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Accurate and timely interpretation of microcytic anemia can be diagnostically challenging in the primary care setting. We sought to develop a novel model for distinguishing iron-deficiency anemia from thalassemia trait in the modern pediatric population. Demographic history and red blood cell indices were retrospectively characterized for 76 children referred to our pediatric hematology clinic for evaluation of microcytic anemia. Statistically significant variables were sequentially added into a logistic regression model to develop the final model. The final discriminating model incorporates red cell distribution width, mean corpuscular hemoglobin concentration, and red blood cell values. Favorable predictive performance is seen in the initial (sensitivity 89.2%, specificity 92.3%) and external validation cohort (sensitivity 84.4%, specificity 88.9%). This novel tool may aid in determining the cause of hypochromic, microcytic anemia in the primary care setting. Finally, the study cohort reflects an underrepresented group in the development of screening tools, and thus offers generalizability., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Hemoglobin (Hb) H disease presents a wide range of clinical phenotypes, from asymptomatic to severe forms, depending on significant genetic heterogeneity. This is the first report of clinical and hematological features of the nondeletional HbH disease caused by -- CR /α CS α. A baby was born to a father and a mother with -- CR and α CS α carriers, respectively. She had severe symptomatic hypochromic microcytic anemia at 2 months of age with Hb 7.8 g/dL, packed cell volume (PCV) 0.27 L/L, mean corpuscular volume (MCV) 64.3 fL, and mean corpuscular Hb (MCH) 18.3 pg. The Hb analysis using capillary electrophoresis (CE) showed Hb Bart's, HbH, and Hb CS peaks at 17.1%, 2.2%, and 1.6%, respectively. A better understanding of a patient's clinical and hematological features with -- CR /α CS α is useful for hemoglobinopathy counseling for the national thalassemia controlling program.

Introduction: Platelet count is crucial for clinical decision. In cases of microcytosis, platelet count based on impedance technique (PLT-I) may overestimate platelet count., Aim: To compare PLT-I with platelet count using the optical technique (PLT-O) and establish a Mean Corpuscular Volume (MCV) threshold for considering PLT-O., Methods: A prospective analytical study conducted over two months involved blood samples collected in standard K2 EDTA tubes for complete blood count analysis, revealing microcytosis (MCV<80 fL). PLT-O analysis in channel-Ret mode was performed using the Sysmex-XN1000 (Sysmex Corporation, Kobe, Japan). Percentage of fragmented red cells (FRC%) and percentage of microcytic red cells (Micro-R%) were recorded. Blood smears stained with May-Grünwald-Giemsa were examined for potential interfering particles., Results: A strong correlation was observed between the two techniques for all platelet values as well as for PLT <150 x 109/L (correlation coefficient r = 0.971, 95% CI: [0.956-0.982]; P<10-3 and r = 0.90, 95% CI: [0.79-0.95]; P< 10-3). The Bland-Altman plot revealed a bias of 16.53 x 109/L between the two methods, with agreement limits between -55.8 and 88.8 x 109/L. A threshold MCV value indicating the use of the optical method, with a cut-off at 72.9fL, demonstrated promising performance consistent with literature findings. However, less favorable performance was observed with Micro-R%., Conclusion: Impedance could be employed in routine practice. However, for MCV<72.9 fL or in the presence of schizocytes, the hemogram validation procedure may incorporate the use of PLT-O.

We reported the identification of two rare α-thalassemia silent carriers with novel HBA1 mutations of CD 39 -C [Thr > Pro] ( HBA1 : c.114del; p.Thr39Profs*11) and CD 109 ACC > CCC [Thr > Pro] ( HBA1 : c.325A > C; p. Thr109Pro), respectively. The two probands were pregnant women diagnosed with mild hypochromic anemia or microcytic hypochromic anemia by routine blood tests. They started iron therapy before taking differential diagnosis from iron deficiency anemia. After wait and watch approach, they both accepted thalassemia genetic screening, which identified CD 39 -C [Thr > Pro] and CD 109 ACC > CCC [Thr > Pro], respectively. Due to inappropriate iron therapy, worse anemia and iron overload were noticed in the first proband, but no obvious side effect was found in both probands. Functional analysis showed that, relative to the wild type, CD 39 -C [Thr > Pro] considerably reduced the expression of the HBA1 protein while CD 109 ACC > CCC [Thr > Pro] only had a minor impact. Our study highlighted the importance of gestational thalassemia screening based on next-generation sequencing for identifying novel rare thalassemia variants and increased our understanding about the relationship between genotype and phenotype of α-thalassemia.

