scholarly journals Differentiation of beta thalassemia trait from iron deficiency anemia by hematological indices

2017 ◽  
Vol 33 (3) ◽  
Author(s):  
Tahir Ahmed Jameel ◽  
Mukhtar Baig ◽  
Ijaz Ahmed ◽  
Muhammad Barakat Hussain ◽  
Motlag bin Doghaim Alkhamaly
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Hematological Indices ◽  
Thalassemia Trait

scholarly journals Application of Bayesian Decision Tree in Hematology Research: Differential Diagnosis of β-Thalassemia Trait from Iron Deficiency Anemia

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Mina Jahangiri ◽  
Fakher Rahim ◽  
Najmaldin Saki ◽  
Amal Saki Malehi
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Hematological Parameters ◽  
False Positive Rate ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Bayesian Tree ◽  
Thalassemia Trait ◽  
Cart Algorithm

Objective. Several discriminating techniques have been proposed to discriminate between β-thalassemia trait (βTT) and iron deficiency anemia (IDA). These discrimination techniques are essential clinically, but they are challenging and typically difficult. This study is the first application of the Bayesian tree-based method for differential diagnosis of βTT from IDA. Method. This cross-sectional study included 907 patients with ages over 18 years old and a mean (±SD) age of 25 ± 16.1 with either βTT or IDA. Hematological parameters were measured using a Sysmex KX-21 automated hematology analyzer. Bayesian Logit Treed (BLTREED) and Classification and Regression Trees (CART) were implemented to discriminate βTT from IDA based on the hematological parameters. Results. This study proposes an automatic detection model of beta-thalassemia carriers based on a Bayesian tree-based method. The BLTREED model and CART showed that mean corpuscular volume (MCV) was the main predictor in diagnostic discrimination. According to the test dataset, CART indicated higher sensitivity and negative predictive value than BLTREED for differential diagnosis of βTT from IDA. However, the CART algorithm had a high false-positive rate. Overall, the BLTREED model showed better performance concerning the area under the curve (AUC). Conclusions. The BLTREED model showed excellent diagnostic accuracy for differentiating βTT from IDA. In addition, understanding tree-based methods are easy and do not need statistical experience. Thus, it can help physicians in making the right clinical decision. So, the proposed model could support medical decisions in the differential diagnosis of βTT from IDA to avoid much more expensive, time-consuming laboratory tests, especially in countries with limited recourses or poor health services.

scholarly journals Study of blood indices and high performance liquid chromatography (HPLC) in differentiation of β-thalassemia trait and iron deficiency anaemia

2017 ◽  
Vol 5 (11) ◽  
pp. 4728 ◽  
Author(s):  
Pravin M. Meshram ◽  
Hemant R. Kokandakar ◽  
Rajan S. Bindu
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Iron Deficiency Anaemia ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Deficiency Anaemia ◽  
Beta Thalassaemia ◽  
Thalassaemia Trait ◽  
Patient Groups ◽  
Thalassemia Trait

Background: Iron deficiency anemia (IDA) and beta thalassaemia trait (BTT) are two of the most common causes of microcytic anemia.It is essential to differentiate between the two, so as to avoid unnecessary iron therapy which is contraindicated in beta thalassaemia .We retrospectively evaluated the reliability of various indices for differential diagnosis of microcytosis and 𝛽-TT in the same patient groups .Methods: A total of 200 patients were evaluated. We calculated 6 discrimination indices in all patients with anemia or suspected beta thalassemia. None of the subjects had  combined  IDA and 𝛽-TT. The patient groups were evaluated according to  the Mentzer, Shine and Lal, England and Fraser,Srivastava, Green and King, Ricerca.Results: According to percentage correctly diagnosed criteria, Ricerca  and Mentzer  index are considered as the two best discrimination indices in differentiation between β thalassemia trait  and iron deficiency anaemia .Youden’s index showed the following ranking with respect to the indices’ ability to distinguish between 𝛽-TT and IDA, Ricerca index >  Mentzer index > Green and King index >  Srivastava index >  Shine and Lal index > England and Fraser index.Conclusions: Ricerca  and Mentzer  index are considered as the two best discrimination indices in differentiation between β thalassemia trait  and iron deficiency anaemia.Keywords: Iron deficiency anemia (IDA) and beta thalassaemia trait (𝛽-TT) 

scholarly journals Blood Rheological Characterization of β-Thalassemia Trait and Iron Deficiency Anemia Using Front Microrheometry

2021 ◽  
Vol 12 ◽  
Author(s):  
Lourdes Méndez-Mora ◽  
Maria Cabello-Fusarés ◽  
Josep Ferré-Torres ◽  
Carla Riera-Llobet ◽  
Elena Krishnevskaya ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Microfluidic Channel ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Rheological Characterization ◽  
Gold Standard Method ◽  
Healthy Donors ◽  
Thalassemia Trait

The purpose of this work is to develop a hematocrit-independent method for the detection of beta-thalassemia trait (β-TT) and iron deficiency anemia (IDA), through the rheological characterization of whole blood samples from different donors. The results obtained herein are the basis for the development of a front microrheometry point-of-care device for the diagnosis and clinical follow-up of β-TT patients suffering hematological diseases and alterations in the morphology of the red blood cell (RBC). The viscosity is calculated as a function of the mean front velocity by detecting the sample fluid-air interface advancing through a microfluidic channel. Different viscosity curves are obtained for healthy donors, β-TT and IDA samples. A mathematical model is introduced to compare samples of distinct hematocrit, classifying the viscosity curve patterns with respect to the health condition of blood. The viscosity of the fluid at certain shear rate values varies depending on several RBC factors such as shape and size, hemoglobin (Hb) content, membrane rigidity and hematocrit concentration. Blood and plasma from healthy donors are used as reference. To validate their potential clinical value as a diagnostic tool, the viscosity results are compared to those obtained by the gold-standard method for RBC deformability evaluation, the Laser-Optical Rotational Red Cell Analyzer (LoRRCA).

