Diagnostic accuracy of reticulocyte parameters on the sysmex XN 1000 for discriminating iron deficiency anaemia and thalassaemia in Saudi Arabia.

American journal of blood research Pub Date : 2021-04-15 eCollection Date: 2021-01-01
Qanita Sedick, Ghaleb Elyamany, Huda Hawsawi, Sultan Alotaibi, Fahad Alabbas, Mohammed Almohammadi, Hassan A Alahmari, Hassan Aljasem, Arnel G Ferrer, Ahmed S Alzahrani, May AlMoshary, Omar Alsuhaibani
{"title":"Diagnostic accuracy of reticulocyte parameters on the sysmex XN 1000 for discriminating iron deficiency anaemia and thalassaemia in Saudi Arabia.","authors":"Qanita Sedick,&nbsp;Ghaleb Elyamany,&nbsp;Huda Hawsawi,&nbsp;Sultan Alotaibi,&nbsp;Fahad Alabbas,&nbsp;Mohammed Almohammadi,&nbsp;Hassan A Alahmari,&nbsp;Hassan Aljasem,&nbsp;Arnel G Ferrer,&nbsp;Ahmed S Alzahrani,&nbsp;May AlMoshary,&nbsp;Omar Alsuhaibani","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Iron deficient erythropoiesis and Thalassaemia are both associated with microcytic erythropoiesis albeit from different pathological mechanisms. Given the high prevalence of Hemoglobinopathies in the Mediterranean region, discriminating these two conditions is important. Several algorithms using conventional red cell indices have been developed to facilitate diagnosis, however, their diagnostic accuracy is low. The new generation haematology analyzers enabled the use of more innovative parameters such as reticulocyte parameters. We aimed to evaluate the diagnostic performance of the reticulocyte parameters on the Sysmex XN 1000 to distinguish between IDA and Thalassemia in our population.</p><p><strong>Methods: </strong>We performed a retrospective analysis of blood samples sent to our laboratory for haemoglobin electrophoresis screening. We categorized our cohort into Thalassemia and Iron Deficient patients based on known diagnostic criteria. We analyzed the reticulocyte parameters using receiver operator curve analysis (ROC) and determined the cut off value for each parameter.</p><p><strong>Results: </strong>Reticulocyte parameters most accurate for discriminating IDA from Thalassemia patients was: RET, RET-HE and IRF. The RET-HE had the best statistical significance for IDA patients with AUC = 0.69 for cut off 22.25. The RET-HE for dual positive patients was more accurate with AUC = 0.78 for cut off 21.25. The IRF had the best statistical significance for Alpha Thalassemia with AUC = 0.66 for cut off value 18.</p><p><strong>Conclusion: </strong>An IRF cut off below 15.5 and RET-HE cut off below 22.25 was the most accurate variable in predicting IDA with a sensitivity of 59.4% and 68.3%.</p>","PeriodicalId":7479,"journal":{"name":"American journal of blood research","volume":"11 2","pages":"172-179"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8165718/pdf/ajbr0011-0172.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of blood research","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Introduction: Iron deficient erythropoiesis and Thalassaemia are both associated with microcytic erythropoiesis albeit from different pathological mechanisms. Given the high prevalence of Hemoglobinopathies in the Mediterranean region, discriminating these two conditions is important. Several algorithms using conventional red cell indices have been developed to facilitate diagnosis, however, their diagnostic accuracy is low. The new generation haematology analyzers enabled the use of more innovative parameters such as reticulocyte parameters. We aimed to evaluate the diagnostic performance of the reticulocyte parameters on the Sysmex XN 1000 to distinguish between IDA and Thalassemia in our population.

Methods: We performed a retrospective analysis of blood samples sent to our laboratory for haemoglobin electrophoresis screening. We categorized our cohort into Thalassemia and Iron Deficient patients based on known diagnostic criteria. We analyzed the reticulocyte parameters using receiver operator curve analysis (ROC) and determined the cut off value for each parameter.

Results: Reticulocyte parameters most accurate for discriminating IDA from Thalassemia patients was: RET, RET-HE and IRF. The RET-HE had the best statistical significance for IDA patients with AUC = 0.69 for cut off 22.25. The RET-HE for dual positive patients was more accurate with AUC = 0.78 for cut off 21.25. The IRF had the best statistical significance for Alpha Thalassemia with AUC = 0.66 for cut off value 18.

Conclusion: An IRF cut off below 15.5 and RET-HE cut off below 22.25 was the most accurate variable in predicting IDA with a sensitivity of 59.4% and 68.3%.

沙特阿拉伯sysmex xn1000网织红细胞参数鉴别缺铁性贫血和地中海贫血的诊断准确性
缺铁性红细胞生成和地中海贫血都与小红细胞生成有关,尽管病理机制不同。鉴于血红蛋白病在地中海地区的高流行率,区分这两种情况很重要。使用传统红细胞指数的几种算法已被开发以促进诊断,然而,它们的诊断准确性较低。新一代血液学分析仪使使用更创新的参数,如网织红细胞参数。我们的目的是评估网织红细胞参数在Sysmex xn1000上的诊断性能,以区分我们人群中的IDA和地中海贫血。方法:我们对送到我们实验室进行血红蛋白电泳筛选的血液样本进行回顾性分析。我们根据已知的诊断标准将我们的队列分为地中海贫血和缺铁患者。我们使用接收算子曲线分析(ROC)分析网织红细胞参数,并确定每个参数的截止值。结果:网织红细胞参数RET、RET- he和IRF是区分地中海贫血患者IDA最准确的指标。对于IDA患者,RET-HE在AUC = 0.69时具有最佳的统计学意义,截点为22.25。双阳性患者的RET-HE更准确,AUC = 0.78, cut off为21.25。IRF对α型地中海贫血最具统计学意义,截值为18时AUC = 0.66。结论:IRF cut off低于15.5和RET-HE cut off低于22.25是预测IDA最准确的变量,敏感性分别为59.4%和68.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
American journal of blood research
American journal of blood research MEDICINE, RESEARCH & EXPERIMENTAL-
自引率
0.00%
发文量
14
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信