the bedside, is operated by medical personnel, patients, and family, and provides rapid test results 1. It is generally used for cardiovascular disease, infectious disease, endocrine disease, eugenics, etc.
With the development of immune technology and molecular biological technology, POCT has been widely used in diagnosis and treatment to test blood glucose (BG), blood gasses, cardiac markers, hemoglobin, beta‐human chorionic gonadotropin (β‐HCG), electrolyte, complete blood count, hematocrit, parathyroid hormone, etc 2, 3. As it is simple to use and supplies rapid results, it might accelerate clinical decision‐making and improve patients' prognosis 4. The most widely‐used POCT system is for BG. Diabetes mellitus (DM) is a metabolic disease that is characterized by hyperglycemia. It is important to control BG effectively, and the dynamic monitoring of BG can control the progress of DM 5, 6. With the amazing increase in the prevalence of DM in China in recent years, China seems to be the country with the largest number of people with DM, which seriously endangers human health 7. As a consequence, the medical personnel and patients themselves widely use the POCT system to monitor BG concentrations in the management of DM.
For self‐monitoring of BG, the International Organization for Standardization (ISO) revised ISO 15197:2013 in May 2013. The requirement is more stringent than the standard of 15179:2003. At BG concentrations ≥5.55 mmol/l (100 mg/dl), the minimum error range of test results is within 15% and within 0.83 mmol/l (15 mg/dl) at glucose measurement results <5.55 mmol/l (100 mg/dl) 8. In many countries, guidelines for the clinical application of BG monitoring systems have been established to regulate diabetes' diagnosis and treatment, and promote the effective management of diabetes.
The main purpose of this study was to investigate the measurement accuracy on venous whole blood samples performed by three different series of POCT systems, and compare it with the central laboratory system. To evaluate system accuracy with the standard ISO 15197:2013, this standard will be mandatory compliance in 2016.
Materials and Methods
Experimental Specimens
This was a retrospective study comprising 162 volunteers (97 males and 65 females; median age, 47 years; range, 14–67 years). All study subjects were recruited from the First Affiliated Hospital of Guangxi Medical University, Guangxi, China. All the volunteers provided written informed consent and the study was approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. The blood samples were collected with NaF anticoagulation tubes (3.1 ml Draw; Sarstedt AG & Co., Nümbrecht, Germany), for which hematocrit values ranged between 34.5% and 54% and the range of glucose concentrations were 1.60–21.30 mmol/l. Each sample was divided into two parts; one was separated by centrifugation and measured by the central laboratory system, and the other was measured by the POCT system in whole blood.
POCT Systems
Three types of BG meter were included in our study. They are ACCU‐CHEK®Performa (Roche Diagnostics, Basel, Switzerland), ACCU‐CHEK®Active (Roche Diagnostics), and OneTouch®UltraVue (Johnson, Shanghai, China). In order to ensure the internal quality control of each test system, the control materials were tested with each batch of analyses, all reagents are provided by the kits. Respectively, 78, 54, and 30 specimens were measured by ACCU‐CHEK®Performa, ACCU‐CHEK®Active, and OneTouch®UltraVue. All the analyses were performed by the same operator.
Clinical Laboratory Measurement System
The clinical laboratory measurement system used the Glucose GOD‐PAP method with a Hitachi 7600‐120 analyzer (Hitachi Corp, Tokyo, Japan). A total of 162 specimens were measured by Hitachi 7600‐120, and all measurements were carried out in accordance with the requirements of the manufacturer.
Statistical Analysis
The Hitachi 7600‐120 was considered a reference method. The relationship between the POCT system and Hitachi 7600‐120 was evaluated by Passing‐Bablok regression analysis. Bland‐Altman analysis was used to identify the mean difference and 95% limits of the results of the BG between the POCT systems and Hitachi 7600‐120. The statistical software was MedCalc Software (version 13.3.1; MedCalc Software, Mariakerke, Belgium). The statistically significant level was P < 0.05.
Result
System Accuracy
In ISO 15197:2013, the requirement of the distribution of samples for system accuracy evaluation was proposed. According to the BG concentrations, samples were assigned to categories (Table 1). The requirement of accuracy had been revised. This standard reduces the error range of test results and enhances the minimum accuracy requirements (Table 2).
Table 1.
