Performance Evaluation of Two Kinds of Rapid Antigen Test Kits for Detection of COVID-19 Infection.

BACKGROUND: The diagnostic standard for COVID-19 infection is real-time reverse transcription-polymerase chain reaction (rRT-PCR) of nasopharyngeal swab and oropharyngeal swab specimens. Rapid antigen tests are cheaper and easier to use than the rRT-PCR method. Although the COVID-19 pandemic is settling down, seasonal epi¬demic is expected. In this study, the performance of two rapid antigen test kits was evaluated based on rRT-PCR test results. METHODS: A total of 346 residual samples was tested by the PowerChek SARS-CoV-2 Real-time PCR Kit or STAN-DARD M nCoV Real-Time-Detection kit, STANDARD Q COVID-19 Ag test kit (SQ RAT), and ND COVID-19 Ag test kit (ND RAT). RESULTS: Compared to rRT-PCR as the standard method, the SQ RAT test kit yielded 77.1% sensitivity (101/131) and 100% specificity (215/215), and the ND RAT yielded 89.3% sensitivity (117/131) and 100% specificity (215/ 215). Both RATs showed sensitivity greater than 85% in samples with RdRp gene Ct value less than 25. There was a false-negative case suspected of prozone phenomenon. CONCLUSIONS: Both RATs showed significant performance, but users should beware of the prozone phenomenon.

Quality improvement of outpatient clinical chemistry tests through a novel middleware-laboratory information system solution.

OBJECTIVES: Rapid and accurate laboratory tests are essential to support clinical decision-making. Despite the various efforts to control quality in the laboratory, our outpatient chemistry turnaround time (TAT) has deteriorated since 2018. Moreover, these difficulties have accelerated further due to the COVID-19 pandemic. Therefore, we aimed to improve laboratory work efficiency by identifying and eliminating the causes of reduced laboratory work efficiency. DESIGN & METHODS: We surveyed to identify tasks that reduce work efficiency. Based on our survey, a new-concept of work assistance middleware linked to laboratory information system (LIS) was developed. The middleware supports test end-time prediction, automatic real-time TAT monitoring, and urgent test requests so that medical technologists can focus on their chemistry tests. The developed middleware was used for 6 months in laboratory and outpatient clinics, and its effectiveness was evaluated. RESULTS: The median TAT for outpatient chemistry tests was reduced by 6.6 min, from 72.4 min to 65.8 min. And not only did the maximum TAT for the sample decrease from 353 min to 214 min, but the proportion of samples exceeding the TAT target (120 min) also decreased by 77%; from 2.00% in 2010 (1,905 out of 94,989 samples) to 0.46% in 2021 (453 out of 98,117 samples). 2,199 samples were urgently requested through middleware, and they were processed about 15% faster than other samples, effectively performing urgent tests. The test end-time prediction showed an error of 8.6 min in the evaluation using the MAE (Mean Absolute Error) index. CONCLUSIONS: Through this study, the quality and efficiency of the laboratory were improved, and while reducing the workload of medical staff, it contributed to enhancing patient safety and satisfaction.

Distinguishing nontuberculous mycobacterial lung disease and Mycobacterium tuberculosis lung disease on X-ray images using deep transfer learning.

BACKGROUND: Nontuberculous mycobacterial lung disease (NTM-LD) and Mycobacterium tuberculosis lung disease (MTB-LD) have similar clinical characteristics. Therefore, NTM-LD is sometimes incorrectly diagnosed with MTB-LD and treated incorrectly. To solve these difficulties, we aimed to distinguish the two diseases in chest X-ray images using deep learning technology, which has been used in various fields recently. METHODS: We retrospectively collected chest X-ray images from 3314 patients infected with Mycobacterium tuberculosis (MTB) or nontuberculosis mycobacterium (NTM). After selecting the data according to the diagnostic criteria, various experiments were conducted to create the optimal deep learning model. A performance comparison was performed with the radiologist. Additionally, the model performance was verified using newly collected MTB-LD and NTM-LD patient data. RESULTS: Among the implemented deep learning models, the ensemble model combining EfficientNet B4 and ResNet 50 performed the best in the test data. Also, the ensemble model outperformed the radiologist on all evaluation metrics. In addition, the accuracy of the ensemble model was 0.85 for MTB-LD and 0.78 for NTM-LD on an additional validation dataset consisting of newly collected patients. CONCLUSIONS: In previous studies, it was known that it was difficult to distinguish between MTB-LD and NTM-LD in chest X-ray images, but we have successfully distinguished the two diseases using deep learning methods. This study has the potential to aid clinical decisions if the two diseases need to be differentiated.

Frequency histograms of three high-sensitivity cardiac troponin assays in a reference population.

BACKGROUND: Cardiac troponin (cTn) values above the 99th percentile upper reference limit (URL) indicate myocardial injury. We established 99th percentile URLs for three high-sensitivity cTn (hs-cTn) assays (Beckman Coulter Access hs-cTnI, Abbott STAT hs-cTnI, and Roche Elecsys hs-cTnT) using a healthy population in Korea. METHODS: Each cTn value was measured by three assays and analyzed by dividing by gender and age. RESULTS: The frequency histograms of log-transformed cTn values for Beckman and Abbott assays exhibited a bell-shaped distribution. The 99th percentile URLs were 9.8, 17.4, and 17.3 ng/L in the total population; 10.9/9.0, 18.9/17.0, and 18.9/17.7 ng/L in the male/female population (p < 0.001 for all three assays); and 11.2/7.2, 19.9/14.5, and 22.7/9.3 ng/L in the older/younger population (p < 0.001 for all three assays) for Beckman, Abbott, and Roche assays, respectively. CONCLUSION: Among the three assays, bell-shaped distributions were observed in a frequency histogram of log-transformed cTn values for healthy population in Beckman and Abbott assays. Also, our findings show that the 99th percentile URLs for cTn levels vary not only by gender but age.

Comparison of ACCEL ELISA COVID-19 with Elecsys Anti-SARS-CoV-2 for Screening of COVID-19.

OBJECTIVE: Although real-time reverse transcription-PCR (RT-PCR) is the gold standard for diagnosing coronavirus disease 2019 (COVID-19), simpler and faster antibody detection tests can be complementary for diagnosis of COVID-19. To manage the COVID-19 pandemic, the need for serologic testing has increased. In this report, the newly developed antibody detection assays ACCEL ELISA COVID-19 (ACCEL) and Elecsys anti-SARS-CoV-2 (Elecsys) were evaluated. METHODS: Serum samples submitted for routine laboratory testing were analyzed (66 and 161 PCR-positive and PCR-negative samples). After the samples were aliquoted, antibody detection tests were performed using ACCEL and Elecsys assays. RESULTS: When detection of viral RNA using RT-PCR was set as the reference method for diagnosis of COVID-19, the sensitivity was 83.3% and 75.8, and the specificity was 96.9 and 99.4% in ACCEL and Elecsys, respectively. The true positivity rates of ACCEL and Elecsys assays were 57.1%/42.9%, 57.1%/28.6%, 77.8%/66.7%, and 97.1%/97.1% among the specimens collected ≤3, 4-7, 8-14, and >14 days after symptom onset, respectively. CONCLUSIONS: The ACCEL assay showed high sensitivity in samples collected within 7 days after symptom onset. Because many patients are asymptomatic in the early stage of SARS-CoV-2 infection, the ACCEL assay could be a good screening tool due to high sensitivity in the early stage of SARS-CoV-2 infection.

Development of machine learning model for diagnostic disease prediction based on laboratory tests.

The use of deep learning and machine learning (ML) in medical science is increasing, particularly in the visual, audio, and language data fields. We aimed to build a new optimized ensemble model by blending a DNN (deep neural network) model with two ML models for disease prediction using laboratory test results. 86 attributes (laboratory tests) were selected from datasets based on value counts, clinical importance-related features, and missing values. We collected sample datasets on 5145 cases, including 326,686 laboratory test results. We investigated a total of 39 specific diseases based on the International Classification of Diseases, 10th revision (ICD-10) codes. These datasets were used to construct light gradient boosting machine (LightGBM) and extreme gradient boosting (XGBoost) ML models and a DNN model using TensorFlow. The optimized ensemble model achieved an F1-score of 81% and prediction accuracy of 92% for the five most common diseases. The deep learning and ML models showed differences in predictive power and disease classification patterns. We used a confusion matrix and analyzed feature importance using the SHAP value method. Our new ML model achieved high efficiency of disease prediction through classification of diseases. This study will be useful in the prediction and diagnosis of diseases.

