No abstract available.
Chemistry, Clinical

No abstract available.
Chemistry, Clinical

In 2016, the clinical chemistry proficiency-testing program consisted of 21 programs, including the general chemistry program of the Korean Association of External Quality Assessment Service. The general chemistry program consisted of 28 test items and was conducted using two level control materials four times per year. Based on the information and results for each test item entered by each institution, statistical analysis data according to test method, instrument, and reagent were reported. The report comprised a general statistics report showing the characteristics of all participating institutions and a separate institutional report showing the evaluation data of individual institutions. The statistics included the number of participating institutions and the mean, standard deviation, coefficient of variation, median, minimum, and maximum values for each group. Each report was composed of a table, histogram, and Levey-Jennings chart showing the statistics for each test item. The results of each institution and the statistics for each classification are presented in the table showing the statistics, and a standard deviation index is presented together with a method classification and a classification by reagent companies. A total of 14 items, including albumin, were evaluated by more than 1,000 institutions. There was no significant difference in the distribution of the measurement methods compared with those used in the previous year. The coefficient of variation showed a tendency to increase as the concentration of the level control material decreased and as the number of participating institutions decreased for each test item. Most of them showed a coefficient of variation within 10%. These statistical data will be useful when interpreting the survey results from the institutions and selecting a test method.
Chemistry ; Chemistry, Clinical* ; Classification ; Korea* ; Methods

BACKGROUND: To evaluate the stability and the precision of quality control materials for clinical chemistry analytes, we compared liquid quality control materials, Moni-Trol H (MAS Inc., Camarillo, CA, USA) with lyophilized and other liquid quality control materials. For urinalysis, liquid MAS UA Controls were compared with analyte affixed-strip type quality control materials. METHODS: Using Hitachi-7600 (Hitachi, Tokyo, Japan), we analyzed lyophilized Seronorm & Pathonorm (SERO AS, Billingstad, Norway) and Moni-Trol H for 26 commonly measured chemistry analytes for 3~4 weeks. Using Synchron CX-7 (Beckman Coulter Inc., Fullerton, CA, USA), liquid Decision (Beckman Coulter) and Moni-Trol H were compared for 12 emergency chemistry analytes. For urinalysis, MAS UA Controls were compared with Chek-Stix (Bayer, Elkhart, IN, USA). We evaluate the stability of analyte by regression coefficient and the imprecision by coefficient of variation. RESULTS: Moni-Trol H was more stable than Seronorm & Pathonorm and Decision. The imprecision was more evident with Moni-Trol H than the others, but the CVs of Moni-Trol H were within 10%. In urinalysis, all the results were within two semi-quantity levels with both MAS UA Control and Chek-Stix. CONCLUSIONS: The MAS quality control materials for common chemistry analytes and urinalysis showed good stability and comparable precision. The materials were efficient for laboratory use due to the advantage of human source based liquid form and long-term stability after preparation.
Chemistry* ; Chemistry, Clinical ; Emergencies ; Humans ; Quality Control* ; Urinalysis*

BACKGROUND: The amount of interference due to hemolysis, bilirubin, and lipemia can be measured on the AU5800 autoanalyzer (Beckman Coulter, USA) by spectrophotometry. This is reported as semi-quantitative indices, specifically H-index, I-index, and L-index, respectively. In this study, we evaluated the impact of interference using chemistry assays and established the concentration of interfering substances and HIL-index above which analytically significant interference exists, according to CLSI guidelines C56-A and EP7-A2. METHODS: Pooled sera including different concentrations of analytes were prepared and mixed with hemoglobin, bilirubin, or Intralipid. These samples were then tested for 35 clinical chemistry analytes by AU5800 and the bias based on interferent concentrations was computed. The interferent concentration above which significant interference exists was calculated from the 50% within-subject biological variation (desirable analytic goal), and the corresponding index was assigned. RESULTS: Among 35 items evaluated, interference was detected for 12 analytes by hemoglobin, 7 analytes by bilirubin, and 12 analytes by Intralipid. We proposed HIL-index₁ and HIL-index₂ for each analyte according to 2 different medical decision levels. HIL-index₁ and HIL-index₂ were considered more reasonable criteria than the HIL-index from the manufacturer's technical document (HIL-index(TD)). This is because HIL-index(TD) was empirically set to 5% or 10%, and had a wide tolerance range, which was not sufficient to reflect the presence of interference, compared to HIL-index₁ and HIL-index₂. CONCLUSIONS: We have demonstrated hemoglobin, bilirubin, and Intralipid interferences according to CLSI guidelines using the desirable analytic goal. Our results provide applicable information for Beckman Coulter automated chemistry analyzers.
Bias (Epidemiology) ; Bilirubin ; Chemistry ; Chemistry, Clinical ; Hemolysis* ; Hyperlipidemias* ; Jaundice* ; Spectrophotometry

