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

xlomafota13 shared this article with you from Inoreader Diagnostic accuracy of reticulocyte parameters on the sysmex XN 1000 for discriminating iron deficiency anaemia and thalassaemia in Saudi Arabia Via American Journal of Blood Research Am J Blood Res. 2021 Apr 15;11(2):172-179. eCollection 2021. 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%. PMID:34079632 | PMC:PMC8165718 View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.