ObjectiveTo investigate the feasibility of quantitative detection of WBC count and bacteria count with UF-1000i urinary sediment analyzer in rapid screening for urinary tract infection by receiver operator characteristic (ROC) curve. MethodsFrom August to December 2013, we used quantitative bacterial culture and UF-1000i automatic urine sediment analyzer respectively to examine asepsis urine specimens of 218 patients with suspected urinary tract infection. Among them, there were 95 males and 123 females, with an average age of 54.7 years old. ResultsAmong the 218 urinary samples, 65 were culture positive specimens. With positive urine culture as the gold standard for making ROC curve, the area under ROC curve for WBC count and bacterial numbers by UF-1000i urine sediment analyzer were respectively 0.839 and 0.894. The cut-off values of Youden index for optimal WBC cell count and bacterial count were ≥31.0/μL and 38.8/μL, respectively. When the above numbers were used as cut-off values, the WBC count sensitivity and specificity were 78.3% and 80.4%, the positive likelihood ratio was 3.99, and the negative likelihood ratio was 1.11. And the bacterial count sensitivity and specificity were 84.3% and 80.6%, the positive likelihood ratio was 4.30, and the negative likelihood ratio was 0.80. ConclusionUsing white blood cell count ≥31/μL and bacterial count ≥38.8/μL detected by UF-1000i urine sediment analyzer as the cut off values of noninvasive screening indexes has a very important value in screening for urinary tract infection in the early stage, determining whether there is a need for urine culture, and guiding clinical rational application of antibiotics
ObjectiveTo establish a comprehensive, appropriate quality control system on the Sysmex-XN series automatic blood cell analyzer to improve the reliability of blood cell count results. MethodsRoutine quality control was carried out every day, using high, normal and low levels of fresh whole blood controls offered by Sysmex. The results from the Sysmex online quality control was got timely. We monitored the variation of mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC) with the moving average method real-timely, and quality control was performed for fresh whole blood samples of patients once every two hours. ResultsEverything was under control, and the moving average was within the permitted range. ConclusionThe reliability of laboratory blood cell count results can be effectively improved by using this quality control system effectively and comprehensively on the Sysmex-XN automatic blood cell analyzer.
ObjectiveTo evaluate the complete blood count performance quality of Sysmex-XN automatic hematology analyzer. MethodsWe investigated the precision rate, residual contamination rate, analytic linearity range, and background counting of Sysmex-XN-B3 analyzer. ResultsThe inner and inter-group precision test showed that the inaccuracy of the analyzer was lower than the allowable standard of 1/4 (CLIA'88). The highest level of residual contamination rate was 0.12%, lower than the standard of manufacturer (≤1%). Linearity evaluation showed that the white blood cell count analytic linear range was from 0.51×109/L to 393.40×109/L, the red blood cell count analytic linear range was from 0.51×1012/L to 8.15×1012/L, the hemoglobin analytic linear range from 15.0 g/L to 244.5 g/L, and the platelet count analytic linear range was from 3.0×109/L to 2 072.5×109/L. Background counting was also lower than the standard of manufacturer. Comparison between the two different series of analyzers showed that the inaccuracy rate of Sysmex-XN-B3 was not only lower than the standard of National Center for Clinical Laboratories, but also lower than the standard of 1/2 (CLIA'88). ConclusionSysmex-XN automatic hematology analyzer has a high performance in capability evaluation. It is an excellent tool for routine hematologic blood examination.
Objective To detect the difference between the peroxidase (POX) by cytochemical staining and cytoplasm myeloperoxidase (cMPO) by flow cytometry in acute leukemia cells, and provide a more accurate basis for the classification of leukemia. Methods The positive rate of POX in acute leukemia cells was detected by cytochemical staining. The positive rate of cMPO in acute leukemia cells was detected by flow cytometry. Then the positive rate of POX and cMPO, and the positive cells score were analyzed. Results The positive rate and the positive cells scores between POX and cMPO in acute lymphoblastic leukemia were significantly different (P<0.05), the positive rate and the positive cells scores of POX were significantly higher than those of cMPO. The positive rate between POX and cMPO in acute non-lymphoblastic leukemia (ANLL) had significant differences (P<0.05), the positive rate of cMPO was higher than that of POX; but no difference was found between POX and cMPO positive cells scores in ANLL (P>0.05). In acute myelocytic leukemia (AML)-M1 subtype, significant difference was found in the positive rate between POX and cMPO (P=0.006); cMPO positive rate was significantly higher than that of POX, but the POX positive cells score was significantly higher than that of cMPO (P=0.001). There were no significances of positive rate and positive cells score in AML-M2, AML-M3, AML-M4, AML-M5 subtypes between POX and cMPO (P>0.05). Conclusions There are not major differences between positive rate of POX and cMPO, as well as the positive cells scores in acute leukemia, especially acute myelocytic leukemia. We can choose the better method according to the actual situation and the sensitivity requirements. The two methods should be replenished by each other and used alternately.