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ORIGINAL ARTICLE  
Year : 2023  |  Volume : 66  |  Issue : 1  |  Page : 85-90
Z score analysis: A novel approach to interpretation of an erythrogram


1 Department of Pathology, Polo Labs, Mohali, Punjab, India
2 Department of Pathology, Polo Labs, Ivy Hospital, Mohali, Punjab, India
3 Department of Pathology, Dr. Ahujas' Pathology and Radiology Collection Centre, Dehradun, Uttarakhand, India

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Date of Submission08-Dec-2021
Date of Decision21-Jan-2022
Date of Acceptance24-Jan-2022
Date of Web Publication18-Jan-2023
 

   Abstract 


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.

Keywords: Anemia, MCH, MCHC, response, shift, spurious

How to cite this article:
Chauhan K, Bisht B, Kathuria K, Bisht R, Hatwal V. Z score analysis: A novel approach to interpretation of an erythrogram. Indian J Pathol Microbiol 2023;66:85-90

How to cite this URL:
Chauhan K, Bisht B, Kathuria K, Bisht R, Hatwal V. Z score analysis: A novel approach to interpretation of an erythrogram. Indian J Pathol Microbiol [serial online] 2023 [cited 2023 Feb 8];66:85-90. Available from: https://www.ijpmonline.org/text.asp?2023/66/1/85/367940





   Introduction Top


Studying the RBC indices in a hemogram is the first step in identifying anemia. In our daily practice, we come across hemograms that show a 'mismatch' in the level of hemoglobin, red cell count and red cell indices. Without prompt availability of clinical details, the reporting pathologist is usually left in a conundrum. For example, in hemolytic anemia, the destroyed red cells release hemoglobin (Hb) in the plasma. The cell counter which measures Hb after lysing RBCs overestimates the Hb for the number of RBCs counted. This can lead to misinterpretation of the patient's condition because Hb lying freely in the plasma does not transport oxygen to the tissues.[1],[2] Only the Hb present in red cells is capable of doing so. Interpretation of anemias and response to therapy requires peripheral smear (PS) examination and reticulocyte count assessment which takes time and mandates use of special dyes.[3] Interobserver variability is another limitation. Last but not the least there are spurious results in the hemogram mostly due to pre-analytical errors like sample collection, transport and storage which can again mislead the pathologist and the clinician. To help deal with the above mentioned scenarios, the authors propose a simple statistical tool known as 'Z score' to be applied on MCH and MCHC which can help identify and classify anemias, the extent of bone marrow response and spurious results.


   Materials and Methods Top


All samples with requisition of hemogram submitted to our laboratory over a period of 6 months from peripheral clinics, tertiary hospitals and in-house collections were included. This comprised the observation cohort. A total of 975 samples obtained were run on the DxH 500 hematology analyzer. Z score for MCH (Zmch) and MCHC (Zmchc) were computed from the obtained hemograms. Interpretation of Z score was derived from the patterns observed in reference to the standard method of diagnosis which included peripheral smear examination, serum iron profile, vitamin B12, folic acid levels, reticulocyte count and other relevant biochemical investigations. Hemograms of children (<10 years) were excluded from the study because the reference range for RBC indices is different from the adults and the sample size of pediatric hemograms in our laboratory is small. This study did not require ethics approval and it was clarified during scientific review that this is a retrospective study and data would be anonymized and collected as part of routine care. The reference interval for MCH and MCHC have been taken from the equipment DxH 500 hematology analyzer. Three levels of controls were run on daily basis and any outliers as per the Westgard rules' were corrected by taking an appropriate action

Statistical analysis

Z score

Z score is the number of standard deviations (SD) by which the observed value is away from the mean. Data points above the mean have positive z scores, while those below the mean have negative z scores. The standard definition of a reference range for a particular measurement is defined as the interval between which 95% of values of a reference population fall into, in such a way that 2.5% of the time a value will be less than the lower limit of this interval, and 2.5% of the time it will be larger than the upper limit of this interval.[4] For a normal distribution, the 95% interval can be defined as the interval limited by 1.96 (often rounded up to 2) standard deviations (SD) from either side of the mean. The common formula to calculate the reference range is: mean ± 1.96 (rounded up to 2) x SD.[4]