Comparison of the ASTA MicroIDSys and VITEK MS matrix-assisted laser desorption/ionization time-of-flight mass spectrometry systems for identification of clinical bacteria and yeasts.

The ASTA MicroIDSys system (ASTA, Suwon, Korea) is a newly developed Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) system for identification of microorganisms. We compared the performance of the ASTA MicroIDSys system with that of the VITEK MS system (bioMérieux, Marcy l'Etoile, France) for identifying clinical microorganisms. A total 2055 isolates including 1910 bacteria and 145 yeasts were tested. Among them, the VITEK MS correctly identified 1999 (97.3%) isolates to species level and 26 (1.3%) to the genus level. The ASTA MicroIDSys correctly identified 1988 (96.7%) isolates to species level and 28 (1.4%) to the genus level. The VITEK MS and ASTA MicroIDSys misidentified one isolate and four (0.2%) isolates, respectively, and provided no identification for 29 (1.4%) and 35 (1.7%) isolates, respectively. The performance of the ASTA MicroIDSys was comparable to that of the VITEK MS for identification of clinically relevant bacterial and yeast isolates.

Stromal cell-derived factor-1 as a serologic biomarker for the diagnosis of colon ischemia with chronic cardiovascular disease.

Colon ischemia (CI) is the most common ischemic disorder of the gastrointestinal tract. Although some markers of CI, such as procalcitonin and alkaline phosphatase, have been reported, few specific serum markers have been identified. We investigated whether serum stromal cell-derived factor-1 (SDF-1) is a specific marker of CI and clarified the relationship between serum SDF-1 level and CI according to a history of combined chronic cardiovascular disease (CVD).We measured SDF-1 level and other serological markers in 84 patients (control, n = 20; CI without chronic CVD, n = 21; chronic CVD without CI, n = 20; CI with chronic CVD, n = 23).Patients with CI were older than those without CI. There were more women in the CI groups than those without CI. At admission, SDF-1 level was significantly higher in patients having CI with chronic CVD (P < .001) than in other groups. SDF-1 level was significantly higher at admission than at discharge in patients having CI with chronic CVD (P < .001) but not in patients having CI without chronic CVD. SDF-1 level did not differ according to symptoms, involved sites, or duration of hospitalization. At a cutoff value of 0.5 pg/mL for the SDF-1 level in patients having CI with chronic CVD, the sensitivity and specificity for SDF-1 were 91.3% and 95%, respectively. The area-under-the-curve (AUC) value was 0.95. In the logistic regression analysis, an elevation of the SDF-1 level to >0.5 pg/mL was a significant indicator of CI with chronic CVD [odds ratio (OR), 114.914; 95% confidence interval, 10.51 to >999.999; P < .001].SDF-1 could be a useful early biomarker for the diagnosis of CI in patients with chronic CVD.

Development of Statistical Software for the Korean Laboratory Accreditation Program Using R Language: LaboStats.

BACKGROUND: In Korea, the Korean Laboratory Accreditation Program (KLAP) has set minimum standards for verification of clinical test performance. This verification process is time-consuming and labor-intensive when performed manually. We developed a free, statistical software program for KLAP, using the R language (R Foundation for Statistical Computing, Vienna, Austria). METHODS: We used CLSI guidelines for the algorithm. We built graphic user interfaces, including data input, with Embarcadero Delphi EX4 (Embarcadero Technologies, Inc., Texas, USA). The R Base Package and MCR Package for Method Comparison Regression were used to implement statistical and graphical procedures. RESULTS: Our program LaboStats has six modules: parallel test, linearity, method comparison, precision, reference interval, and cutoff. Data can be entered into the field either manually or by copying and pasting from an MS Excel worksheet. Users can print out precise reports. CONCLUSIONS: LaboStats can be useful for evaluating clinical test performance characteristics and preparing documents requested by KLAP.

Evaluation of AdvanSure AlloScreen Max Panel With 92 Different Allergens for Detecting Allergen-Specific IgE.

