{"title":"Sysmex XN 系列血液分析仪上的微红细胞、碎红细胞、血小板分布宽度、平均血小板体积和血小板-大细胞比可用于临床实践中的阻抗血小板计数反射测试。","authors":"Si Chen, Zhigang Mao, Shuang Wang, Jiamin Deng, Hongyan Liao, Qin Zheng","doi":"10.5858/arpa.2022-0030-OA","DOIUrl":null,"url":null,"abstract":"<p><strong>Context.—: </strong>Platelet (PLT) counting with impedance (PLT-I) is widely used but has low specificity. PLT counting with fluorescence (PLT-F), tested by the Sysmex XN series with high specificity, can be a complementary method to PLT-I.</p><p><strong>Objective.—: </strong>To identify red blood cell (RBC)- and PLT-related parameters as potential influencing factors for PLT-I and establish PLT reflex test rules with PLT-F.</p><p><strong>Design.—: </strong>We prospectively tested both PLT-I and PLT-F in all 3480 samples. In a development data set of 3000 samples, differences between the reflex and nonreflex groups were compared and influencing factors for PLT-I were identified by logistic regression. The area under the receiver operating characteristic (ROC) curve and cutoff values were obtained by ROC curve analysis. Validation was conducted in the remaining 480 samples (validation data set).</p><p><strong>Results.—: </strong>PLT-F showed comparable results with immunoplatelet counting. In logistic regression, increased micro-RBC absolute count (micro-RBC#), fragmented RBC absolute count (FRC#), PLT distribution width (PDW), mean PLT volume (MPV), PLT-large cell ratio (P-LCR), and immature PLT fraction absolute count (IPF#) were influencing factors for PLT-I. In ROC curve analysis, the cutoff values of micro-RBC#, FRC#, PDW, MPV, and P-LCR were 0.64 × 106/μL, 0.082 × 106/μL, 15.40 fL, 11.15 fL, and 33.95%, respectively. The areas under the ROC curve of micro-RBC# and FRC# were 0.77 and 0.79, respectively.</p><p><strong>Conclusions.—: </strong>Micro-RBC#, FRC#, PDW, MPV, P-LCR, and IPF# were factors affecting PLT-I. Among them, micro-RBC# and FRC# were the most impactful factors. From our study results, micro-RBC#, FRC#, MPV, PDW, and P-LCR can be used to establish reflex test rules for PLT counting in clinical work.</p>","PeriodicalId":8305,"journal":{"name":"Archives of pathology & laboratory medicine","volume":" ","pages":"61-67"},"PeriodicalIF":3.7000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Micro-Red Blood Cell, Fragmented Red Blood Cell, Platelet Distribution Width, Mean Platelet Volume, and Platelet-Large Cell Ratio on Sysmex XN Series Hematology Analyzers Can Be Used for the Reflex Test of Impedance Platelet Count in Clinical Practice.\",\"authors\":\"Si Chen, Zhigang Mao, Shuang Wang, Jiamin Deng, Hongyan Liao, Qin Zheng\",\"doi\":\"10.5858/arpa.2022-0030-OA\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Context.—: </strong>Platelet (PLT) counting with impedance (PLT-I) is widely used but has low specificity. PLT counting with fluorescence (PLT-F), tested by the Sysmex XN series with high specificity, can be a complementary method to PLT-I.</p><p><strong>Objective.—: </strong>To identify red blood cell (RBC)- and PLT-related parameters as potential influencing factors for PLT-I and establish PLT reflex test rules with PLT-F.</p><p><strong>Design.—: </strong>We prospectively tested both PLT-I and PLT-F in all 3480 samples. In a development data set of 3000 samples, differences between the reflex and nonreflex groups were compared and influencing factors for PLT-I were identified by logistic regression. The area under the receiver operating characteristic (ROC) curve and cutoff values were obtained by ROC curve analysis. Validation was conducted in the remaining 480 samples (validation data set).</p><p><strong>Results.—: </strong>PLT-F showed comparable results with immunoplatelet counting. In logistic regression, increased micro-RBC absolute count (micro-RBC#), fragmented RBC absolute count (FRC#), PLT distribution width (PDW), mean PLT volume (MPV), PLT-large cell ratio (P-LCR), and immature PLT fraction absolute count (IPF#) were influencing factors for PLT-I. In ROC curve analysis, the cutoff values of micro-RBC#, FRC#, PDW, MPV, and P-LCR were 0.64 × 106/μL, 0.082 × 106/μL, 15.40 fL, 11.15 fL, and 33.95%, respectively. The areas under the ROC curve of micro-RBC# and FRC# were 0.77 and 0.79, respectively.</p><p><strong>Conclusions.—: </strong>Micro-RBC#, FRC#, PDW, MPV, P-LCR, and IPF# were factors affecting PLT-I. Among them, micro-RBC# and FRC# were the most impactful factors. From our study results, micro-RBC#, FRC#, MPV, PDW, and P-LCR can be used to establish reflex test rules for PLT counting in clinical work.</p>\",\"PeriodicalId\":8305,\"journal\":{\"name\":\"Archives of pathology & laboratory medicine\",\"volume\":\" \",\"pages\":\"61-67\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of pathology & laboratory medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.5858/arpa.2022-0030-OA\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL LABORATORY TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of pathology & laboratory medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.5858/arpa.2022-0030-OA","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
Micro-Red Blood Cell, Fragmented Red Blood Cell, Platelet Distribution Width, Mean Platelet Volume, and Platelet-Large Cell Ratio on Sysmex XN Series Hematology Analyzers Can Be Used for the Reflex Test of Impedance Platelet Count in Clinical Practice.
Context.—: Platelet (PLT) counting with impedance (PLT-I) is widely used but has low specificity. PLT counting with fluorescence (PLT-F), tested by the Sysmex XN series with high specificity, can be a complementary method to PLT-I.
Objective.—: To identify red blood cell (RBC)- and PLT-related parameters as potential influencing factors for PLT-I and establish PLT reflex test rules with PLT-F.
Design.—: We prospectively tested both PLT-I and PLT-F in all 3480 samples. In a development data set of 3000 samples, differences between the reflex and nonreflex groups were compared and influencing factors for PLT-I were identified by logistic regression. The area under the receiver operating characteristic (ROC) curve and cutoff values were obtained by ROC curve analysis. Validation was conducted in the remaining 480 samples (validation data set).
Results.—: PLT-F showed comparable results with immunoplatelet counting. In logistic regression, increased micro-RBC absolute count (micro-RBC#), fragmented RBC absolute count (FRC#), PLT distribution width (PDW), mean PLT volume (MPV), PLT-large cell ratio (P-LCR), and immature PLT fraction absolute count (IPF#) were influencing factors for PLT-I. In ROC curve analysis, the cutoff values of micro-RBC#, FRC#, PDW, MPV, and P-LCR were 0.64 × 106/μL, 0.082 × 106/μL, 15.40 fL, 11.15 fL, and 33.95%, respectively. The areas under the ROC curve of micro-RBC# and FRC# were 0.77 and 0.79, respectively.
Conclusions.—: Micro-RBC#, FRC#, PDW, MPV, P-LCR, and IPF# were factors affecting PLT-I. Among them, micro-RBC# and FRC# were the most impactful factors. From our study results, micro-RBC#, FRC#, MPV, PDW, and P-LCR can be used to establish reflex test rules for PLT counting in clinical work.
期刊介绍:
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