In other words, when a range is available,



L = lower limit, U = upper limitation

μ = mean, σ = standard deviation, x = observed value

For example, reference range for MCH as per DxH 500 is 26.5-33.5 pg



Similarly, for MCHC, the calculated mean and SD are 34.1 and 0.6 respectively

Once calculated, three main things need to be observed

  1. Direction of shift of z score with respect to mean (+=right side, -=left side)
  2. If the z score >2 (outside the defined range) or <2 (within the range)?
  3. Difference between Zmch and Zmchc (if the shift in both of them is towards the same side)


Chi-square (χ2) test was used to correlate z score interpretation of a diagnosis and the reference method. The reference method comprised peripheral smear examination of a Leishman stained blood film along with serum iron studies, vitamin B12, folic acid levels and other relevant biochemical investigations which were obtained from the laboratory information system. P value was obtained for each diagnosis which included iron deficiency anemia (IDA), beta thalassemia trait (BTT), megaloblastic anemia (MA), hemolytic anemias (HA), anemia of chronic disease (ACD), regenerative anemia post treatment and spurious findings, to determine the strength of association. For validation, an independent cohort of 100 samples was tested on Sysmex XN 550. Receiver operating characteristic (ROC) curve along with the area under curve (AUC) was used to describe the performance of z score in both observation and validation cohorts.

Observations

The 975 cases studied comprised 103 cases of IDA, 18 cases of BTT, 107 cases of MA, 88 cases of ACD, 37 cases of HA, 412 cases with spurious findings and 210 cases of anemias treated with hematinics. Z score was sensitive (>95%) in detecting MA (p <.001), HA (p <.001), HA (p <.001), regenerative anemias (p <.001) and spurious results in RBC indices (p <.001). The sensitivity was significantly low in BTT (22.2%, P = 0.09) followed by ACD (68.1%, P <.001) and IDA (72.8%, P <.001) respectively.(supplementary file). Receiver operating characteristics (ROC) curves were used to evaluate the predictive Z score and the reference standard method in both the derivation and validation cohort. Z score yielded an area under the curve (AUC) of 0.68 in the derivation cohort [Figure 1]a. AUC increased to 0.72 when tested in the validation cohort [Figure 1]b. It was found that Z score fails to be of much diagnostic importance in microcytic hypochromic (mchc) blood pictures especially in cases where IDA and BTT coexist because the state of relative erythrocytosis in BTT is countered by a decline in Hb due to coexisting IDA. This mandates the use of Hb. electrophoresis/HPLC which is the gold standard in diagnosing hemoglobinopathies. However for evaluation of response to treatment in IDA, Z score showed a perfect correlation with the reticulocyte count. ACD has a broad spectrum and includes anemia of renal disorders, liver disorders, inflammatory disorders etc., and thus can have a microcytic, normocytic or a macrocytic picture because of which MCHC keeps floating in either direction creating confusion with other diagnoses.
Figure 1: Receiver Operating Curves (ROC) with area under curve (AUC) for a) observation and b) validation cohort

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   Discussion Top


[Table 1] summarizes the several conditions described above with examples. Decrease in red cell count and HCT is not always proportional to Hb. For example, in IDA, Hb decreases first and the RBC count drops much later. Similarly, in macrocytic anemias the decline in RBCs is seen much before the decline in Hb. Hence comes the role of RBC indices (MCV, MCH, MCHC, RDW) in interpreting the correct RBC picture.[5],[6] MCV is directly measured by the cell counter. It defines the mean size of red cells. A change in MCV (microcytosis or macrocytosis) is either related to the bone marrow function or to the osmotic milieu of plasma or suspending media. But MCH (Hb/RBC × 10) and MCHC (Hb/PCV × 100) or (Hb/MCVxRBC × 100) are derived or calculated parameters. By determining the extent of change in MCH and MCHC brought about by Hb, RBC and MCV, the RBC picture can be better understood. The proposed Z score is a measure of deviation of an observed value from the mean. A score of more than '2'(on either side) implies that the observed value is outside the range. When the marrow is under stress to compensate for the RBC loss or when the nutritional deficiency is met, there is a spurt in the release of new RBCs which are called reticulocytes They are larger in size and exhibit polychromasia on romanowsky stain owing to their high RNA content. The hemoglobin content of these cells is suboptimal because of persistent nuclear remnants in the cytoplasm. To summarize, a regenerating marrow causes two main changes. 1) increase in RBC count and 2) increase in MCV. The former event causes a left shift in MCH because the RBC count has increased while Hb is the same. The later event causes an increase in HCT (MCVx RBC) which also shifts MCHC to the left. But because of an associated increase in MCV, the shift in MCHC is larger in comparison to MCH. In simple words, in a regenerative marrow Zmchc > Zmch with the difference being directly proportional to the reticulocyte count. Higher the difference, better is the response.
Table 1: Example cases (E) of each diagnostic type (by standard method) correctly interpreted by Z score

