BACKGROUND: The purpose of this study was to evaluate the performance and agreement among HbA(1c) values measured using selected analyzers certified by the National Glycohemoglobin Standardization Program (NGSP) and standardized by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). METHODS: HbA(1c) determined using D-10 (Bio-Rad, USA), Variant II Turbo (Turbo; Bio-Rad, USA), Cobas Integra 800 (Integra; Roche, Switzerland) and Afinion AS100 (Afinion; Axis-Shield, Norway) were compared with each other. Precision and method comparisons with Deming regression were evaluated according to CLSI recommendations. We also compared the HbA(1c) values obtained with each analyzer using either IFCC or NGSP methods by correlation analysis and kappa statistics. RESULTS: The repeatability and method/device precisions of D-10 and Afinion were acceptable. The correlation coefficients of HbA(1c) were 0.986 for D-10 vs. Afinion, 0.997 for D-10 vs. Turbo, 0.988 for D-10 vs. Integra, and 0.991 for Integra vs. Afinion. The average biases of HbA(1c) Afinion (IFCC) and HbA(1c) Integra (IFCC) against HbA(1c) D-10 (NGSP) were -1.90% and -1.79%, respectively. Kappa agreement statistics for the three diabetic control group HbA(1c) values of "less than 6.5%," "6.5%-7.5%," and "greater than 7.5%" for D-10 vs. Turbo, D-10 vs. Integra, and D-10 vs. Afinion were 0.872, 0.836, and 0.833, respectively. CONCLUSIONS: The strong correlations and good clinical agreements of HbA(1c) between each analyzer expressed in terms of either NGSP or IFCC-derived NGSP indicate that these analyzers can be used interchangeably.
Blood Chemical Analysis/instrumentation/methods/standards ; Diabetes Mellitus/therapy ; Hemoglobin A, Glycosylated/*analysis/standards ; Humans ; Reproducibility of Results

BACKGROUND: Measurement uncertainty characterizes the dispersion of the quantity values attributed to a measurand. Although this concept was introduced to medical laboratories some years ago, not all medical researchers are familiar with it. Therefore, the evaluation and expression of measurement uncertainty must be highlighted using a practical example. METHODS: In accordance with the procedure for evaluating and expressing uncertainty, provided by the Joint Committee for Guides in Metrology (JCGM), we used plasma glucose (Glu) as an example and defined it as the measurand. We then analyzed the main sources of uncertainty, evaluated each component of uncertainty, and calculated the combined uncertainty and expanded uncertainty with 2 budgets for single measurements and continuous monitoring, respectively. RESULTS: During the measurement of Glu, the main sources of uncertainty included imprecision, within-subject biological variance (BVw), calibrator uncertainty, and systematic bias. We evaluated the uncertainty of each component to be 1.26%, 1.91%, 5.70%, 0.42%, and -2.87% for within-run imprecision, between-day imprecision, BVw, calibrator uncertainty, and systematic bias, respectively. For a single specimen, the expanded uncertainty was 7.38% or 6.1+/-0.45 mmol/L (kappa=2); in continuous monitoring of Glu, the expanded uncertainty was 13.58% or 6.1+/-0.83 mmol/L (kappa=2). CONCLUSIONS: We have demonstrated the overall procedure for evaluating and reporting uncertainty with 2 different budgets. The uncertainty is not only related to the medical laboratory in which the measurement is undertaken, but is also associated with the calibrator uncertainty and the biological variation of the subject. Therefore, it is helpful in explaining the accuracy of test results.
Blood Chemical Analysis/methods/standards ; Clinical Chemistry Tests/*methods/standards ; Glucose/*analysis/standards ; Humans ; Models, Statistical ; Quality Control ; *Uncertainty

BACKGROUND: Measurement uncertainty characterizes the dispersion of the quantity values attributed to a measurand. Although this concept was introduced to medical laboratories some years ago, not all medical researchers are familiar with it. Therefore, the evaluation and expression of measurement uncertainty must be highlighted using a practical example. METHODS: In accordance with the procedure for evaluating and expressing uncertainty, provided by the Joint Committee for Guides in Metrology (JCGM), we used plasma glucose (Glu) as an example and defined it as the measurand. We then analyzed the main sources of uncertainty, evaluated each component of uncertainty, and calculated the combined uncertainty and expanded uncertainty with 2 budgets for single measurements and continuous monitoring, respectively. RESULTS: During the measurement of Glu, the main sources of uncertainty included imprecision, within-subject biological variance (BVw), calibrator uncertainty, and systematic bias. We evaluated the uncertainty of each component to be 1.26%, 1.91%, 5.70%, 0.42%, and -2.87% for within-run imprecision, between-day imprecision, BVw, calibrator uncertainty, and systematic bias, respectively. For a single specimen, the expanded uncertainty was 7.38% or 6.1+/-0.45 mmol/L (kappa=2); in continuous monitoring of Glu, the expanded uncertainty was 13.58% or 6.1+/-0.83 mmol/L (kappa=2). CONCLUSIONS: We have demonstrated the overall procedure for evaluating and reporting uncertainty with 2 different budgets. The uncertainty is not only related to the medical laboratory in which the measurement is undertaken, but is also associated with the calibrator uncertainty and the biological variation of the subject. Therefore, it is helpful in explaining the accuracy of test results.
Blood Chemical Analysis/methods/standards ; Clinical Chemistry Tests/*methods/standards ; Glucose/*analysis/standards ; Humans ; Models, Statistical ; Quality Control ; *Uncertainty

