OBJECTIVETo establish a method for simultaneous determination of 54 elements in whole blood by inductively coupled plasma mass spectrometry (ICP-MS).

METHODSThe whole blood sample was digested with nitric acid and hydrogen peroxide in a water bath at 90°C, and then analyzed by ICP-MS with 0.1% ethanol as an matrix-matching agent.

RESULTSA good linear relationship was achieved when the concentrations of the 54 elements in whole blood were in the standard range (all r >0.999). The recovery rate of the sample plus the standard was between 80% and 106%, and the relative standard deviation was less than 5%. The standard material of whole blood was determined and the results met the certification requirements.

CONCLUSIONThe method is simple, rapid, sensitive, and accurate. It is applicable for simultaneous determination of multi-elements in a large number of whole blood samples.

Blood Chemical Analysis ; methods ; Humans ; Metronidazole ; blood ; Spectrophotometry, Ultraviolet

OBJECTIVETo establish a method for simultaneous determination of 17 common pesticides in whole blood by solid phase extraction-gas chromatography-mass spectrometry (SPE-GC-MS).

METHODSWhole blood samples were treated by extraction with acetonitrile, and the obtained extract was cleaned up using an Oasis HLB SPE cartridge; pesticides were separated by GC and quantitatively analyzed by MS with selected ion monitoring.

RESULTSThe concentrations of 17 pesticides in whole blood were 1.0-5.0 mg/L, and the recovery rate was 41.3-102.1%, with a relative standard deviation of less than 10%in most pesticides. The 17 pesticides showed a good linear relationship between concentration and peak area within 0.5-5.0 mg/L, with a correlation coefficient of 0.9945-0.9994. The limit of detection and limit of quantification were 0.02-0.05 mg/L and 0.05-0.09 mg/L, respectively.

CONCLUSIONWith this method, 17 pesticides in whole blood can be well separated and determined. This method has high sensitivity, accuracy, and precision and can be used for identification and quantification of multiple pesticides in blood samples.

No abstract available.
Ascorbic Acid/*chemistry ; Blood Chemical Analysis/instrumentation/*methods ; Blood Glucose/*analysis ; Maltose/*chemistry

OBJECTIVETo evaluate the comparability and bias of the test results of two detection systems for serum procalcitonin (PCT) under the same laboratory condition.

METHODSAccording to the profile NCCLS-EP9-A, the two systems were used to detect PCT to obtain the correlation coefficient and the liner equation for evaluation of the test result bias.

RESULTS AND CONCLUSIONThe test results of PCT showed no significant difference between the two detection systems (P>005) with a kappa value greater than 0.75. The correlation coefficients of both systems were above 0.975, suggesting a consistency between them for clinical detection of PCT.

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

OBJECTIVETo investigate the sensitization effect of different chemical modifiers in the determination of indium in whole blood by graphite furnace atomic absorption spectrometry, and to develop a new method for the determination of indium in whole blood.

METHODSA mixture of 0.3% HNO3 (V/V) + 0.1% Triton X-100 (V/V) was used as a diluent, and a solution of 1 000 µg/ml Pd (NO3)2 + 3 000 µg/ml Mg (NO3)2 was used as modifier. After being diluted five times, the concentration of indium of the blood was directly determined by graphite furnace atomic absorption spectrometry.

RESULTSThe detection limit of the method was 0.33 µg/L, the linear range was 0.33~100.00 µg/L, the relative standard deviation was 1.43%~2.65%, and the recovery rate was 98.3%~105.3%.

CONCLUSIONThe method is simple and fast and has high recovery and precision, and it is suitable for the determination of indium in whole blood.

BACKGROUND: The Hb levels of prospective blood donors are usually determined using a finger prick test. A new noninvasive Hb device has the advantage of not causing any sampling pain. The purpose of this study was to evaluate the accuracy of the noninvasive Hb sensor and to compare its measurements with those of a currently used portable hemoglobinometer. METHODS: Hb was measured using a noninvasive Hb sensor (NBM-200; OrSense, Israel), a portable hemoglobinometer (HemoCue; HemoCue AB, Sweden), and an automated hematology analyzer (LH500; Beckman Coulter, USA). The correlations between Hb measurements taken by the NBM-200 and HemoCue with those by an automated hematology analyzer were assessed using intraclass correlation coefficients (ICCs). Hb measurements were compared among 3 different Hb level groups. RESULTS: The mean Hb values of 506 blood donors were 14.1 g/dL by the NBM-200, 14.0 g/dL by the LH500, and 14.3 g/dL by the HemoCue. The correlation between the LH500 and the NBM-200 was substantial (ICC=0.69), while that between the LH500 and the HemoCue agreed almost perfectly (ICC=0.86). CONCLUSIONS: The possibility to judge to be eligible for donors who are ineligible to donate was substantial when using NBM-200. Even though the NBM-200 has the apparent advantage of noninvasiveness, its use in pre-screening should be given meticulous attention. Since pre-donation testing is crucial to protecting donors' health, complete evaluation of the instrument should be performed prior to use.
Automation ; Biosensing Techniques/*instrumentation ; Blood Chemical Analysis/*instrumentation ; Blood Donors ; Donor Selection/*methods ; Female ; Hemoglobins/*analysis ; Humans ; Male ; Sensitivity and Specificity

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