OBJECTIVES: The objective of this study was to examine the performance of AdvanSure AlloScreen Max with 92 different allergens compared to Polycheck Allergy and ImmunoCAP. The relationship of serum IgE concentration with the number and the highest class/level of positive allergen-specific IgEs was also examined. METHODS: A total of 406 serum samples were included in this study. Discrepant cases between AdvanSure AlloScreen Max and Polycheck Allergy underwent ImmunoCAP testing for allergen-specific IgE. RESULTS: Total agreement of the two multiple allergen simultaneous tests (MAST) was 92.5%. Compared to ImmunoCAP, total agreement rate was higher with AdvanSure AlloScreen Max (60.8%) than that with Polycheck Allergy (39.2%). Serum IgE concentration showed a significant and positive correlation with the number and the highest class/level of positive allergen-specific IgEs. CONCLUSIONS: A MAST assay panel containing as many allergens as possible would be more helpful in the allergen screening for patients with high serum IgE concentration.

Comparison between creatine kinase MB, heart-type fatty acid-binding protein, and cardiac troponin T for detecting myocardial ischemic injury after cardiac surgery.

BACKGROUND: Heart-type fatty acid-binding protein (H-FABP) is a cytoplasmic protein and is released form necrotic cardiac myocytes, as well as ischemic cardiac myocytes. In this study, we compared creatine kinase MB (CK-MB), H-FABP, and cardiac troponin T (cTnT) after coronary artery bypass grafting (CABG), heart valve surgery, or septal defect surgery to evaluate the difference in detecting myocardial injury between three markers. METHODS: A total of 69 patients (CABG, 32; valve surgery, 27; and septal defect surgery, 10) were prospectively enrolled. Blood samples were taken at specific intervals. RESULTS: Mean amount (AUC0-72h) of CK-MB and cTnT released for 72 h in the patients with valve surgery were 2446 h·ng/ml and 93.2 h·ng/ml, which were significantly larger than those in the patients with CABG or septal defect surgery (p < .05). Mean amount (AUC0-72h) of H-FABP released for 72 h in the patients with CABG was 1939 h·ng/ml, which was significantly larger than that in the patients with septal defect surgery (700.1 h·ng/ml) (p < .05). CONCLUSION: H-FABP would be a more useful marker for detecting myocardial ischemic injury than CK-MB and cTnT. CK-MB and cTnT would be more sensitive to myocardial injury with surgical trauma than with ischemic injury in the patients with cardiac surgery.

Comparison of Four Automated Carcinoembryonic Antigen Immunoassays: ADVIA Centaur XP, ARCHITECT I2000sr, Elecsys E170, and Unicel Dxi800.

BACKGROUND: Carcinoembryonic antigen (CEA) is one of the tumor markers available for evaluating disease progression status after initial therapy and monitoring subsequent treatment modalities in colorectal, gastrointestinal, lung, and breast carcinoma. We evaluated the correlations and differences between widely used, automated CEA immunoassays at four different medical laboratories. METHODS: In total, 393 serum samples with CEA ranging from 3.0 to 1,000 ng/mL were analyzed on ADVIA Centaur XP (Siemens Diagnostics, Tarrytown, NY, USA), ARCHITECT i2000sr (Abbott Diagnostics, Abbott Park, IL, USA), Elecsys E170 (Roche Diagnostics, Indianapolis, IN, USA), and Unicel DxI800 (Beckman Coulter, Fullerton, CA, USA), and the results were compared. Deming regression, Passing-Bablok regression, and Bland-Altman analyses were performed to evaluate the data correlation and % differences among these assays. RESULTS: Deming regression analysis of data from Elecsys E170 and UniCel DxI800 showed good correlation (y=3.1615+0.8970x). According to Bland-Altman plot, no statistically significant bias (-1.78 ng/mL [95% confidence interval: -4.02 to 0.46]) was observed between Elecsys E170 and UniCel DxI800. However, the relative differences of CEA concentrations between assays exceeded the acceptable limit of 30%. Regarding the agreement of positivity with cut-off value 5.0 ng/mL, ARCHITECT i2000sr and Elecsys E170 showed the highest agreement (95.2%), whereas ADVIA Centaur XP and ARCHITECT i2000sr showed the lowest agreement (70.7%). CONCLUSIONS: Agreements between automated CEA immunoassays are variable, and individual CEA concentrations may differ significantly between assays. Standardization of serum CEA concentrations and further harmonization are needed.

Pentraxin 3 and lipid profile status in pregnancy.

