A Local Equation for Differential Diagnosis of β-Thalassemia Trait and Iron Deficiency Anemia by Logistic Regression Analysis in Southeast Iran

Hemoglobin ◽  
2014 ◽  
Vol 38 (5) ◽  
pp. 355-358 ◽  
Author(s):  
Narjes Sargolzaie ◽  
Ebrahim Miri-Moghaddam
Keyword(s):  
Logistic Regression ◽  
Differential Diagnosis ◽  
Regression Analysis ◽  
Iron Deficiency ◽  
Iron Deficiency Anemia ◽  
Logistic Regression Analysis ◽  
Deficiency Anemia ◽  
Local Equation ◽  
Thalassemia Trait

scholarly journals Factors Associated with Anemia among Children Aged 6–23 Months Attending Growth Monitoring at Tsitsika Health Center, Wag-Himra Zone, Northeast Ethiopia

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Haile Woldie ◽  
Yigzaw Kebede ◽  
Amare Tariku
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Iron Deficiency ◽  
Health Center ◽  
Iron Deficiency Anemia ◽  
Logistic Regression Analysis ◽  
Associated Factors ◽  
Deficiency Anemia ◽  
Northeast Ethiopia ◽  
Prevalence Of Anemia

Background. Globally, about 47.4% of children under five are suffering from anemia. In Ethiopia, 60.9% of children under two years are suffering from anemia. Anemia during infancy and young childhood period is associated with poor health and impaired cognitive development, leading to reduced academic achievement and earnings potential in their adulthood life. However, there is scarcity of information showing the magnitude of iron deficiency anemia among young children in Ethiopia. Therefore, this study aimed at assessing prevalence and associated factors of iron deficiency anemia among children under two (6–23 months).Methods. Institution based cross-sectional study was carried out from March to May, 2014, at Tsitsika Health Center in Wag-Himra Zone, Northeast Ethiopia. Systematic random sampling technique was employed. Automated hemoglobin machine was used to determine the hemoglobin level. Socioeconomic and demographic data were collected by using a pretested and structured questionnaire. Binary logistic regression analysis was used to identify associated factors and odds ratio with 95% CI was computed to assess the strength of association.Results. Total of 347 children participated in this study. The overall prevalence of anemia was 66.6%. In multivariate logistic regression analysis, male sex (AOR = 3.1 (95% CI: 1.60–5.81)), 9–11 months of age (AOR = 9.6 (95% CI: 3.61–25.47)), poor dietary diversity (AOR = 3.2 (95% CI: 1.35–7.38)), stunting (AOR = 2.7 (95% CI: 1.20–6.05)), diarrhea (AOR = 4.9 (1.63–14.59)), no formal education (AOR = 2.6 (95% CI: 1.26–5.27)), early initiation of complementary food (AOR = 11.1 (95% CI: 4.08–30.31)), and lowest wealth quintile (AOR = 3.0 (95% CI: 1.01–8.88)) were significantly associated with anemia.Conclusion. The overall prevalence of anemia among children who aged 6–23 months has sever public health importance in the study area. Integrated efforts need to be prioritized to improve health as well as appropriate infant and young child feeding practice among children under.

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.

Decision-tree-based methods for differential diagnosis of β-thalassemia trait from iron deficiency anemia

2017 ◽  
Vol 34 (3) ◽  
pp. e12201 ◽  
Author(s):  
Mina Jahangiri ◽  
Elahe Khodadi ◽  
Fakher Rahim ◽  
Najmaldin Saki ◽  
Amal Saki Malehi
Keyword(s):  
Differential Diagnosis ◽  
Iron Deficiency ◽  
Decision Tree ◽  
Iron Deficiency Anemia ◽  
Deficiency Anemia ◽  
Thalassemia Trait

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 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.

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