BACKGROUND: Optimal operational efficiency requires specific technical solutions such as open, flexible, and adaptable space, suitable equipment requirements, and laboratory instrumentation that combine excellent analytical performance with a capacity for testing large panels in a high throughput manner, under rapid turnaround times. Thus, the aim of this study was to assess the analytical performance of the novel Roche-Hitachi cobas 8000 c702 Chemistry Autoanalyzer. METHODS: Precision, linearity, carry over, detection limits, and comparison studies were performed with 31 routine clinical chemistry tests according to the CLSI guidelines. Commercial quality chemistry control material (Lyphochek, Bio-Rad, USA) and patient sera were used as the test specimens. Unicel DxC instrument (Beckman Coulter, USA) was used as a control analyzer to evaluate the correlation. RESULTS: The total coefficients of variations (CVs) of almost all the analytes were between 0.4 and 4.1%, except for CO2 and ammonia. Excellent linearities were observed in the performance ranges used (r>0.99, slope, 0.961-1.048). Correlations with analogous tests ran on the Unicel DxC instrument were good, correlation coefficients ranging between 0.921 and 1.000. The carryover ranged from -0.216 to 0.481%. CONCLUSIONS: The Roche-Hitachi cobas 8000 c702 Chemistry Autoanalyzer showed satisfactory precision, linearity, carry over, detection limits, and high throughput capacity. The instrument performance correlated well with the Unicel DxC analyzer. We conclude that the balance of elevated throughput and optimal analytical performance should make Roche-Hitachi cobas c702 Chemistry Autoanalyzer suitable for very large clinical laboratories.
Ammonia ; Chemistry* ; Clinical Chemistry Tests ; Humans ; Limit of Detection

BACKGROUND: Results of automated clinical chemistry tests are affected by many factors including analytical variability. In 1976, the College of American Pathologists (CAP) Conference on the analytical goals in clinical chemistry recommended that analytical variability should be less than 1/4 of the appropriate biological variability to improve distinction between normal and diseased populations. This study is conducted to evaluate whether automated clinical chemisty analyses performed in our laboratory is in conformance with the CAP's recommendation. METHODS: Routine chemistry and electrolyte tests were performed using Hitachi 747 automatic analyzer on 22 healthy volunteers. Blood samples were obtained from the volunteers' same vein twice in one week interval to study the total variability. Serum samples from 12 subjects were tested in duplicate immediately after blood collection for within-run analytical variability; and samples from another 10 subjects were repeated after 6 hours for within-day analytical variability. Within-run analytical variability plus within-day analytical variability make total analytical variability. Biological variability was defined as the difference between total variability and the analytical variability. Finally, ratios of analytical and biological variabilities were calculated. RESULTS: The ratios of analytical and biological variabilities of uric acid, glucose, and K were less than 0.25. But ratios of BUN, PO4, alkaline phosphatase, total bilirubin, AST, cholesterol, ALT, Cl, and protein exceeded 0.25. The ratios of Na, Ca, albumin, CO2, and creatinine could not be calculated. CONCLUSIONS: It is suggested that the analytical processes of the automated clinical chemistry tests be improved so as to be in conformity with the CAP's recommendation.
Alkaline Phosphatase ; Bilirubin ; Chemistry ; Chemistry, Clinical* ; Cholesterol ; Clinical Chemistry Tests* ; Creatinine ; Glucose ; Healthy Volunteers ; Uric Acid ; Veins

