The Efficacy of Routine Haematological Parameters
in the Diagnosis of Anaemia in Indian Children
Background: Anaemia is a common disease in children resulting in many problems including impaired cognitive performance, behavioural and language development, and scholastic achievements. The use of simple investigations to make an accurate diagnosis is of paramount importance. Material and Methods: The present study is a prospective study done on 100 children in the school-going age group of five years to fifteen years. The automated haematology analyser was used to calculate various haematology parameters and the iron profile was used to confirm the diagnosis of iron deficiency anaemia. Results: Mild iron deficiency anaemia is the commonest type of microcytic anaemia in school age children. The differentiation between iron deficiency anaemia and thalassaemia trait is possible with the RBC indices provided by the automated analysers. The significant tests in differentiation between iron deficiency anaemia and thalassaemia trait were found to be mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) and red blood cell (RBC) count. In iron deficiency anaemia, MCV and MCH are decreased proportionately with decrease in haemoglobin value. The RBC count is slightly decreased, normal or in few cases slightly increased. Peripheral smear examination is also helpful to corroborate the findings. Conclusion: Use of basic haematological parameters is useful for the diagnosis of anaemia in the Indian children where expensive tests cannot be afforded by many.
Anaemia is a common problem and is considered as one of the silent killer diseases as it causes a variety of problems over a period of time. Some of the effects of anaemia may not be reversed if it is not treated in time, especially if the anaemia is in childhood. The various medical conditions that lead to anaemia encompass nearly the full spectrum of human disease. Anaemia results in impaired cognitive performance, behavioural and language development, and scholastic achievements in children. Therefore, detection of even mild degree of anaemia may be of great significance.
About one third of the world’s population is found to be anaemic and the prevalence of anaemia worldwide among the 6-12 years age group is about 36%, and 7% in developing countries.[1, 2] India is one of the countries with very high prevalence of anaemia in the world. Nutritional anaemia is a major public health problem in India and is primarily due to iron deficiency. Microcytic hypochromic is seen in iron deficiency anaemia (IDA), thalassaemia trait (TT), lead poisoning, and anaemia of chronic disease (ACD). Various haematological indices have been proposed as simple and inexpensive tools to diagnose IDA to reduce the investigative costs.
This study was done to evaluate the routine haemocytometric parameter profile in the diagnosis of iron deficiency anaemia as accurately as possible.
Material and Methods:
The present study is a prospective study done on 100 children in the school-age group of five years to fifteen years, who came to the hospital. A detailed history was elicited, and a thorough clinical examination was undertaken.
The automated haematology analyser Sysmex XS-1000i was used to calculate various haematology parameters. The analyser is a 5-part differential which uses Fluorescent Flow Cytometry principle or WBC-Diff, Direct Current–Sheath Flow principle for RBC, haematocrit, platelet count and Noncyanide, Sodium Lauryl Sulphate (SLS) for haemoglobin estimation.
The children with haemoglobin value of less than 12 grams per decilitre (gm/dl) in this age group were selected and the children with MCV less than normal (microcytic hypochromic anaemia) were included. All other haematology parameters in these patients were recorded. This was followed by a detailed peripheral smear examination. Peripheral smear examination was done on slides stained with Leishman’s stain.
The iron profile included serum iron, serum ferritin and total iron binding capacity (TIBC). Erba Manheim Chem 7, an automated clinical chemistry analyser, was used for ferritin measurement. It is based on immunoturbidimetric quantitative assay in which antigen antibody reaction by endpoint method is used. For serum iron and TIBC, VITROS 5,1 FS Chemistry System analyser was used.
Data obtained were compiled, tabulated, and analyzed. Descriptive statistics were applied. Means were compared by using one-way ANOVA. Chi-square tests were applied to find out the association between two attributes. A p-value of < 0.05 was statistically significant. SPSS version 20 was used to analyze the data.
Out of the children coming to the Paediatric outpatient department, we selected 100 children in the school going age group (5-15 years) who had anaemia. The children were divided into two age groups, 10 and under and over 10 years (adolescents). Out of the 100 children, 67% were 10 years or below and 33% were over 10 years of age. The mean age of the children was 9 years. The female to male ratio in the present study was found to be 1.2:1.
The anaemia was categorised into three grades:
mild, moderate, and severe anaemia having haemoglobin values of 10.5-11.5g/dl, 7-10.4g/dl and <7g/dl respectively. In this study, 71% (69% below 10 years of age) had mild anaemia, 24% (70.8% below 10 years of age) cases had moderate and only 5% (80% over 10 years of age) had severe anaemia. There was no statistical significance found between age and the severity of anaemia as determined by Pearson chi-square test (p=0.77).