Hyperlipidaemia and hypercholesterolaemia are risk factors of atherosclerosis and cardiovascular disease. The reference range of lipids during pregnancy has not yet been clearly set. This study sought to measure lipid parameters and pentraxin (PTX) 3 levels in low-risk pregnant women. The participants had serial blood samples taken between their 6th-9th week, 10th-13th week, 14th-19th week, 24th-29th week and 35th-40th week (as long as there were no contractions), during the labour period, and 2 days after delivery. The same tests were carried out on cord blood after delivery. There were 116 participants, of which 72 were included in the study and 44 were excluded. Total-c, HDL-c, LDL-c, TG and PTX3 increased as the pregnancy progressed. During labour, Total-c, HDL-c, LDL-c and PTX3 increased, but TG decreased. After delivery, TG and PTX3 increased but other parameters decreased from the value measured during the 35th-40th week. This study measured changes in lipid profiles and PTX3 during pregnancy, labour and after delivery, establishing a foundation for future studies.

Usefulness of biological variation in the establishment of delta check limits.

BACKGROUND: Biological variation is used in the calculation of reference change values (RCVs) for a delta check. In this study, we examined the correlation between intra-individual biological coefficients of variation (CVI) and delta check limits according to population distribution. METHODS: A total of 1,533,359 paired test results of nine routine chemistry tests were used to make the population distributions of delta percent changes. Their 0.5th, 2.5th, 97.5th, and 99.5th percentiles were then used for delta check limits. RESULTS: A large difference was observed between the chemistry tests in the percentage exceeding the delta check limits according to the RCVs. The mean percentage of test results of each test item exceeding the delta check limits of RCV95% ranged from 12.3% to 40.6%. Delta percent changes of protein, albumin, sodium (Na), potassium (K) and chloride (Cl) showed a symmetric distribution. However, an asymmetric distribution was observed in the delta percent changes of glucose, aspartate transaminase (AST), alanine aminotransferase (ALT) and creatinine. A good correlation was observed between CVI and the delta check limits according to population distribution and a closer correlation was observed when using the test items with CVI of <5.0%. CONCLUSIONS: Intra-individual biological coefficients of variation (CVI) would be useful for the establishment of delta check limits.

Evaluation of the Performance of Two Point-of-Care Analyzers for Total Cholesterol, Triglyceride, and High-Density Lipoprotein Cholesterol Analysis.

BACKGROUND: In this study, we evaluated the analytic performance of two POCT devices and compared the results with a central laboratory method. METHODS: A total of 100 patients were enrolled in this study. LipidPro (Infopia, USA) and LandMark (Infopia, Korea), were used for measuring total cholesterol (TC), triglyceride (TG), and high density lipoprotein cholesterol (HDL-C). Imprecision and linearity were assessed and the results of two POCT analyzers were compared with a central laboratory method. RESULTS: Imprecision of LipidPro met the National Cholesterol Education Program (NCEP) criteria (mean % CV: TC 2.8%, TG 3.9%, and HDL-C 4.0%). LandMark met the National Cholesterol Education Program (NCEP) imprecision criteria for TC and TG, but not HDL-C (mean % CV: 2.7%, 3.5%, and 4.7%, respectively). Both analyzers showed excellent linearity for TC, TG, and HDL-C in test ranges. Total errors of TC, TG, and HDL-C measured by LipidPro were 6.1%, 8.7%, and 8.1%, respectively, and met the NCEP goals. The total errors of TG and HDL-C measured by LandMark met the NCEP goals; however, the total error of TC analysis did not meet the NCEP goals (total error; TC 11.1%, TG 11.2%, and HDL-C 9.6%). CONCLUSIONS: LipidPro and LandMark are simple and rapid tests that provide a reliable alternative to conventional laboratory methods. The LipidPro device showed a slightly better analytical performance than LandMark based on the NCEP goals.

Direct Identification of Urinary Tract Pathogens From Urine Samples Using the Vitek MS System Based on Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry.