Standard ISO 15179:2013 Requirement of the Distribution of Samples for System Accuracy Evaluation
| Blood glucose range, mmol/l (mg/dl) | Requires capillary blood samples (%) | Requires fresh blood samples (%) |
|---|---|---|
| ≤2.77 (≤50) | 5 | 0 |
| >2.77 to 4.44 (>50 to 80) | 15 | At least 8 |
| >4.44 to 6.66 (>80 to 120) | 20 | 20 |
| >6.66 to 11.10 (>120 to 200) | 30 | 30 |
| >11.10 to 16.65 (>200 to 300) | 15 | 15 |
| >16.65 to 22.20 (>300 to 400) | 10 | At least 5 |
| >22.20 (>400) | 5 | 0 |
Table 2.
Standard ISO 15179:2013 System Accuracy
| Measurement range, mmol/l (mg/dl) | Minimum accuracy requirements, mmol/l (mg/dl) |
|---|---|
| <5.55 (100) | <±0.83 (±15) |
| ≥5.55 (100) | ±15% |
Statistical Result
The significant differences between the POCT system and Hitachi were confirmed by Passing‐Bablok regression. It ranged from −0.11 to 0.036 mmol/l for intercept A and from 0.95 to 0.96 for slope B. The regression equation was Y = −0.11 + 0.95X for ACCU‐CHEK®Performa, Y = 0.036 + 0.96X for ACCU‐CHEK®Active, and Y = −0.073 + 0.95X for OneTouch®UltraVue (Table 3, Fig. 1). Bland‐Altman analysis showed no significant bias between POCT and Hitachi, ranging from 0.4 to 0.7 (Table 3).
Table 3.
Relative Bias and Passing‐Bablok Regression Parameters for Point‐of‐Care Testing System and Hitachi
| System | Bias (95% CI, mmol/l) | Intercept A (95% CI) | Slope B (95% CI) | Regression, mmol/l |
|---|---|---|---|---|
| ACCU‐CHEK®Performa | 0.65 (−0.57 to 1.86) | −0.11 (−0.26 to 0.047) | 0.95 (0.95 to 0.97) | Y = −0.11 + 0.95X |
| ACCU‐CHEK®Active | 0.40 (−1.3 to 2.1) | 0.036 (−0.20 to 0.38) | 0.96 (0.92 to 1.00) | Y = 0.036 + 0.96X |
| OneTouch®UltraVue | 0.70 (−0.44 to 1.83) | −0.073 (−0.32 to 0.24) | 0.95 (0.90 to 0.98) | Y = −0.073 + 0.95X |
Bias‐relative bias according to Bland‐Altman.
Figure 1.
(A) Passing‐Bablok analysis between point‐of‐care testing systems and Hitachi 7600‐120, the regression equation was Y = −0.11 + 0.95X for ACCU‐CHEK®Performa. (B) A subplot for the regression analysis between ACCU‐CHEK®Active and Hitachi 7600‐120, Y = 0.036 + 0.96X. (C) A subplot for the regression analysis between OneTouch®UltraVue and Hitachi 7600‐120, Y = −0.073 + 0.95X.
Applying the criteria of ISO 15197:2013 to the whole range of BG concentrations, 94.9%, 92.6%, and 96.7% of the results were within 0.83 mmol/l (15 mg/dl) at glucose measurement results <5.55 mmol/l (100 mg/dl) and within 15% at glucose concentrations ≥5.55 mmol/l (100 mg/dl) for ACCU‐CHEK®Performa, ACCU‐CHEK®Active, and OneTouch®UltraVue, respectively. At BG concentrations <5.55 mmol/l (100 mg/dl), all systems showed 100% of measurement results within 0.83 mmol/l (15 mg/dl). At BG concentrations ≥5.55 mmol/l (100 mg/dl), 92%, 89.2%, and 95.7% of measurement results were within 15% for ACCU‐CHEK®Performa, ACCU‐CHEK®Active, and OneTouch®UltraVue, respectively (Table 4, Fig. 2).
Table 4.
