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

Through the present delta value check used in quality control programs is a powerful tool for detecting random errors in clinical chemistry analysis, it has some problems, such as missed true errors and delays in reporting time, because it also has the potential of showing erroneous positive results. Recently, new calculation methods for delta check with delta difference, delta percent change, rate difference, and rate percent change have been suggested by Lacher and Connelly (Clin Chem 34:1966-1970, 1988). Based on this new delta check method, we made the new criteria of which calculation method is applied to the clinical chemistry tests, i.e., the differential application of rate and delta check, and selectively applied the new method to 17 chemistry tests in order to solve the above problems. The applied criteria were the time dependence of the test item and the coefficient of variation of the absolute delta difference. Calcium, inorganic phosphorus, total protein, albumin, sodium, potassium, and chloride were classified as delta difference calculation method group; glucose and cholesterol as delta percent change group; creatinine, total and direct bilirubin as rate difference group; and urea nitrogen, uric acid, ALP, ALT, and AST as rate percent change group. With the previous criteria by Whitehurst et al. (Clin Chem 221:87-92) for 5045 specimens, the check-out rate was 47.8% (2,411 out of 5,045), and the positive predictive value was 0.41% (10 out of 2,411). For the new criteria, the check-out rate was 12.7% (621 out of 5,045), and the positive predictive value was 1.8% (nine out of 621).(ABSTRACT TRUNCATED AT 250 WORDS)
Albumins/analysis ; Bilirubin/analysis ; Calcium/analysis ; Chemistry, Clinical/methods/*standards ; Clinical Laboratory Information Systems/*standards ; Creatine/analysis ; Glucose/analysis ; Phosphorus/analysis ; Quality Control ; Reference Values ; *Sensitivity and Specificity ; Specimen Handling ; Urea/analysis ; Work Simplification

OBJECTIVETo use the data of occupational epidemiology to estimate the benchmark dose (BMD) of renal dysfunction induced by lead.

METHODSBlood lead was considered as an exposure biomarker, while urinary total protein (TP), urinary beta(2)-microglobulin (beta(2)-MG) and urinary N-Acetyl-beta-D-glucosaminidase (NAG) were considered as effect biomarkers reflecting the damage of renal function. The dichotomized (binary) data was used as effect endpoints. The BMD and BMD lower limit (BMDL) of blood lead were estimated at the 10% benchmark response using BMDS version 1.3.1.

RESULTSThere was an increased prevalence of hyper-TP-uria, hyper-beta(2)-MG-uria and hyper-NAG-uria with an increasing blood lead concentration. There was obviously dose-response relationship between blood lead and TP, beta(2)-MG and NAG, respectively. The BMD and BMDL of blood lead affecting renal function were estimated to be 323.6 - 754.3 microg/L and 274.2 - 541.5 microg/L. The BMDL of blood lead was ranged from low to high as NAG, TP and beta(2)-MG. The urinary NAG activity might be served as a sensitive biomarker in detecting early renal dysfunction.

CONCLUSIONIt should be feasible to use the BMD approach to set up the reference dose (RfD) and reference concentration (RfC). BMD approach might provide a new and better way for setting up the RfD/RfC.

Acetylglucosaminidase ; urine ; China ; epidemiology ; Clinical Chemistry Tests ; methods ; standards ; Humans ; Lead ; blood ; Lead Poisoning ; blood ; epidemiology ; urine ; Occupational Exposure ; analysis ; Prevalence ; Proteinuria ; urine ; beta 2-Microglobulin ; urine

BACKGROUND: Many laboratories use 4 delta check methods: delta difference, delta percent change, rate difference, and rate percent change. However, guidelines regarding decision criteria for selecting delta check methods have not yet been provided. We present new decision criteria for selecting delta check methods for each clinical chemistry test item. METHODS: We collected 811,920 and 669,750 paired (present and previous) test results for 27 clinical chemistry test items from inpatients and outpatients, respectively. We devised new decision criteria for the selection of delta check methods based on the ratio of the delta difference to the width of the reference range (DD/RR). Delta check methods based on these criteria were compared with those based on the CV% of the absolute delta difference (ADD) as well as those reported in 2 previous studies. RESULTS: The delta check methods suggested by new decision criteria based on the DD/RR ratio corresponded well with those based on the CV% of the ADD except for only 2 items each in inpatients and outpatients. Delta check methods based on the DD/RR ratio also corresponded with those suggested in the 2 previous studies, except for 1 and 7 items in inpatients and outpatients, respectively. CONCLUSIONS: The DD/RR method appears to yield more feasible and intuitive selection criteria and can easily explain changes in the results by reflecting both the biological variation of the test item and the clinical characteristics of patients in each laboratory. We suggest this as a measure to determine delta check methods.
Alanine Transaminase/blood ; Alkaline Phosphatase/blood ; Aspartate Aminotransferases/blood ; Bilirubin/blood ; Blood Urea Nitrogen ; Chemoembolization, Therapeutic ; Clinical Chemistry Tests/methods/*standards ; Creatine/blood ; *Decision Trees ; Humans ; Reference Values ; Renal Dialysis ; Uric Acid/blood

BACKGROUND: Many laboratories use 4 delta check methods: delta difference, delta percent change, rate difference, and rate percent change. However, guidelines regarding decision criteria for selecting delta check methods have not yet been provided. We present new decision criteria for selecting delta check methods for each clinical chemistry test item. METHODS: We collected 811,920 and 669,750 paired (present and previous) test results for 27 clinical chemistry test items from inpatients and outpatients, respectively. We devised new decision criteria for the selection of delta check methods based on the ratio of the delta difference to the width of the reference range (DD/RR). Delta check methods based on these criteria were compared with those based on the CV% of the absolute delta difference (ADD) as well as those reported in 2 previous studies. RESULTS: The delta check methods suggested by new decision criteria based on the DD/RR ratio corresponded well with those based on the CV% of the ADD except for only 2 items each in inpatients and outpatients. Delta check methods based on the DD/RR ratio also corresponded with those suggested in the 2 previous studies, except for 1 and 7 items in inpatients and outpatients, respectively. CONCLUSIONS: The DD/RR method appears to yield more feasible and intuitive selection criteria and can easily explain changes in the results by reflecting both the biological variation of the test item and the clinical characteristics of patients in each laboratory. We suggest this as a measure to determine delta check methods.
Alanine Transaminase/blood ; Alkaline Phosphatase/blood ; Aspartate Aminotransferases/blood ; Bilirubin/blood ; Blood Urea Nitrogen ; Chemoembolization, Therapeutic ; Clinical Chemistry Tests/methods/*standards ; Creatine/blood ; *Decision Trees ; Humans ; Reference Values ; Renal Dialysis ; Uric Acid/blood