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

2021 ◽  
Author(s):  
Mina Jahangiri ◽  
Fakher Rahim ◽  
Najmaldin Saki ◽  
Amal Saki Malehi
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Area Under The Curve ◽  
Microcytic Anemia ◽  
Diagnostic Methods ◽  
Deficiency Anemia ◽  
Bayesian Decision ◽  
Predictive Values ◽  
Thalassemia Trait

Abstract Background: Several discriminating techniques have been proposed to discriminate between β‐thalassemia trait (βTT) and iron deficiency anemia (IDA) so far. These discrimination techniques are important clinically, but they are challenging and normally difficult; so if a patient with IDA is diagnosed as βTT, then it is deprived of iron therapy. This study is the first application of the Bayesian tree-based method for differential diagnosis of βTT from IDA. Method: In this study, 907 patients were enrolled with the ages over 18-year-old with microcytic anemia. Bayesian Logit Treed (BLTREED) has been used to discriminate βTT from IDA. Results: Mean corpuscular volume (MCV) was found as the main predictor in diagnostic discrimination. BLTREED model showed high sensitivity (96%), specificity (93%), accuracy (95%), Youden's index (89), as well as positive and negative predictive values in the differential diagnosis of βTT from IDA. Also, AUC revealed a more precise classification with an area under the curve value of 0.98.Conclusions: BLTREED model showed excellent diagnostic accuracy for differentiating βTT from IDA. In addition, understanding tree-based methods are easy and need not a statistical experience, so this advantage can help physicians in making the right clinical decision. Thus, we suggest the using of the BLTREED model as a powerful method in data mining techniques in order to develop sensitive and accurate diagnostic methods for for discriminating between these two anemia disorders.

scholarly journals Reticulocyte hemoglobin equivalent in differential diagnosis of iron deficiency, iron deficiency anemia and β thalassemia trait in children.

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Yeter Düzenli Kar ◽  
Konca Altınkaynak
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Roc Analysis ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Healthy Children ◽  
Hypochromic Microcytic Anemia ◽  
Thalassemia Trait ◽  
Diagnostic Power

AbstractObjectivesThis study investigated the diagnostic power of reticulocyte hemoglobin equivalent (Ret-He) in the differential diagnosis of hypochromic microcytic anemia to differentiate iron deficiency anemia (IDA) and thalassemia trait (TT) based on the traditionally used erythrocyte index and formulas.MethodsTwenty-six children with iron deficiency (ID), 26 with IDA, 33 with β-TT, 41 healthy children were assessed. Complete blood count parameters, Ret-He, immature reticulocyte fraction (IRF), low-fluorescence ratio (LFR), Mentzer’s indexes (MI) were evaluated. The diagnostic power of Ret-He in distinguishing between IDA and β-TT was investigated using ROC analysis.ResultsRet-He levels were (median(Q1-Q3)) 20.6(19.7–21.5) pg in β-TT, 16.1(13.1–20) pg in IDA, 29.7(27.2–30.7) pg in ID, 30.5(29.8–31.7) pg in healthy controls. Based on ROC analysis, diagnostic power for distinguishing between IDA and β-TT was determined as RBC>MI>Ret-He>RDW>LFR>IRF. The highest sensitivity and specificity for differential diagnosis was obtained when the Ret-He cut-off value was 18.2pg. The AUC (95%CI) value was calculated as 0.765(0.637–0.866), and a statistically significant difference was found between groups (p<0.0006).ConclusionsIn patients with hypochromic microcytic anemia, Ret-He≤18.2pg combined with RBC≤5.3x106/L and MI>10.42 can be safely used to distinguish IDA from β-TT. In particular, patients with low Ret-He who don’t respond to iron therapy should be examined for β-TT.

scholarly journals Hematological Indices for Differential Diagnosis of Beta Thalassemia Trait and Iron Deficiency Anemia

Anemia ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Aysel Vehapoglu ◽  
Gamze Ozgurhan ◽  
Ayşegul Dogan Demir ◽  
Selcuk Uzuner ◽  
Mustafa Atilla Nursoy ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Beta Thalassemia ◽  
Distribution Width ◽  
Patient Groups ◽  
Thalassemia Trait ◽  
Rbc Count

