With the development and popularization of current medical technology, blood cell analyzer has been widely used in the laboratory of primary hospitals. The practical experience shows that the blood cell analyzer has the advantages of simple operation, fast response, good repeatability and high data accuracy [1-2]. However, due to the limitation of its own detection principle, the blood cell analyzer will be affected by many internal and external factors in the clinical application. Especially for the detection of platelets, the counting results will be influenced by many factors, which has become one of the problems with more clinical reactions. From this point of view, how to make clear the influencing factors of blood cell analyzer in the process of detecting platelets and implement corresponding correction and control methods has attracted the attention and attention of medical workers. In this paper, 50 healthy people in 20 14 ~ 1-3 months were selected as the research object, and the results of platelet count were analyzed by blood cell analyzer, which were summarized as follows.
1 data and methods
1. 1 general information
From October14 to 1-3, 50 healthy subjects were selected as the research objects. The general data of all the selected subjects were analyzed retrospectively: 27 males and 23 females, aged 65438 0 ~ 72 years, with an average of (34.5 2.6) years.
1.2 method
The platelet count of all the selected people was detected by KX-2 1 automatic blood cell analyzer. Hemolytic agent and diluent are provided by Hysenmei Company. In fasting state, venous blood samples (blood sample dosage is 2 ml) and peripheral blood samples (blood sample dosage is 120 μl) were taken respectively, and stored and analyzed with 0. 15 mg EDTA anticoagulant tube. The instrument method and manual method are realized respectively. Perform three counting operations respectively, and take the average value as the final counting result.
1.3 observation index
Observe and compare the corresponding platelet counts in different time states by instrument method and manual method, and compare the detection results of platelet counts in venous blood and peripheral blood.
1.4 statistical processing
The data were statistically analyzed by SPSS 19.0 software. The measurement data were expressed by the mean standard deviation (x s), and t test was used for comparison. P & lt0.05 was statistically significant.
Two results
In the process of platelet counting by instrument method and manual method respectively, the data detected by instrument method is obviously lower than that by manual method in the state of instant determination, and the difference is statistically significant; Let's stand for10 p = ""> 0.05); After standing for 8 h, the data detected by instrumental method was significantly lower than that of the control group, and the difference was statistically significant, as shown in table 1. In the process of platelet counting in different blood sampling areas, the platelet count in venous blood was (165.15.9) ×109p = ""> 0.05).
3 discussion
Platelets in plasma are small, colorless and have high adhesion. When blood flows out from the damaged part of a blood vessel, once platelets come into contact with endothelial cells or tissue components of the damaged blood vessel, they are bound to adhere to the wall of the blood vessel quickly. In addition, in the process of using blood cell analyzer to detect platelets, plasma samples need to contact and react with the surface of anticoagulant tube, which eventually leads to a large number of platelets adhering to the inner wall of anticoagulant tube and aggregation reaction, resulting in the deviation of platelet count [3]. From this point of view, the number of platelets collected by both instrumental and manual methods is lower than the actual data. At the same time, the data of this study showed that there was no significant difference in platelet count between peripheral blood and venous blood (P & gt0.05). However, it should be noted that compared with venous blood, there are a lot of potential influencing factors in peripheral blood collection (including needle depth, blood collection speed, etc.). ), which will have an impact on the final platelet count results. Therefore, if conditions permit, it is recommended to collect venous blood samples to complete blood cell analysis. If peripheral blood must be used for analysis, the depth of needle insertion is 3 mm, and the blood sample naturally flows out to ensure the accuracy of platelet test data.
At the same time, related research reports show that: for anticoagulants, in the process of detecting platelets by blood cell analyzer, the types of anticoagulants will have a great influence on the detection results [4]. At present, the anticoagulant recommended by the International Chemical Standards Committee is EDTA dipotassium anticoagulant, and the application of this recommended anticoagulant can ensure the accuracy of the test results to the greatest extent. At the same time, the proportional relationship between blood and anticoagulant will also have a considerable impact on the detection quality. Relevant clinical studies have pointed out that when the proportion of blood to be tested is too high, anticoagulants can not form a matching relationship with it, which may lead to a small amount of blood clots in the plasma sample to be tested. However, the generation of tiny blood clots will inevitably lead to the blockage of blood cell analyzer, resulting in the deviation of test results. On the other hand, when the blood ratio is too low, the anticoagulant can not form a matching relationship with it, which is mainly manifested in the increase of the concentration, which drives the expansion and disintegration of platelets in plasma samples and produces a large number of fragments basically consistent with the size of platelets, resulting in deviation in the counting process [5-6].
At the same time, the data of this study showed that there were significant differences between the immediately measured data and the measured data after 8 hours (P < 0.05). This research data suggests that, on the one hand, anticoagulant is consistent with platelet adhesion and aggregation, and at the same time, it will lead to the change of platelet morphology from concave mode to spherical mode, and the volume will increase obviously, which will lead to the obviously low platelet measurement data under immediate computer test. In the placement of 10 p = "">; 0.05)。 At the same time, with the extension of storage time, platelet count has a certain downward trend, and there is a significant difference at 8 h, suggesting that determination time is also one of the key factors causing platelet count deviation.
Combined with relevant research data, the results are basically reliable and stable in the process of counting platelets by blood cell analyzer, whether for light scattering method or impedance method. However, for the objects with abnormal platelet morphology and obvious decrease, the counting results under different methods are often quite different. Therefore, under the influence of pathological factors, a large number of non-platelet particles will be produced in plasma, which will eventually lead to a false increase in counting results. At present, there are two kinds of methods to ensure accurate platelet count: the first kind is based on immunology, that is, anti-platelet antibodies in plasma samples are labeled by fluorescence; The second type is a measurement method based on laser scattering. Under the intervention of laser scattering counting, non-platelet particles are separated from platelets to ensure the accuracy of counting [7-8]. However, the above two methods have high cost and poor popularity. Therefore, the current audit method is mainly manual counting. Considering the counting accuracy of this method, an indirect counting method of platelets on blood smear can be added as a supplement. With the treatment of Agkistrodon halys, the red blood cell count 1000, and the corresponding platelet count. According to the ratio between them, the final data can be obtained in the way of platelet count/red blood cell count × red blood cell count [9- 10]. According to the implementation of the above measures and close contact with clinicians, we can eliminate the platelet count error and improve the accuracy of blood cell analysis.
To sum up, in practice, it is necessary to pay attention to the analysis and control of the influencing factors such as anticoagulant type, blood collection area and storage time, and if necessary, smear and direct count review, in conjunction with the close contact of clinicians, can achieve the purpose of eliminating platelet count errors and improving the accuracy of blood cell analysis.
refer to
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Guo Lili, Gu Ping, Zhang Kui, et al. Dynamic analysis of platelet detection in patients with EDTA-dependent pseudothrombocytopenia [J]. journal of clinical transfusion and laboratory medicine Medical Journal, 20 12,14 (3): 21214.
Wu Junxia, Fan Xianfeng, Xu Gan, et al. Clinical significance of blood coagulation index and platelet detection in patients with hepatolenticular degeneration [J]. journal of clinical transfusion and laboratory medicine Medical Journal, 20 1 1, 13 (3): 23 1-233.
Li Yong, Mu Yueyi, Xia Yonghui, et al. Application value of SysmexXE-5000 blood analyzer in platelet detection [J]. China Journal of Hemorheology, 201,21(2): 329-332,369.
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