Julien Guy, Marie-C Béné, Ramon Simon Lopez, Marc Maynadié, Céline Row
{"title":"缺铁性贫血与地中海贫血的自动形态学鉴别。","authors":"Julien Guy, Marie-C Béné, Ramon Simon Lopez, Marc Maynadié, Céline Row","doi":"10.1002/jcla.70097","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Iron deficiency anemia (IDA) and hemoglobinopathies (HbP) are two frequent conditions characterized by microcytemia. Published criteria/scores discriminating these conditions with hematology analyzer parameters are not fully satisfactory. Although patients with HbP have been reported to have more red blood cells (RBC) with a target cell (TC) morphology than patients with IDA, obtaining TC percentages remains a time-consuming task since at least 1000 RBC must be examined.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Using the Mindray CAL 8000 2.0 0111 and MC-80 module, 152 microcytic samples from 51 patients with IDA and 101 with HbP were analyzed. Data from RBC parameters used in published scores were collected, as well as the percentages of target cells automatically provided by the MC-80.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Patients with IDA had significantly lower median hemoglobin level, red blood cell numbers, and mean corpuscular hemoglobin concentration than those with HbP, yet had more microcytes. Using TC percentages provided by the MC-80 module, receiving operator characteristic curves identified this parameter as the most discriminant to segregate patients with IDA or HbP. With a 0.4% threshold, this yielded a 74.2% sensitivity and 86.3% specificity, confirming that patients with HbP have significantly higher TC percentages.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>The automated identification and enumeration of abnormal RBC performed by Mindray MC-80 rapidly provides TC percentages, allowing for a fast discrimination between IDA and HbP in samples with microcytosis, orienting early towards confirmatory tests for these disorders. Moreover, this study confirms TC, which can obviously be obtained through other methods, as a robust parameter in this context.</p>\n </section>\n </div>","PeriodicalId":15509,"journal":{"name":"Journal of Clinical Laboratory Analysis","volume":"39 19","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcla.70097","citationCount":"0","resultStr":"{\"title\":\"Automated Morphologic Differentiation Between Iron Deficiency Anemia and Thalassemia\",\"authors\":\"Julien Guy, Marie-C Béné, Ramon Simon Lopez, Marc Maynadié, Céline Row\",\"doi\":\"10.1002/jcla.70097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Iron deficiency anemia (IDA) and hemoglobinopathies (HbP) are two frequent conditions characterized by microcytemia. Published criteria/scores discriminating these conditions with hematology analyzer parameters are not fully satisfactory. Although patients with HbP have been reported to have more red blood cells (RBC) with a target cell (TC) morphology than patients with IDA, obtaining TC percentages remains a time-consuming task since at least 1000 RBC must be examined.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>Using the Mindray CAL 8000 2.0 0111 and MC-80 module, 152 microcytic samples from 51 patients with IDA and 101 with HbP were analyzed. Data from RBC parameters used in published scores were collected, as well as the percentages of target cells automatically provided by the MC-80.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Patients with IDA had significantly lower median hemoglobin level, red blood cell numbers, and mean corpuscular hemoglobin concentration than those with HbP, yet had more microcytes. Using TC percentages provided by the MC-80 module, receiving operator characteristic curves identified this parameter as the most discriminant to segregate patients with IDA or HbP. With a 0.4% threshold, this yielded a 74.2% sensitivity and 86.3% specificity, confirming that patients with HbP have significantly higher TC percentages.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>The automated identification and enumeration of abnormal RBC performed by Mindray MC-80 rapidly provides TC percentages, allowing for a fast discrimination between IDA and HbP in samples with microcytosis, orienting early towards confirmatory tests for these disorders. Moreover, this study confirms TC, which can obviously be obtained through other methods, as a robust parameter in this context.</p>\\n </section>\\n </div>\",\"PeriodicalId\":15509,\"journal\":{\"name\":\"Journal of Clinical Laboratory Analysis\",\"volume\":\"39 19\",\"pages\":\"\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-09-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jcla.70097\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Laboratory Analysis\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jcla.70097\",\"RegionNum\":4,\"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":"Journal of Clinical Laboratory Analysis","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jcla.70097","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL LABORATORY TECHNOLOGY","Score":null,"Total":0}
Automated Morphologic Differentiation Between Iron Deficiency Anemia and Thalassemia
Background
Iron deficiency anemia (IDA) and hemoglobinopathies (HbP) are two frequent conditions characterized by microcytemia. Published criteria/scores discriminating these conditions with hematology analyzer parameters are not fully satisfactory. Although patients with HbP have been reported to have more red blood cells (RBC) with a target cell (TC) morphology than patients with IDA, obtaining TC percentages remains a time-consuming task since at least 1000 RBC must be examined.
Methods
Using the Mindray CAL 8000 2.0 0111 and MC-80 module, 152 microcytic samples from 51 patients with IDA and 101 with HbP were analyzed. Data from RBC parameters used in published scores were collected, as well as the percentages of target cells automatically provided by the MC-80.
Results
Patients with IDA had significantly lower median hemoglobin level, red blood cell numbers, and mean corpuscular hemoglobin concentration than those with HbP, yet had more microcytes. Using TC percentages provided by the MC-80 module, receiving operator characteristic curves identified this parameter as the most discriminant to segregate patients with IDA or HbP. With a 0.4% threshold, this yielded a 74.2% sensitivity and 86.3% specificity, confirming that patients with HbP have significantly higher TC percentages.
Conclusion
The automated identification and enumeration of abnormal RBC performed by Mindray MC-80 rapidly provides TC percentages, allowing for a fast discrimination between IDA and HbP in samples with microcytosis, orienting early towards confirmatory tests for these disorders. Moreover, this study confirms TC, which can obviously be obtained through other methods, as a robust parameter in this context.
期刊介绍:
Journal of Clinical Laboratory Analysis publishes original articles on newly developing modes of technology and laboratory assays, with emphasis on their application in current and future clinical laboratory testing. This includes reports from the following fields: immunochemistry and toxicology, hematology and hematopathology, immunopathology, molecular diagnostics, microbiology, genetic testing, immunohematology, and clinical chemistry.