Medical diagnostics plays a significant role in clinical decisions. The first medical laboratory test to be developed was urine analysis, in which urine properties were analyzed for diagnosis. Urine analysis has been long used as a routine laboratory test that was improved with the development of sampling and test methods. As the field of hematology progressed with the invention of the microscope, blood tests were developed. Demands for tests based on clinical chemistry have existed since the 17th century, and research using patient blood began in the 18th century. In the 20th century, with the development of the spectrophotometer, chemical analyses were performed for diagnostic purposes. With the appearance of cholera outbreaks, the identification of microorganisms was necessary for patient diagnosis, and the development of specific test methods contributed to microorganism detection in the laboratory. Blood transfusion, which started with blood collection in the 15th century, is currently used as a therapeutic method in medicine. Moreover, once the hypothesis of acquired immunity was proven in the 18th century, various methods for measuring immunity were developed. Molecular diagnosis, which was established during the 20th century after the presentation of Mendel's Genetic Laws in the 19th century, developed rapidly and became the predominant field in medical laboratory diagnostics. Thus, medical laboratory technology became an academic field, with foundations based on basic sciences. Modern medicine will further progress thanks to medical advancements, leading to an extension of average human lifespan up to 100 years. Laboratory medicine will provide significant support for this development.
Adaptive Immunity ; Blood Transfusion ; Chemistry, Clinical ; Cholera ; Diagnosis ; Disease Outbreaks ; Foundations ; Hematologic Tests ; Hematology ; History, Modern 1601- ; Humans ; Inventions ; Jurisprudence ; Medical Laboratory Science ; Methods ; Pathology, Molecular

Laboratory values change with age and interpreting laboratory results from elderly people using the reference intervals for younger adults may not be appropriate. The authors investigated the distribution patterns of routine chemistry values from elderly people to determine whether current reference intervals are also valid for elderly people. A total of 1,215 persons older than 65 years and 1,827 healthy adults below 65 years of age were evaluated. Blood samples were collected after an overnight fast and analyzed for chemistry tests. Computing the central 95th percentile showed that the total protein, albumin, ALP, LD, creatinine, uric acid, triglyceride, HDL-cholesterol, and electrolytes of elderly people were within the standard reference intervals used in our laboratory. For AST and ALT, the upper range of the central 95th percentile in the elderly population was found to be outside the common reference interval. However, the central 90th percentile values of AST and ALT were compatible with the common reference intervals. GGT, BUN, total cholesterol, LDL-cholesterol, and glucose showed higher values than the upper limits of the reference intervals. For common clinical chemistry tests, the common reference values in general should be applicable to elderly people, even though some parameters showed wider distributions in the elderly.
Adult ; Aged ; Chemistry, Clinical ; Cholesterol ; Clinical Chemistry Tests ; Creatinine ; Electrolytes ; Glucose ; Humans ; Reference Values ; Uric Acid

Motecular imaging provides a visualization of normal as well as abnormal cellular processes at a molecular or genetic level rather than at the anatomical level. Molecular imaging is rapidly emerging and a multidisciplinary field coordinating medicine, molecular cell biology, chemistry, pharmacology, genetics, biomedical engineering, and physics. Conventional medical imaging methods utilize the imaging signals produced by nonspecific physico chemical interaction. However, molecular imaging methods utilize the imaging signals derived from specific cellular or molecular events. Because molecular and genetic changes precede anatomical change in the course of disease development, molecular imaging can detect early events in disease progression. Molecular imaging includes images of proteomics, metabolism, cellular biologic processes as well as genetics. In a narrow sense, molecular imaging means genetic imaging using imaging reporter genes. We can image diverse cellular processes including gene expression, proteinprotein interaction, signal transduction pathway, and monitoring of target cell distribution (cancer cells, immune cells, and stem cells) by imaging reporter gene. Molecular imaging methods are classified as optical imaging, nuclear imaging and magnetic resonance imaging. Each imaging modalities have their advantages and weaknesses. In the near future, through molecular imaging we can understand basic mechanisms of disease, and diagnose earlier and, subsequently, treat earlier intractable diseases such as cancer, neuro degenerative diseases, and immunologic disorders.
Biomedical Engineering ; Chemistry ; Diagnostic Imaging ; Disease Progression ; Gene Expression ; Genes, Reporter ; Genetics ; Magnetic Resonance Imaging ; Metabolism ; Molecular Imaging ; Molecular Medicine ; Optical Imaging ; Pharmacology ; Proteomics ; Signal Transduction