ESTIMATION OF HEMOGLOBIN A1C USING THE COMPLETE BLOOD COUNT MEASURES IN THE DIAGNOSIS OF DIABETES
Â Objective: Diabetes is a metabolic disorder occurring either due to the inadequate secretion of insulin or ineffective utilization of insulin by the body. The study was aimed to identify the variations of the complete blood count (CBC) parameters among the diabetic and normal individuals and to derive an empirical formula to estimate hemoglobin A1c (HbA1c) of an individual using CBC parameters.
Methods: A total of 83 subjects (mean age: 52.8Â±9.0 years) involved in the study, among which 39 (mean age: 49.1Â±8.8 years) were normal and 44 (mean age: 56Â±7.8 years) were diabetic. The blood was drawn from the participants and was subjected to CBC analysis using automated hematology analyzer. The stepwise linear regression model was used to determine the empirical formula to estimate HbA1c using the CBC parameters. The Studentâ€™s t-test was performed to identify the group differences.
Results: A negative correlation was observed for Hb (r=âˆ’0.35**, p<0.001) and packed cell volume (PCV) (r=âˆ’0.23**, p<0.05) against HbA1c. The CBC parameters Hb, erythrocyte sedimentation rate, PCV, red blood cells count, mean corpuscular volume, and mean corpuscular Hb exhibited a statistically significant difference at the level (p<0.05) between the normal and diabetic groups. The empirically derived formula yielded sensitivity, specificity, positive predictive value, negative predictive value, and accuracy measures of 91%, 49%, 67%, 83%, and 71%, respectively, in diagnosing diabetes based on the estimated HbA1c.
Conclusion: The empirical formula derived to estimate HbA1c could be useful in the prediction of diabetes with an appreciable accuracy.
2. Ibrahim R. Diabetes mellitus Type II: Review of oral treatment options. Int J Pharm Pharm Sci 2010;2(1):21-30.
3. Roglic G, Unwin N, Bennett PH, Mathers C, Tuomilehto J, Nag S, et al. The burden of mortality attributable to diabetes: Realistic estimates for the year 2000. Diabetes Care 2005;28(9):2130-5.
4. Palanisamy V, Mariamichael A. Diagnosis of diabetes mellitus by extraction of morphological features of red blood cells using an Artificial neural network. Exp Clin Endocrinol Diabetes 2016;124(9):548-56.
5. China Faces â€œDiabetes Epidemicâ€, Research Suggests. BBC. March 25; 2010.
6. Gale J. Indiaâ€™s Diabetes Epidemic Cuts Down Millions Who Escape Poverty. Bloomberg. November 7; 2010. Available from: http://www. fullertreacymoney.com. [Last retrieved on 2012 Jun 08].
7. Diabetes can be Controlled in 80 Percent of Cases in India. IANS. News. Available from: http://www.biharprabha.com. [Last retrieved on 2014 Feb 06].
8. Indian Heart Association Why South Asians Facts Web. 30 April; 2015. Available from: http://indianheartassociation.org/why-indians-why-south-asians/overview/. [Last retrieved on ???AQ1 ].
9. Wild S, Roglic G, Green A, Sicree R, King H. Global prevalence of diabetes. Diabetes Care 2004;27(5):1047-53.
10. Kleinfield NR. Modern Ways Open Indiaâ€™s Doors to Diabetes. New York Times: New York Times; 2006. [Last retrieved on 2012 Jun 8].
11. Saladin KS. Anatomy and Physiology: The Unity of Form and Function. 7th ed. New York: McGraw-Hill; 2007.
12. Vuong J, Qiu Y, La M, Clarke G, Swinkels DW, Cembrowski G. Reference intervals of complete blood count constituents are highly correlated to waist circumference: Should obese patients have their own â€œnormal values?â€ Am J Hematol 2014;89(7):671-7.
13. Mohan V, Vijayachandrika V, Gokulakrishnan V, Anjana RM, Ganesan A, Weber MB, et al. A1c cut points to define various glucose intolerance groups in Asian Indians. Diabetes Care 2010;33(3):515-9.
14. Chinmay S, Manjula SD, Bekur R, Rao KR. Association of increased levels of glycated haemoglobin with variations in red blood cell parameters in diabetic mellitus. Int J Adv Res 2015;3(6):31-7.
15. De Keijzer MH, van der Meer W. Automated counting of nucleated red blood cells in blood samples of newborns. Clin Lab Haematol 2002;24(6):343-5.
16. Babu N, Singh M. Influence of hyperglycemia on aggregation, deformability and shape parameters of erythrocytes. Clin Hemorheol Microcirc 2004;31(4):273-80.
17. Manjunatha M, Singh M. Digital analysis of induced erythrocyte shape changes in hypercholesterolemia under in vitro conditions. Curr Sci 2000;79(11):1589-91.
18. Kanakaraj P, Singh M. Influence of hypercholesterolemia on morphological and rheological characteristics of erythrocytes. Atherosclerosis 1989;76(2-3):209-17.
19. Bessis M. Red cell shapes. An illustrated classification and its rationale. Heidelberg Springer; 1973.
20. Marchesi VT. The red cell membrane skeleton: Recent progress. Blood 1983;61(1):1-11.
21. Lowe GD. Clinical Blood Rheology. Vol. 1. Boca Raton: CRC Press; 1988.
22. Chien S, Dormandy J, Ernst E, Matrai A. Clinical Hemorheology. Boston: M. Nijhoff; 1987.
23. Stoltz JF, Singh M, Riha P. Hemorheology in Practice. Amsterdam: IOS Press; 1999.
24. Alam J, Mallik SC, Mukti MN, Hoque M, Hasan M, Islam S, et al. A comparative analysis of biochemical and hematological parameters in diabetic and non-diabetic adults. Adv Med Sci Int J 2015;2(1):1-9.
25. Ifeanyichukwu MO, Esan AJ. Evaluation of haemoglobin concentration, packed cell volume and red cell indices in pre-and post-anti-malaria drug treatment in plasmodium falciparum malaria infected and control individuals. Glob Adv Res J Microbiol 2014;3(2):2-7.
26. Yuvraj V, Indumathi J, Singh M. Effects of cigarette smoking on morphology and aggregation of erythrocytes. Clin Hemorheol Microcirc 2012;51:169-75.
27. Trinder P. Determination of glucose in blood using glucose oxidase with an alternative oxygen acceptor. Ann Clin Biochem 1969;6:24-7.
28. Bry L, