scholarly journals A Novel Algorithm Using Cell Population Data (VCS Parameters) as a Screening Discriminant between Alpha and Beta Thalassemia Traits

Diagnostics ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2163
Author(s):  
Angeli Ambayya ◽  
Santina Sahibon ◽  
Thoo Wei Yang ◽  
Qian-Yun Zhang ◽  
Rosline Hassan ◽  
...  
Keyword(s):  
Cell Population ◽  
Population Data ◽  
Cost Effective ◽  
Beta Thalassemia ◽  
Evaluation Tool ◽  
Blood Disorders ◽  
Thalassaemia Trait ◽  
Thalassemia Trait ◽  
Novel Algorithm ◽  
Apparently Healthy

Thalassemia is one of the major inherited haematological disorders in the Southeast Asia region. This study explored the potential utility of red blood cell (RBC) parameters and reticulocyte cell population data (CPD) parameters in the differential diagnosis of α and β-thalassaemia traits as a rapid and cost-effective tool for screening of thalassemia traits. In this study, a total of 1597 subjects (1394 apparently healthy subjects, 155 subjects with α-thalassaemia trait, and 48 subjects with β-thalassaemia trait) were accrued. The parameters studied were the RBC parameters and reticulocyte CPD parameters derived from Unicel DxH800. A novel algorithm named αβ-algorithm was developed: (MN-LMALS-RET × RDW) − MCH) to discriminate α from β-thalassaemia trait with a cut-off value of 1742.5 [AUC = 0.966, sensitivity = 92%, specificity = 90%, 95% CI = 0.94–0.99]. Two prospective studies were carried: an in-house cohort to assess the specificity of this algorithm in 310 samples comprising various RBC disorders and in an interlaboratory cohort of 65 α-thalassemia trait, and 30 β-thalassaemia trait subjects to assess the reproducibility of the findings. We propose the αβ-algorithm to serve as a rapid, inexpensive surrogate evaluation tool of α and β-thalassaemia in the population screening of thalassemia traits in geographic regions with a high burden of these inherited blood disorders.

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) 

Beta Thalassemia Trait: How the New Information Provided by the Routine Hematology Analysers May Help in Its Differential Diagnosis or Flagging

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 5186-5186
Author(s):  
Susanna Barella ◽  
Ramon Simon-Lopez ◽  
Nicola Di Gaetano ◽  
Renzo Galanello
Keyword(s):  
Research Funding ◽  
Roc Analysis ◽  
Dna Analysis ◽  
Population Data ◽  
Beta Thalassemia ◽  
Control Group ◽  
Target Cells ◽  
New Information ◽  
Thalassemia Trait ◽  
Best Parameters

Abstract Abstract 5186 Introduction: Beta Thalassemia (β-thalassemia) is one of the more common hemoglobinopathies worldwide, being the heterozygous variant, called Beta Thalassemia Trait, a benign variant, but important to diagnose, for genetic counseling, trying to avoid the homozygous variant, called major. Diagnostic of Beta Thalassemia Trait: Classic testing for β-thalassemia includes: hematologic testing of red blood cell indices, peripheral blood smear (prewsence of target cells and RBC with basophilic stippling, etc.), and qualitative and quantitative hemoglobin analysis. Have been proposed too Discriminant functions, like the one published many years ago, by England and Fraser. Objective: Recently have been developed new parameters and information in the new automated hematology analyzer called DxH8008™ from Beckman Coulter as @MSCV, @RSF, @MAF, @ LHD% and many morphological parameters for RBC and Reticulocytes calles Cell Population Data. All this parameters may be used to create flagging for laboratory use only (LUO) or Research use only (RUO). The purpose of this study is to investigate the possible use or utility of this new information for the screening/flagging of Beta Thalassemia Trait. Patient and Methods: We have collected 30 patients with Beta Thalassemia Trait. All of them were confirmed by red cell morphology, Hgb Electroforesis, cromatography in liquid phase in human whole blood for the determination of Hemoglobin A2, F, A1c, and identification of abnormal hemoglobins and DNA analysis (DNA Analysis by GAP-PCR). We have compared these patients with a control group (184 individuals) and with other anemias (see Table 1). Results: Using ROC analysis, the best parameters differentiating the Beta Thalassemia Trait from the normals were: MCV (AUC 1. 000), MRV (AUC 0. 999), @MAF(AUC 0. 999), @MCNRET (AUC 0. 997), RDW (AUC 0. 957), HGB (AUC 0. 915), RBC(AUC 0. 912). Using ROC analysis, the best parameters differentiating the Beta Thalassemia Trait from other anemias (excluding normals) were: RDW-SD (AUC 0. 937), DF Eng-Fra (AUC 0. 779), RDW (AUC 0. 766), RBC (AUC 0. 734) Disclosures: Simon-Lopez: Beckman Coulter: @LHD, @MAF, @RSF, @LHD, @MAF, @RSF Patents & Royalties, Employment. Di Gaetano:Instrumentation Laboratory spa: Work for a distributor of Beckman Coulter Instruments in Italy Other. Galanello:Ferrokin: Research Funding; Apopharma: Research Funding, Speakers Bureau; Novartis: Research Funding, Speakers Bureau.