Background: The most common causes of microcytic hypochromic anemia are thalassemia trait (TT) and iron deficiency anemia (IDA). Clinically, the differential diagnosis of TT and IDA is crucial, but it is typically challenging. Thus, in order to differentiate between TT and IDA, we seek to develop a new discriminative index on an automatic hematology analyzer utilizing the two new RBC characteristics of low hemoglobin density (LHD) and microcytic anemia factor (MAF)., Methods: We recruited a total of 323 subjects, including 115 healthy controls, 83 TT, and 125 IDA. An automated hematology analyzer (DxH800, Beckman Coulter) was used to determine peripheral blood parameters; LHD and MAF were calculated using the parameters of MCHC, Hb, and MCV. The receiver operating characteristic (ROC) curve was used to determine the cutoff values and evaluate the diagnostic value for TT and IDA., Results: LHD was significantly lower in TT than IDA, whereas MAF was higher. To distinguish between TT and IDA, a new formula based on LHD and MAF was developed, with a cutoff value of 0.5, AUC of 0.9706 (95% CI: 0.9503 - 0.9909), and specificity, sensitivity, positive predictive value, and negative predictive values were 92.91%, 91.36%, 89.16%, and 94.40%, respectively. The new formula has proven advantages over conventional indices, such as RDW-SD, MCV, MCH, etc. Conclusions: The RBC parameters LHD and MAF detected by hematology analyzer could be useful for screening for TT and IDA. Our new formula outperforms other discriminant formulas in the literature with high sensitivity and specificity, is simple, rapid, and can aid in early detection and management.

Background: Iron deficiency anemia (IDA) and thalassemia trait (TT) are the most common causes of microcytic hypochromic anemia (MHA) and are endemic in lower resource settings and rural areas with poor medical infrastructure. Accurate discrimination between IDA and TT is an essential issue for MHA patients. Although various discriminant formulas have been reported, distinguishing between IDA and TT is still a challenging problem due to the diversity of anemic populations., Methods: We retrospectively collected laboratory data from 798 MHA patients. High proportions of α-TT (43.33 %) and TT concomitant with IDA (TT&IDA) patients (14.04 %) were found among TT patients. Five machine learning (ML) approaches, including Liner SVC (L-SVC), support vector machine learning (SVM), Extreme gradient boosting (XGB), Logistic Regression (LR), and Random Forest (RF), were applied to develop a discriminant model. Performance was assessed and compared with six existing discriminant formulas., Results: The RF model was chosen as the discriminant algorithm, namely TT@MHA. TT@MHA was tested in an interlaboratory cohort with a sensitivity, specificity, accuracy, and AUC of 91.91 %, 91.00 %, 91.53 %, and 0.942, respectively. A webpage tool of TT@MHA (https://dxonline.deepwise.com/prediction/index.html?baseUrl=%2Fapi%2F&id=26408&topicName=undefined&from=share&platformType=wisdom) was developed to facilitate the healthcare providers in rural areas., Conclusion: The ML-based TT@MHA algorithm, with high sensitivity and specificity, could help discriminate TT patients from MHA patients, especially in populations with high proportions of α-TT patients and TT&IDA patients. Moreover, a user-friendly webpage tool for TT@MHA could facilitate healthcare providers in rural areas where advanced technologies are not accessible., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Context: Z score defines the shift of an observed value from the mean., Aims: By determining the direction of this shift and its absolute value for mean corpuscular hemoglobin (MCH) and mean corpuscular hemoglobin concentration (MCHC), one can quickly screen the hemogram for any spurious results in RBC parameters and also predict the type of anemia. This is because MCH and MCHC are derived parameters (from Hb, RBC, MCV) and thereby reflect the true as well as false changes in an erythrogram., Materials and Methods: A total of 975 hemograms were studied retrospectively. Basic statistical formulae using mean and standard deviation were applied to calculate z scores for MCH and MCHC. Results obtained were compared with the standard method and validated by an independent cohort of 100 random samples run on a different machine., Results and Statistical Analysis: Z score was found to be statistically significant (p <.001) in diagnosing iron deficiency anemias, megaloblastic anemias, hemolytic anemias, regenerative anemias, anemia of chronic disease and spurious findings. Z score was not significant (p = 0.9) in predicting beta thalassemia trait. The sensitivity was low for the differentials of microcytic hypochromic anemias., Conclusions: Despite this, Z score can be of immense help to the clinicians and pathologists in making quick interpretation of the underlying red cell abnormalities. Also, it can be used as a quality assessment tool in hematology laboratories taking pre analytical and analytical factors into account., Competing Interests: None

Competing Interests: Declaration of competing interest The authors declare no conflict of interest.