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Title: New bioinformatics-based discrimination formulas for differentiation of thalassemiatraits from iron deficiency anemia
Authors: Abdul Hafeez Kandhro
Watshara Shoombuatong
Virapong Prachayasittikul
Pornlada Nuchnoi
Mahidol University
Keywords: Biochemistry, Genetics and Molecular Biology
Issue Date: 1-Aug-2017
Citation: Lab Medicine. Vol.48, No.3 (2017), 230-237
Abstract: © American Society for Clinical Pathology, 2017. All rights reserved. Thalassemia traits (TTs) and iron deficiency anemia (IDA) are the most common disorders of hypochromic microcytic anemia (HMA). The present study aimed to differentiate TTs from IDA by analyzing discrimination formulas and provides comprehensive data of hemoglobin disorders prevalent in Pakistan. Among 12 published discrimination formulas, 6 formulas-MI, EF, G&K, RDWI, R, and HHI-were the most reliable to discriminate TTs from IDA. The failure cutoff values were improved by the random forest (RF) decision-tree approach. Moreover, the Shine and Lal (S&L) formula, which completely failed to discriminate IDA from TTs with original cutoff value (<1530), improved with the use of new proposed cutoff value (<1016) and was found to successfully discriminate all cases of TTs from those with IDA. In addition, 2 newly proposed formulas discriminated TTs from IDA more reliably than the original 12 formulas assessed. The proposed formulas could play a crucial role for clinicians to discriminate between TTs and IDA.
ISSN: 19437730
Appears in Collections:Scopus 2016-2017

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