BACKGROUND: We evaluated the coincidence rate between Vitek MS system (bioMérieux, France) and Vitek 2 in identifying uropathogens directly from urine specimens. METHODS: Urine specimens submitted to our microbiology laboratory between July and September 2013 for Gram staining and bacterial culture were analyzed. Bacterial identification was performed by using the conventional method. Urine specimens showing a single morphotype by Gram staining were processed by culturing and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Of 2,370 urine specimens, 251 showed a single morphotype on Gram staining, and among them, 202 were available for MALDI-TOF MS. RESULTS: In these 202 specimens, colony growth was observed in 189 specimens, and 145 specimens had significant growth of single-colony morphotype in culture. One hundred and ten (75.9%) of them had colony counts of ≥10(5) colony-forming units (CFU)/mL and included 71 enteric gram-negative bacteria (GNB), 5 glucose-non-fermenting GNB, 9 gram-positive cocci (GPC), and 25 yeasts. Furthermore, 70 (98.6%), 3 (60.0%), 4 (44.4%), and 5 (20.0%), respectively, of these were correctly identified by Vitek MS. Thirty-one specimens (21.4%; 11 GNB, 7 GPC, 12 yeasts, and 1 gram-positive bacillus) had colony counts of 10(4)-10(5) CFU/mL. Four specimens (2.8%) yielded colony counts of 10(3)-10(4) CFU/mL. CONCLUSIONS: Vitek MS showed high rate of accuracy for the identification of GNB in urine specimens (≥10(5) CFU/mL). This could become a rapid and accurate diagnostic method for urinary tract infection caused by GNB. However, for the identification of GPC and yeasts, further studies on appropriate pre-treatment are warranted.

Polymorphisms of the heart-type fatty acid-binding protein as a prognostic factor in patients with atherosclerosis.

The amount of heart-type fatty acid-binding protein (FABP3) in cardiomyocytes may affect the prognosis of patients with coronary atherosclerosis. In this study, we examined whether single nucleotide polymorphisms (SNPs) of the FABP3 gene were prognostic factors in patients with coronary atherosclerosis. We enrolled 100 patients with myocardial infarction and coronary atherosclerosis and 100 healthy individuals to assess the genotypes of four SNPs of the FABP3 gene (RS2271072, RS16834408, RS2279885, and RS10914367). The MI patients with coronary atherosclerosis exhibited a higher frequency (16%) of the C/G-G/G haplotype of RS2271072 and RS10914367 than healthy individuals (7%). Koreans with the C/G-G/G haplotype for these SNPs had a higher risk of MI than did Koreans with the G/G-A/A haplotype. We calculated an odds ratio of 2.83 (95% confidence interval: 1.01-7.96). In conclusion, the C/G-G/G haplotype at RS2271072 and RS10914367 SNPs of FABP3 might be a prognostic factor in patients with coronary atherosclerosis.

Evaluation of enzymatic BM Test HbA1c on the JCA-BM6010/C and comparison with Bio-Rad Variant II Turbo, Tosoh HLC 723 G8, and AutoLab immunoturbidimetry assay.

BACKGROUND: A novel enzymatic HbA1c assay was introduced for use in an automated chemistry analyzer. With this unique method, HbA1c and plasma glucose can be measured from the same EDTA tube. We evaluated the analytical performance of this enzymatic HbA1c assay in a JCA-BM6010/C analyzer and compared the HbA1c values with the results from other widely used methodological instruments. METHODS: The imprecision, linearity, carry-over and concordance rate of the enzymatic HbA1c test (BM Test HbA1c) using the JCA-BM6010/C analyzer were evaluated. Three hundred and seventy-seven specimens with HbA1c concentrations from 16 to 133 mmol/mol were used for a comparison study with two high performance liquid chromatography methods: Variant II Turbo and Tosoh HLC 723 G8 and the AutoLab Hemoglobin A1c immunoturbidimetry reagent using a Hitachi 7600-110. Forty specimens were used for the glucose method comparison. RESULTS: The HbA1c coefficients of variation of the within-run imprecision for low and high levels were 0.6% and 0.4%, respectively. The linearity of the BM Test HbA1c using the JCA-BM6010/C analyzer was excellent in the range between 31 mmol/mol and 143 mmol/mol. The carry-over rate was 0.2%. The relationships between the BM test and the other three methods were 0.916×Tosoh G8+3.644, r=0.986; 0.887×Bio-Rad Variant II+1.896, r=0.972; and 0.941×AutoLab+4.532, r=0.977. The concordance rates using a cut-off of 48 mmol/mol were 91.5% with Tosoh G8, 82.8% with Bio-Rad Variant II, and 91.0% with AutoLab. The simultaneously assayed plasma glucose with HbA1c was 1.002×Routine plasma glucose+0.625, r=1.000 CONCLUSIONS: The enzymatic BM Test HbA1c in the JCA-BM6010/C analyzer showed excellent precision and linearity, and a minimal carry-over rate. The simultaneously assayed plasma glucose analysis showed good performance.