System Accuracy Criteria of ISO 15197:2013
| System | Overall | <5.55 mmol/l | ≥5.55 mmol/l |
|---|---|---|---|
| ±0.83 mmol/l/±15% | ±0.83 mmol/l | ±15% | |
| ACCU‐CHEK®Performa | 74/78 (94.9%) | 28/28 (100%) | 46/50 (92%) |
| ACCU‐CHEK®Active | 50/54 (92.6%) | 17/17 (100%) | 33/37 (89.2%) |
| OneTouch®UltraVue | 29/30 (96.7%) | 7/7 (100%) | 22/23 (95.7%) |
Figure 2.
The absolute differences in measurement results between point‐of‐care testing systems and Hitachi 7600‐120. (A) A subrange plot of absolute differences for ACCU‐CHEK®Performa. (B) A subrange plot of absolute differences for ACCU‐CHEK®Active. (C) A subrange plot of absolute differences for OneTouch®UltraVue. Dashed lines: accuracy criteria of ISO 15197:2013.
Discussion
Diabetes is the long‐term existence of hyperglycemia that results in dysfunction in various tissues, especially the eyes, kidneys, heart, and blood vessels, and chronic nerve damage. Exact, reliable, and fast BG results are important for diagnostic and dynamic metabolic tests. They contribute to the accurate diagnosis of abnormal glucose metabolism and to control BG well 9.
This study showed that BG concentrations measured by venous whole blood was comparable with the reference method according to Bland‐Altman and Passing‐Bablok regression analysis. The result is similar to those of Guido et al. and Ye et al. 10, 11, both indicated that the POCT system was comparable with the central laboratory system in capillary blood and venous whole blood. Although the POCT can provide rapid measurement results, the type of specimen, interference factors, environmental conditions, and hematocrit may affect the results 12, 13, 14. In addition, the POCT system lacks strict quality control and a management system 3, 15. Furthermore, POCT is operated by non‐professional personnel, such as the patients, clinicians, and nurses. The above‐mentioned reasons may lead to the deviation of measurement results and then affect the clinical diagnosis and treatment. All of these demonstrated that the POCT system and central laboratory system were not interchangeable and the POCT system cannot replace the central laboratory system. In order to ensure the reliability of the measurement results, the POCT system should be compared with the central laboratory system regularly and calibrated efficiently.
The ISO 15197:2013 standard required at least 95% of the measurement results to be within 0.83 mmol/l or 15%. However, according to ISO 15197:2013, the measurement accuracy of the POCT systems, being 94.9%, 92.6%, and 96.7% for ACCU‐CHEK®Performa, ACCU‐CHEK®Active, and OneTouch®UltraVue, respectively, did not all meet the requirement. The same result was found for BG concentrations ≥5.55 mmol/l (100 mg/dl). With BG concentrations <5.55 mmol/l (100 mg/dl), the accuracy of all POCT systems meet the criteria of the ISO 15197:2013 standard. With the increase in BG concentrations, the rate of discrepancy increased. The result is contradicted with those of Guido et al. 10, who indicated that the POCT system meet the criteria of the ISO 15197:2013 standard. In order to ensure that POCT can be more effectively applied to auxiliary diagnosis, the operators should fully understand the factors affecting the detection results.
This study had some limitations. Firstly, the sample sizes were too small. A total of 162 specimens were included, with 78 were measured by ACCU‐CHEK®Performa, 54 were measured by ACCU‐CHEK®Active, and 30 were measured by OneTouch®UltraVue. Secondly, only venous whole blood was analyzed. To evaluate the accuracy of POCT system, tests in capillary blood was also needed. It was found that BG concentrations in capillary blood were higher than in venous whole blood 16. Thirdly, this study neglected the influence factors on measurement results, such as oxygen partial pressure, pH, the features of the POCT system, and so on.
In conclusion, our data indicated that the POCT system can only be used as a screening test for continuous, qualitative, or semi‐quantitative detection as a complement emergency measure to the central laboratory, instead of being used as a standard result in clinical diagnosis 17. If the POCT system is used in testing too low or too high BG concentrations in clinical diagnosis, it may mislead the diagnosis and treatment 18. Therefore, clinical application should be fully aware of the disadvantage of POCT, influencing factors, result analysis, etc. Meanwhile, the POCT system should be compared with the central laboratory and calibrated regularly to improve the accuracy of the results.
Huiping Wei and Fang Lan have contributed equally to this study and should be considered as co‐first authors.
Contributor Information
Xue Qin, Email: qinxue919@126.com.
Shan Li, Email: lis8858@126.com.
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