scholarly journals Erythrocyte Catalase Activity in More Frequent Microcytic Hypochromic Anemia: Beta-Thalassemia Trait and Iron Deficiency Anemia

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Sandra Stella Lazarte ◽  
María Eugenia Mónaco ◽  
Cecilia Laura Jimenez ◽  
Miryam Emilse Ledesma Achem ◽  
Magdalena María Terán ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Catalase Activity ◽  
Iron Status ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Total Blood ◽  
Erythrocyte Catalase ◽  
Significant Difference ◽  
Thalassemia Trait

Most common microcytic hypochromic anemias are iron deficiency anemia (IDA) andβ-thalassemia trait (BTT), in which oxidative stress (OxS) has an essential role. Catalase causes detoxification of H2O2in cells, and it is an indispensable antioxidant enzyme. The study was designed to measure erythrocyte catalase activity (ECAT) in patients with IDA (10) or BTT (21), to relate it with thalassemia mutation type (β0orβ+) and to compare it with normal subjects (67). Ninety-eight individuals were analyzed since September 2013 to June 2014 in Tucumán, Argentina. Total blood count, hemoglobin electrophoresis at alkaline pH, HbA2, catalase, and iron status were performed.β-thalassemic mutations were determined by real-time PCR. Normal range for ECAT was 70,0–130,0 MU/L. ECAT was increased in 14% (3/21) of BTT subjects and decreased in 40% (4/10) of those with IDA. No significant difference (p=0,245) was shown between normal and BTT groups, while between IDA and normal groups the difference was proved to be significant (p=0,000). Inβ0andβ+groups, no significant difference (p=0,359) was observed. An altered ECAT was detected in IDA and BTT. These results will help to clarify how the catalase activity works in these anemia types.

scholarly journals Comparison of red cell distribution width and a red cell discriminant function incorporating volume dispersion for distinguishing iron deficiency from beta thalassemia trait in patients with microcytosis

1996 ◽  
Vol 114 (5) ◽  
pp. 1265-1269 ◽  
Author(s):  
Carmen Silvia Passos Lima ◽  
Aparecida Ribeiro de Carvalho Reis ◽  
Helena Zerlotti Wolf Grotto ◽  
Sara Teresinha Ollala Saad ◽  
Fernando Ferreira Costa
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Discriminant Function ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Red Cell ◽  
Cell Distribution ◽  
Distribution Width ◽  
Thalassemia Trait

The red cell distribution width (RDW), and another red cell discriminant function incorporating RDW (MCV² x RDW/Hgb x 100) were determined in a group of 30 patients with iron deficiency anemia, 30 patients with beta thalassemia trait, and 30 normal subjects. Both RDW and (MCV² x RDW/Hgb x 100) mean values were significantly higher in iron deficiency anemia than in beta thalassemia trait (p<0.001). Taking RDW equal or above 21.0 percent among microcytic anemia patients, we identified correctly 90.0 percent of patients with iron deficiency anemia. The sensitivity and specificity of the test were 90.0 percent (IC 95 percent: 0.75 - 0.96) and 77.0 percent (IC 95 percent: 0.60 - 0.88), respectively. RDW values below 21.0 percent identified correctly 77.0 percent of beta thalassemia trait with a sensitivity and a specificity of 77.0 percent (IC 95 percent: 0.60 - 0.88) and 90.0 percent (IC 95 percent: 0.75 - 0.96), respectively. Taking values of (MCV² x RDW/Hgb x 100) above and below 80.0 percent as indicative of iron deficiency and beta thalassemia trait, respectively, we identified correctly 97.0 percent of those patients in each group. Both sensitivity and specificity were 97.0 percent (IC 95 percent: 0.84 - 0.99). These results indicated that the red cell discriminant function incorporating volume dispersion (MCV² x RDW/Hgb x 100) is a highly sensitive and specific method in the initial screening of patients with microcytic anemia and is better than RDW in differentiating iron deficiency anemia from beta thalassemia trait.

scholarly journals Indices in differentiating iron deficiency anemia from thalassemia trait- a comparative study

2021 ◽  
Vol 12 (10) ◽  
pp. 81-86
Author(s):  
Sufia Ahmad ◽  
Noorin Zaidi ◽  
Syed Riaz Mehdi ◽  
Sumaiya Irfan ◽  
Sharique Ahmad
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Hypochromic Anemia ◽  
Bone Marrow Examination ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Blood Samples ◽  
Biochemical Assays ◽  
Different Types ◽  
Thalassemia Trait

Background: Iron deficiency anemia (IDA) and beta thalassemia trait (BTT) are the two most common and important causes of microcytic hypochromic anemia in India. It is very difficult to differentiate between the two. Many different types of techniques have been proposed for the same. While some are invasive like bone marrow examination others are not available at all centers, like electrophoresis. Hence different indices come into play. Aims and Objective: This study was undertaken to compare the efficacy of Shine and Lal index and Mentzer index in differentiating between IDA and BTT. Materials and Methods: A total of 407 anemia cases were studied over a period of 18 months and their blood samples were subject to different hematological and biochemical assays to diagnose the type of anemia. Results: Based on these tests 92.1% cases were found to be of IDA whereas 3.7% cases were found to be of BTT. Then both the indices were applied in the above mentioned cases. Conclusion: While Shine and Lal index was found to have better sensitivity, Mentzer index was found to have better specificity.

Sign in / Sign up

Export Citation Format

Share Document