Increasing evidence suggests an association between elevated serum aminotransferase level and the metabolic syndrome. However, the significance of relatively low levels of aminotransferase in relation to the metabolic syndrome has not been fully investigated in the general population. We investigated the association between serum amiontransferase level and the metabolic syndrome using data from a nationwide survey in Korea. We measured serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels and metabolic conditions among 9771 participants aged 20 or more in the 1998 and 2001 Korean National Health and Nutrition Examination Surveys. Metabolic syndrome was defined according to NCEP-ATP III criteria with a modified waist circumference cutoff (men > 90cm; women > 80cm). Serum aminotransferase level, even within normal range, was associated with the metabolic syndrome independent of age, body mass index, waist circumference, smoking, and alcohol intake. Compared with the lowest level (<20IU/L), the adjusted odds ratios (95% CI) for an AST level of 20-29, 30-39, 40-49 and > or = 50IU/L were 1.10 (0.85-1.42), 1.37 (1.02-1.83), 1.62 (1.08-2.43), and 2.25 (1.47-3.44) in men, and 1.18 (0.99-1.41), 1.43 (1.29-1.83), 1.71 (1.09-2.68), and 2.14 (1.20-3.80) in women, respectively. Corresponding odds ratios for ALT levels were 1.27 (0.99-1.63), 1.69 (1.28-2.23), 2.17 (1.58-2.99), and 2.65 (1.96-3.58) in men, and 1.44 (1.22-1.70), 1.65 (1.26-2.15), 2.94 (1.93-4.47), and 2.25 (1.54-3.30) in women, respectively. In conclusion, elevated serum aminotransferase levels, even in the normal to near normal range, are associated with features of the metabolic syndrome.
Reference Values ; Middle Aged ; Metabolic Syndrome X/*blood ; Male ; Korea ; Humans ; Female ; Blood Chemical Analysis/*methods/standards ; Aspartate Aminotransferases/*blood ; Alanine Transaminase/*blood ; Adult

BACKGROUND: Hemolysis, icterus, and lipemia (HIL) cause preanalytical interference and vary unpredictably with different analytical equipments and measurement methods. We developed an integrated reporting system for verifying HIL status in order to identify the extent of interference by HIL on clinical chemistry results. METHODS: HIL interference data from 30 chemical analytes were provided by the manufacturers and were used to generate a table of clinically relevant interference values that indicated the extent of bias at specific index values (alert index values). The HIL results generated by the Vista 1500 system (Siemens Healthcare Diagnostics, USA), Advia 2400 system (Siemens Healthcare Diagnostics), and Modular DPE system (Roche Diagnostics, Switzerland) were analyzed and displayed on physicians' personal computers. RESULTS: Analytes 11 and 29 among the 30 chemical analytes were affected by interference due to hemolysis, when measured using the Vista and Modular systems, respectively. The hemolysis alert indices for the Vista and Modular systems were 0.1-25.8% and 0.1-64.7%, respectively. The alert indices for icterus and lipemia were <1.4% and 0.7% in the Vista system and 0.7% and 1.0% in the Modular system, respectively. CONCLUSIONS: The HIL alert index values for chemical analytes varied depending on the chemistry analyzer. This integrated HIL reporting system provides an effective screening tool for verifying specimen quality with regard to HIL and simplifies the laboratory workflow.
Blood Chemical Analysis/instrumentation/*methods/standards ; Female ; Hemoglobins/analysis ; *Hemolysis ; Humans ; Hyperlipidemias/metabolism/*pathology ; Jaundice/metabolism/*pathology ; Male ; Quality Control ; Reproducibility of Results

BACKGROUND: Point-of-care (POC) tests are used increasingly due to fast results and simple test procedures, which enables rapid diagnosis and therapeutic monitoring. We evaluated the performance of the Piccolo xpress Chemistry Analyzer (Abaxis, USA) a POC chemistry analyzer. METHODS: Fourteen analytes, Na+, K+, Cl-, Ca2+, total carbon dioxide, AST, ALT, total bilirubin, alkaline phosphatase, blood urea nitrogen, creatinine, albumin, total protein, and glucose; were measured simultaneously with a 100 microliter of whole blood sample using a Comprehensive Metabolic Reagent disk. Within-run and total precision and linearity were evaluated according to CLSI EP15-A and EP6-A guidelines, respectively. Comparison with a central laboratory chemistry analyzer was performed using 144 patient samples. RESULTS: The coefficients of variations of within-run and total precision were all within 5% for three levels except for total carbon dioxide, ALT, alkaline phosphatase, total bilirubin, and creatinine in low level, and creatinine in middle level. The results of 14 analytes were linear within a commonly encountered range in clinical samples (r2> or =0.98). More than 10% of samples in Na+, AST, ALT, glucose, BUN did not satisfy CLIA analytical quality requirement. CONCLUSIONS: The Piccolo xpress Chemistry Analyzer can analyze multiple analytes with a minimal amount of whole blood in a short time. It showed an acceptable performance for precision, linearity and comparison with central laboratory analyzer. It can be useful as a screening tests modality in mobile clinics, ambulances, and field clinics for military use, and for pediatric patients from whom enough sample volume is difficult to obtain.
Alanine Transaminase/blood ; Alkaline Phosphatase/blood ; Aspartate Aminotransferases/blood ; Bilirubin/blood ; Blood Chemical Analysis/*instrumentation/methods/*standards ; Blood Glucose/analysis ; Calcium/blood ; Carbon Dioxide/blood ; Chlorides/blood ; Creatinine/blood ; Humans ; *Point-of-Care Systems ; Potassium/blood ; Quality Control ; Reproducibility of Results ; Serum Albumin/analysis ; Sodium/blood