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Microcytic blood picture

IDA and BTT are the two main differentials in this category. As erythropoiesis is occurring in the marrow, hemoglobin synthesis continues simultaneously as the cell divides and matures into an orthochromatic erythroblast stage. Mature RBCs being devoid of ribosomes are unable to synthesize Hb.[7],[8] There is evidence suggesting a relationship between nuclear division and intracellular Hb. concentration. Hb enters into the nucleus through pores in the membrane. When a critical concentration is reached, Hb reacts with nucleohistones to cause chromosomal inactivation and nuclear condensation. Hence the number of cell divisions and the ultimate RBC size are related to the rate of Hb synthesis. Any disorder in either heme (IDA) or globin synthesis (BTT) prevents Hb to reach its critical concentration and in an attempt to achieve that critical value the RBC keeps dividing. Hence there are numerous smaller RBCs in IDA and thalassemia with suboptimal Hb levels. In other words, the RBC count is higher with respect to the Hb level which is reflected by a low MCH or hypochromia. In thalassemia, due to an additional hemolytic component (intramedullary hemolysis), the RBC count is even higher than that seen in IDA.[9],[10] So MCH is much lower in BTT. In other words, Zmch > Zmchc in BTT (E3). On the other hand, in IDA, Zmchc > Zmch (E1). In untreated cases of IDA, the difference is usually less than 2. But as the marrow starts to respond to iron supplementation, there is a marked increase in the difference (E2). However it was observed that the sensitivity and specificity of Z score decreases in differentiating BTT from untreated IDA when the Zmchc is greater than Zmch by a difference less than or equal to 2 as seen in (E4) and (E5). In other words, Z score analysis may not be helpful in differentiating and diagnosing BTT and IDA, especially when the two coexist, but is very sensitive in estimating the response to iron therapy in a known case of IDA. Serum iron profile and Hb. electrophoresis/HPLC are the definite diagnostic methods for BTT and IDA.

Macrocytosis

Vit. B12 and folic acid (FA) deficiency impairs methionine synthase reaction which ultimately results in an arrest of nuclear division in hematopoietic precursors in various stages which causes asynchronous nuclear cytoplasmic maturation.[11] The change is most apparent in erythroid precursors. Presence of macro ovalocytes and hypersegmented neutrophils in peripheral smear are diagnostic of megaloblastic anemia.[12] Decrease in red blood cell count precedes the decrease in hemoglobin because retarded nuclear maturation interferes with cell division and replication. This is why anemia or pallor is not often seen in initial stages. As a result, MCH shifts towards right (Zmch >2) and can be considered as the first sign of B12/FA deficiency. In hemolytic types of MA (intramedullary hemolysis of dyspeptic erythroid precursors), the marrow attempts to compensate by regenerating more precursors but fails because of the ineffective erythroid maturation.[13],[14],[15] Hence HCT is also low which shifts MCHC as well to the right (Zmchc >2) but Zmch > Zmchc because the B12/FA deficient RBCs are larger in size (E6). In non-hemolytic type of MA, the shift in MCH and MCHC is in opposite directions such that Zmch >2 (right side) and Zmchc <2 (left side) because the RBC is low but the HCT is normal or high due to macrocytosis (E8). Post therapy, due to release of new RBCs, MCH moves towards the mean or may even shift to the opposite side but stays within the 2sd range unlike MCHC which shifts outside the 2sd range (left side) (E7, E9).