Background. The two most frequent types of microcytic anemia are beta thalassemia trait (β-TT) and iron deficiency anemia (IDA). We retrospectively evaluated the reliability of various indices for differential diagnosis of microcytosis andβ-TT in the same patient groups.Methods. A total of 290 carefully selected children aged 1.1–16 years were evaluated. We calculated 12 discrimination indices in all patients with hemoglobin (Hb) values of 8.7–11.4 g/dL. None of the subjects had a combined case of IDA andβ-TT. All children with IDA received oral iron for 16 weeks, and HbA2 screening was performed after iron therapy. The patient groups were evaluated according to red blood cell (RBC) count; red blood distribution width index; the Mentzer, Shine and Lal, England and Fraser, Srivastava and Bevington, Green and King, Ricerca, Sirdah, and Ehsani indices; mean density of hemoglobin/liter of blood; and mean cell density of hemoglobin.Results. The Mentzer index was the most reliable index, as it had the highest sensitivity (98.7%), specificity (82.3%), and Youden’s index (81%) for detectingβ-TT; this was followed by the Ehsani index (94.8%, 73.5%, and 68.3%, resp.) and RBC count (94.8%, 70.5%, and 65.3%).Conclusion. The Mentzer index provided the highest reliabilities for differentiatingβ-TT from IDA.

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 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 ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
V. Laengsri ◽  
W. Shoombuatong ◽  
W. Adirojananon ◽  
C. Nantasenamat ◽  
V. Prachayasittikul ◽  
...  
Keyword(s):  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Nearest Neighbor ◽  
Laboratory Data ◽  
Model Performance ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Support Vector ◽  
Web Based ◽  
Thalassemia Trait

Abstract Background The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Although considerable RBC formulas and indices with various optimal cut-off values have been developed, distinguishing between IDA and TT is still a challenging problem due to the diversity of various anemic populations. To address this problem, it is desirable to develop an improved and automated prediction model for discriminating IDA from TT. Methods We retrospectively collected laboratory data of HMA found in Thai adults. Five machine learnings, including k-nearest neighbor (k-NN), decision tree, random forest (RF), artificial neural network (ANN) and support vector machine (SVM), were applied to construct a discriminant model. Performance was assessed and compared with thirteen existing discriminant formulas and indices. Results The data of 186 patients (146 patients with TT and 40 with IDA) were enrolled. The interpretable rules derived from the RF model were proposed to demonstrate the combination of RBC indices for discriminating IDA from TT. A web-based tool ‘ThalPred’ was implemented using an SVM model based on seven RBC parameters. ThalPred achieved prediction results with an external accuracy, MCC and AUC of 95.59, 0.87 and 0.98, respectively. Conclusion ThalPred and an interpretable rule were provided for distinguishing IDA from TT. For the convenience of health care team experimental scientists, a web-based tool has been established at http://codes.bio/thalpred/ by which users can easily get their desired screening test result without the need to go through the underlying mathematical and computational details.

scholarly journals Discriminant indexes to simplify the differential diagnosis between iron deficiency anemia and thalassemia minor in individuals with microcytic anemia

2020 ◽  
Vol 66 (9) ◽  
pp. 1277-1282
Author(s):  
Fernando Minervo Pimentel Reis ◽  
Raul Ribeiro de Andrade ◽  
Célio Fernando de Sousa Rodrigues ◽  
Fabiano Timbó Barbosa
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Microcytic Anemia ◽  
Deficiency Anemia ◽  
Cross Sectional ◽  
Require Time ◽  
Additional Tool ◽  
Thalassemia Minor ◽  
Confirmatory Tests

SUMMARY INTRODUCTION: Microcytic anemias are very common in clinical practice, with iron deficiency anemia (IDA) and thalassemia minor (TT) being the most prevalent. Diagnostic confirmation of these clinical entities requires tests involving iron metabolism profile, hemoglobin electrophoresis, and molecular analysis. In this context, several discriminant indices have been proposed to simplify the differential diagnosis between IDA and TM. OBJECTIVE: The aim of this paper was to demonstrate the clinical relevance of the use of discriminant indices in individuals with microcytic anemia to simplify the differential diagnosis between iron deficiency anemia and minor thalassemia. METHODS: A bibliographic and cross-sectional search was performed in the PubMed, SciELO and LILACS databases, using the following descriptors: iron deficiency anemia, thalassemia minor, and differential diagnosis. RESULTS: More than 40 mathematical indices based on erythrocyte parameters have been proposed in the hematological literature in individuals with microcytosis. Green & King indexes (IGK), Ehsani index, and erythrocyte count (RBC) had excellent performances, especially when their efficacy was observed in adults and children. CONCLUSIONS: Confirmatory tests for differential diagnosis between IDA and TM require time-consuming and costly methods. Despite the excellent performances of IGK, Ehsani index, and RBC, none of them presented sufficient sensitivity and specificity to establish a diagnosis. However, they can provide a powerful additional tool for diagnostic simplification between IDA and TM.

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