In the present study, 38 out of 54 girls had mild anaemia, 12 had moderate and 4 had severe anaemia. Out of 46 boys, 33 had mild anaemia, 12 had moderate and only 1 boy had severe anaemia. No significant correlation was found between the severity of anaemia and gender as determined by Pearson chi-square test (p=0.468).
The MCV, MCH, MCHC, packed cell volume (PCV), RBC count and red blood cell distribution width (RDW) were analysed and correlated with the grades of anaemia. The details are shown in Table 1. A statistically significant relation was found between severity of anaemia and MCV (p = 0.001), with MCH (p = <0.001), with PCV (p = <0.001) and RBC count (p = 0.003). MCV, MCH, and PCV were mild, moderate and severe anaemia, while RBC statistically significant which differed between count was significant only when compared between mild and moderate cases. A statistically non-significant relation was found between RDW and severity of anaemia (p = 0.537).
Iron profile and haemoglobin electrophoresis were done to corroborate the diagnosis. Out of the 78 cases of iron deficiency anaemia in this study, 57 were mild, 17 were moderate and only 4 cases were severe grade.
When Bonferroni Correction was applied as an adjustment for all pair-wise comparisons of means, there was a significant association between the MCV, MCH, and RBC counts and the three types of microcytic anaemia (IDA versus TT and ACD versus TT). MCV, MCH and RBC count were the most significant indices for comparison between IDA and TT as per the results of this study. For differentiating between IDA and ACD, no single index was found significant statistically.
Anaemia is functionally defined as an insufficient RBC mass to adequately deliver oxygen to peripheral tissues, thereby causing tissue hypoxia. Although red cell mass is the gold standard in the assessment of anaemia, its measurement is cumbersome and rarely performed outside of clinical research. Anaemia can also be defined as a reduction in haemoglobin (Hb) concentration, haematocrit or number of RBCs per cubic millimetre. As per the World Health Organization (WHO), the haemoglobin threshold for children aged 5.00 to 11.99 years is 11.5 g/dl and for children aged 12.00-14.99 years is 12.0 g/dl.
Iron deficiency is the most common nutritional deficiency in the world; responsible for a staggering amount of ill health, lost productivity, and premature death. Anaemia resulting from iron deficiency affects approximately 2 billion people or 34% of the world population. It accounts for 2.4 per cent of the total Disability Adjusted Life Years (DALYs) worldwide. In India, the NFHS-2 data indicates a fairly extensive prevalence of iron deficiency among the children between age 6-35 months portending a difficult future for children.
Iron is necessary for production of haemoglobin which contains more than one-half of the total-body iron. The demands for iron during erythropoiesis are created by three variables: tissue oxygenation, erythrocyte turnover, and erythrocyte loss from haemorrhage. Three pathogenic factors are implicated in the anaemia of iron deficiency. First, haemoglobin synthesis is impaired because of reduced iron supply. Second, there is a generalised defect in cellular proliferation. Third, the survival of erythroid precursors and erythropoiesis is reduced.[15,16]
The causes of iron deficiency in school children may be physiological or pathological. The physiological causes include rapid growth (puberty), menarche, blood loss, iron-poor diet, gastrointestinal diseases including peptic ulceration, Meckel diverticulum, celiac disease, inflammatory bowel disease, polyposis coli, milk-induced enteropathy, parasitic worms, as well as renal tract blood loss, idiopathic pulmonary haemosiderosis and bleeding diatheses.[18, 19]
Children with iron deficiency may present with no signs or symptoms and come to medical attention only because of abnormalities in laboratory tests; with the features of the underlying disorder responsible for the development of iron deficiency; with the manifestations common to all anaemias like lethargy and dyspnoea; or one or more of the few signs and symptoms considered highly specific for iron deficiency, namely, pagophagia, koilonychia, and blue sclerae.
The most concerning systemic effects in children are impaired intellectual and motor functions that can occur early in iron deficiency before anaemia develops and those might not even be fully reversible even after treatment. Laboratory evaluation reveals characteristic changes in blood parameters for iron regulation storage, transport, and utilization. Iron deficiency should be distinguished from other causes of anaemia because of its associations with underlying conditions that mandate specific investigation, and because treatment is simple, safe and effective. The important differential diagnosis is thalassaemic conditions in which iron therapy can lead to iron overload.[20, 21]
Inherited disorders of iron metabolism include congenital atransferrinemia (congenital absence of transferrin is an autosomal recessive condition), congenital microcytic hypochromic anaemia with iron overload and microcytic anaemia due to an isolated abnormality of malabsorption and defective utilization of iron.