Hemolytic anemias (HA)

An acute episode of hemolysis (in vivo) due to autoimmune causes, toxin/drug mediated lysis or (in-vitro) due to wrong phlebotomy practices, improper storage and transportation and sample degeneration, leads to a decline in both RBCs HCT. Hb levels are unaffected.[16],[17] This leads to a right shift in MCH and MCHC such that Zmchc > Zmch. The in-vitro and in-vivo causes can be differentiated on clinical grounds by examining for any hemoglobinemia or hematuria or organomegaly (E11). As regeneration is a process occurring in vivo, the difference 'Zmchc-Zmch' begins to decrease because there is stress reticulocytosis[16] which can also be predicted by an increased RDW (E10). A pure regenerative anemia (where the cause has been cured completely) will shift MCH and MCHC towards the left side of the mean such that Zmchc > Zmch (E13).

Anemia of chronic diseases (ACD)

Anemia observed in patients with infections, inflammatory or neoplastic diseases that persists for more than 1-2 months is called ACD. This category also includes anemia of renal disease, anemia of liver disease and endocrine disorders related anemias because the pathogenesis is interrelated and the final outcome is a non-regenerative anemia. This anemia is characterized by an occurrence of hypoferremia in the presence of ample reticuloendothelial iron stores. The RBCs are usually normocytic and normochromic (ncnc) however hypochromia and microcytosis may be observed but is not as striking as in IDA.[18] RDW may be normal or high but reticulocytosis is not usually observed (E12). The three main causes associated with ACD are 1) shortened RBC life span. 2) impaired marrow response due to decreased EPO secretion by a diseased kidney or cytokines. 3) disturbance in iron metabolism in which there is a predilection of shift in iron from a transferrin bound available state to a ferritin incorporated storage state in macrophages.[19],[20] ACD is associated both with an insufficient erythropoiesis and ineffective hemoglobinization. This results in a decrease in both RBC count and Hb concentration, though the decline is not always proportional. As a result, MCH and MCHC keep oscillating near the mean value. This is why it can mimic many other conditions and the sensitivity of Z score is comparatively less. Further assistance can be provided by the H&H rule which provides a rough estimate of Hb and HCT [Figure 2]
Figure 2: Algorithm describing the H and H rule

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   Spurious results Top


There are instances where the hematology cell counters may give artifactual results. The changes henceforth brought in the parameters can be misinterpreted and lead to deleterious consequences. For example, turbid samples as seen in patients with hyperlipidemic disorders are the commonest cause of falsely elevated Hb.[21],[22] Spuriously high Hb with unaffected RBC count and MCV will cause false elevation in MCH and MCHC. Similarly, pseudo elevated MCH and MCHC are also seen in in-vitro hemolyzed samples which can be due to faulty collection and storage practices. But here the cause is decrease in RBC count and HCT. Visual inspection of the plasma after centrifugation can help in differentiating the causes. (E16) RBC count may be falsely decreased in EDTA dependent panagglutination, cold agglutinin disease and in multiple myeloma where there is rouleaux formation. In these instances, clumps of RBCs are counted as single cells causing an artificial elevation in MCV. The hemogram may look similar to that of MA. This warrants a peripheral smear examination. MCV >110 fl can only be seen in MA. Hyperosmolar states like hyperglycemia, hypernatremia and EDTA excess due to suboptimal quantity of sample in vial can cause pseudo elevation of MCV because in the body, RBCs exist in a hyperosmolar state which causes them to contract. Later on when placed in an isotonic diluent (in the machine), the RBCs swell. MCH remains unaffected but MCHC becomes falsely low owing to a high MCV. Prolonged storage of samples (>24 hours) and non fulfilment of cold chain can cause degeneration and swelling of RBCs which causes pseudo elevation in MCV and HCT. In simple words, cases with high MCV, high HCT and low MCHC in the absence of anemia should raise a suspicion of degenerative changes in RBCs.[23] Hemoconcentration can be in vivo due to dehydration, fluid loss in burns or it can be in vitro when the tourniquet is left tied on for a long time during phlebotomy. In vivo, the body fluid osmotic pressure is maintained by the adaptive mechanisms due to which the size of RBCs is not affected. But there is a pseudo elevation of Hb and RBC. (E14) In vitro hemoconcentration creates a hypoosmolar environment due to which RBCs swell initially and then contract in the machine diluent leading to a pseudodepression in MCV.[24],[25] Hence MCH becomes falsely low due to a pseudo increase in RBC count and MCHC is falsely normal or high because of a low MCV. (E15) Similar change in the hemogram is also seen in overfilled EDTA vials where the RBCs are suspended in a hypo-osmolar medium.[26] In other words if MCH is moving towards the left side of the mean, MCHC cannot move towards the right side because a microcytic RBC can never be hyperchromic or normochromic