scholarly journals NESTROFT AS SCREENING TEST FOR BETA THALASSEMIA TRAIT

2020 ◽  
pp. 1-3
Author(s):  
Keshav Bansal ◽  
Dhaval Bhatt ◽  
G.K. Sharma
Keyword(s):  
Positive Predictive Value ◽  
Negative Predictive Value ◽  
Predictive Value ◽  
Screening Test ◽  
Cost Effective ◽  
Thalassemia Major ◽  
Hplc Method ◽  
Beta Thalassemia ◽  
Thalassemia Trait ◽  
Sensitivity Specificity

Objective: To evaluate the utility of NESTROFT as a screening test for Beta Thalassemia Trait. Material and Methods: A Prospective study of total 137 clinically normal siblings of thalassemia major patients registered at thalassemia clinic in department of pediatrics, Govt. medical college, Kota were selected randomly for the study. All cases were investigated for CBC, Mentzer’s index, NESTROFT and HbA2 estimation by HPLC method. Result: Total 137 cases were screened for thalassemia carrier by HbA2 estimation using HPLC technique. Total 67 (48.90%) cases having HbA2 level ≥3.5 % considered as carrier whereas rest 70 (51.10%) cases were normal. In this study 95 cases showed MCV<80. Out of them 59 cases were carrier and 36 cases were normal. The Sensitivity, specificity, positive predictive value and negative predictive value of MCV<80 are 90.12%, 49.71%, 63.78% and 84.68% respectively. The Sensitivity, specificity, positive predictive value and negative predictive value of Mentzer index are 85.25%, 97.16%, 96.45% and 89.19 % respectively. In present study, NESTROFT were done in all cases, the sensitivity of NESTROF test is 94.21%, specificity is 89.72%, Predictive value of positive test is 89.17% and Predictive value of negative test is 93.75%. So NESTROFT is better test for screening for Beta Thalassemia trait. Conclusion: NESTROF test is reliable, cost effective and better screening test for Thalassemia carrier detection. Positive cases can be confirmed by HPLC. NESTROFT can be used as mass screening programme for hemoglobinopathies.

scholarly journals High Frequency Electromagnetic Shielding by Biochar-Based Composites

Nanomaterials ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 2383
Author(s):  
Daniele Torsello ◽  
Mattia Bartoli ◽  
Mauro Giorcelli ◽  
Massimo Rovere ◽  
Rossella Arrigo ◽  
...  
Keyword(s):  
Complex Permittivity ◽  
Raw Materials ◽  
Cost Effective ◽  
Electromagnetic Shielding ◽  
Building Construction ◽  
Physical Parameters ◽  
Preliminary Evaluation ◽  
Evaluation Tool ◽  
Structural Composites ◽  
Microwave Shielding

We report on the microwave shielding efficiency of non-structural composites, where inclusions of biochar—a cost effective and eco-friendly material—are dispersed in matrices of interest for building construction. We directly measured the complex permittivity of raw materials and composites, in the frequency range 100 MHz–8 GHz. A proper permittivity mixing formula allows obtaining other combinations, to enlarge the case studies. From complex permittivity, finally, we calculated the shielding efficiency, showing that tailoring the content of biochar allows obtaining a desired value of electromagnetic shielding, potentially useful for different applications. This approach represents a quick preliminary evaluation tool to design composites with desired shielding properties starting from physical parameters.

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.

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