A thorough history and careful physical examination are critical in the initial evaluation of the anaemic patient. The laboratory work-up of anaemia includes a complete blood count including red cell indices, reticulocyte count, and microscopic examination of the blood smear. In addition, in many cases a bone marrow examination may be a critical component of the initial laboratory assessment.[22-25]
Anaemia is classified as macrocytic (increased MCV), normocytic (normal MCV), or microcytic (decreased MCV) based on the MCV. The MCV is determined by the histogram of the red cell size distribution, based on electrical impedance, generated by the automated cell counter. The mean of the red blood cell distribution histogram is the MCV. The mean value in 6-12-year-old children is 86 femtolitres/cell (fL) with a standard deviation of 9.5.[10, 22, 26]
The red blood cell distribution width (RDW) measures variations in the size of RBCs. It is derived from the red cell size distribution histogram, representing a value derived from the coefficient of variation or, in some cases, the standard deviation. Due to its relatively low specificity, RDW is not as useful alone as a screening test, but it is used frequently in conjunction with MCV to differentiate among the various causes of anaemia. For example, RDW is high in iron deficiency anaemia, but low in thalassemia minor. The mean value as coefficient of variation (CV) is 12.8% with a standard deviation of 1.2 and as standard deviation (SD) is 42.5 fL with a standard deviation of 3.5.[27, 28]
In our study, the mean age of the children was similar to a study by Muthayya and Sudhagandhi et al. The female to male ratio in the present study was found to be 1.2:1 similar to Sudhagandhi’s study. However, in a study by Sabale et al, the prevalence of anaemia in female and male children was found to be almost equal. Verma et al in their study in Punjab found that anaemia was higher in girls over the age of 12 years. Thus, most of the studies conducted in India on the prevalence of anaemia in children showed a higher prevalence among girls compared to boys which could be explained by gender preference (better food intake in boys) and menorrhagia at menarche.
In the present study, mild anaemia in both boys and girls was more prevalent, followed by moderate anaemia. Mild anaemia was more common in some studies.[2, 29, 33] In our study, 81% had iron deficiency anaemia similar to other studies that were conducted.[34-38]
In our study the mean MCV, MCH and RBC counts in ACD, iron deficiency and thalassemia trait were similar to some studies[3, 39, 40] It was found that Milunsky in his text mentioned that MCV less than 60 fL and MCH less than 20 picograms (pg)/cell are considered indicators of a low probability of having IDA and a higher probability of thalassemia minor, which co-relate with our study. In a study by Madan et al, even values as MCV below 80 fL and MCH value below 27 pg were found to be very sensitive markers in the detection of beta thalassaemia.
As per Batebi, the RBC count is a valuable index for differentiation between IDA and TT with a high sensitivity but a low specificity. RBC count is increased in severe chronic cases of iron deficiency and in the initial response to treatment. RBC count and RDWI appear to be reliable and useful index for the differentiation of TT and IDA, as both indices have more than 80% sensitivity and specificity in the differentiation of IDA and beta-TT.[43, 44] RDWI was not done in this study.
It was observed in some studies,[45, 46] that there was an inverse relationship between RDW and the haemoglobin value, in iron deficiency anaemia. The sensitivity was 92.1% and specificity was 90.9% of RDW in detecting iron deficiency. However, RDW completely failed to differentiate between IDA and beta-TT. In our study also, RDW was not useful in differentiation between any of the microcytic anaemias.
In our study we concluded that haemoglobin and PCV does not differ significantly but MCV, MCH, and RBC count differ significantly, between thalassaemia trait and ACD and iron deficiency. Aslam et al. in their study had similar results. As per a study by Fahim and Ahmed, the most striking and consistent finding in typical heterozygous beta thalassaemia is the combination of a relatively high RBC count (> 5×1012/l), with a slightly low to normal haemoglobin and a disproportionate reduction of MCV and MCH in relation to the haemoglobin.
The findings of our study were comparable with most of the studies used for discrimination between IDA and TT. Low MCV, low MCH out of proportion to haemoglobin value and a high RBC count go largely in favour of TT. These indices combined with a thorough peripheral smear examination could diagnose TT cases efficiently.
Mild iron deficiency anaemia is the commonest type of microcytic anaemia in school-age children. The differentiation between iron deficiency anaemia and thalassaemia trait which is very important to prevent iron overload is possible with the RBC indices provided by the automated analyzers. The differentiation can further be aided by a detailed peripheral smear examination. These findings are useful in the Indian population where expensive tests cannot be afforded by many. The necessity to treat iron deficiency because of its effects on the growth and development of children must be emphasized.
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