   Conclusions Top


Hemogram is one of the first investigations ordered in all patients. Any significant abnormality in the hemogram validates and directs further actions in patient management and treatment. However, its significance in direct interpretation of anemias, preanalytical errors and accuracy of machine results, is not studied much. With a high specificity and sensitivity, the Z score can be of immense help to the clinicians and pathologists in making quick interpretation of the underlying red cell abnormality especially in cases received from peripherals where there are transport and storage related issues (degeneration, lysis etc.) Also, it can be used as a quality assessment tool in hematology laboratories taking preanalytical and analytical factors into account. Z score application on hemograms run at the cognate site, may reduce the dependency on peripheral smears for interpretation of anemias. This will significantly save resources and decrease the turnaround time of reporting. There do exist cases where the Z score application may not perfectly correlate with the diagnosis or may have many differentials. This re-establishes the fact that peripheral smear examination will always remain the gold standard for classification of anemias. Incidences like rouleaux formation, RBC agglutination which cause pseudo decrease in RBC count and elevation in MCV can mimic a megaloblastic anemia on hemogram. Also, interferences caused by giant platelets (falsely elevated RBCs) and fragmented RBCs (false decrease in RBCs) can only be excluded by light microscopic examination of smears. Hb. electrophoresis/HPLC is the gold standard for diagnosing hemoglobinopathies and for differentiating between IDA from BTT.

The findings of this study have been summarized in [Figure 3].
Figure 3: Chart summarizing the findings of Z score analysis

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Acknowledgements

The authors are extremely thankful to the technical staff of hematology department especially Mrs. Satvir for her help in running this series of experiments and retrieving patient details.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Mcgrath JP. Assessment of hemolytic and hemorrhagic anemias in preclinical safety assessment Studies. Toxicol Pathol 1993;21:158-63.  Back to cited text no. 1
    
2.
Sandhaus LM, Meyer P. How useful are CBC and reticulocyte reports to clinicians? Am J Clin Pathol 2002;118:787–93.  Back to cited text no. 2
    
3.
Brugnara C. Reticulocyte cellular indices: A new approach in the diagnosis of anemias and monitoring of erythropoietic function. Crit Rev Clin Lab Sci 2000;37:93-130.  Back to cited text no. 3
    
4.
Sterne JA, Kirkwood BR. Essential Medical Statistics, 2nd ed. Oxford: Blackwell Science; 2003.  Back to cited text no. 4
    
5.
Doig K, Zhang B. A Methodical approach to interpreting the red blood cell parameters of the complete blood count. ASCLS 2017;30:173-85.  Back to cited text no. 5
    
6.
Sarma PR. Red cell indices. In: Walker HK, Hall WD, Hurst JW, editors. Clinical Methods: The History, Physical, and Laboratory Examinations. 3rd ed. Boston: Butterworths; 1990. Chapter 152.  Back to cited text no. 6
    
7.
Conrad ME, Umbreit JN. Pathways of iron absorption. Blood Cells Mol Dis 2002;29:336-55.  Back to cited text no. 7
    
8.
Firkin F, Rush B. Interpretation of biochemical tests for iron deficiency: Diagnostic difficulties related to limitations of individual tests. Aust Prescr 1997;20:74-6.  Back to cited text no. 8
    
9.
Galanello R, Origa R. Beta-thalassemia. Orphanet J Rare Dis 2010;5:11.  Back to cited text no. 9
    
10.
Muncie HL Jr, Campbell J. Alpha and beta thalassemia. Am Fam Physician 2009;80:339-44.  Back to cited text no. 10
    
11.
Nagao T, Hirokawa M. Diagnosis and treatment of macrocytic anemias in adults. J Gen Fam Med 2017;18:200-4.  Back to cited text no. 11
    
12.
Aslinia F, Mazza JJ, Yale SH. Megaloblastic anemia and other causes of macrocytosis. Clin Med Res 2006;4:236–41.  Back to cited text no. 12
    
13.
Waheed MA, Elzouki A. Vitamin B12 deficiency presenting as hemolytic anemia. Libyan J Med Sci 2018;2:114-5.  Back to cited text no. 13
  [Full text]  
14.
Veit K. Pseudothrombotic microangiopathy and vitamin B12 deficiency in pernicious anemia. Proc (Bayl Univ Med Cent) 2017;30:346-7.  Back to cited text no. 14
    
15.
Sasi S, Yassin M. A rare case of Acquired hemolytic anemia and pancytopenia secondary to Pernicious Anemia. Case Rep Oncol 2020;13:783-8.  Back to cited text no. 15
    
16.
Leonid LY. Elevated hemoglobin and macrocytosis: A neglected association to become a diagnostic tool (A Case Report). Perm J 2021;25:262.  Back to cited text no. 16
    
17.
Alder L, Tambe A. Acute Anemia. In: StatPearls. Treasure Island (FL): StatPearls Publishing; 2021. [Updated 2020 Jul 19].  Back to cited text no. 17
    
18.
Nairz M, Theurl I, Wolf D, Weiss G. Iron deficiency or anemia of inflammation?: Differential diagnosis and mechanisms of anemia of inflammation. Wien Med Wochenschr 2016;166:411-23.  Back to cited text no. 18
    
19.
Peng YY, Uprichard J. Ferritin and iron studies in anaemia and chronic disease. Ann Clin Biochem 2017;54:43-8.  Back to cited text no. 19
    
20.
Feelders RA, Vreugdenhil G, Eggermont AM, Kuiper-Kramer PA, van Eijk HG, Swaak AJ. Regulation of iron metabolism in the acute-phase response: Interferon gamma and tumour necrosis factor alpha induce hypoferremia, ferritin production and a decrease in circulating transferrin receptors in cancer patients. Eur J Clin Invest 1998;28:520-7.  Back to cited text no. 20
    
21.
Cornbelt J. Spurious results from automated hematology cell counters. Lab Med 1983;14:509–14.  Back to cited text no. 21
    
22.
Guder WG, da Fonseca-Wollheim F, Heil W, Schmitt YM, Topfer G, Wisser H, et al. The haemolytic, icteric and lipemic sample recommendations regarding their recognition and prevention of clinically relevant interferences. J Lab Med 2000;24:357-64.  Back to cited text no. 22
    
23.
Zandecki M, Genevieve F, Gerard J, Godon A. Spurious counts and spurious results on haematology analysers: A review. Part II: White blood cells, red blood cells, haemoglobin, red cell indices and reticulocytes. Int J Lab Hematol 2007;29:21-41.  Back to cited text no. 23
    
24.
Godon A, Genevieve F, Marteau-Tessier A, Zandecki M. Automated hematology analysers and spurious counts. Part 3. Haemoglobin, red blood cells, cell count and indices, reticulocytes. Ann Biol Clin (Paris) 2012;70:155-68.  Back to cited text no. 24
    
25.
Decaux G, Efira A, Dhaene M, Unger J. Interference of serum tonicity with the measurement of red cell mean corpuscular volume. Acta Haematol 1982;67:62-6.  Back to cited text no. 25
    
26.
Beautyman W, Bills T. Osmotic error in erythrocyte volume determinations. Am J Hematol 1982;12:383-9.  Back to cited text no. 26
    

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Kriti Chauhan
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DOI: 10.4103/ijpm.ijpm_1188_21

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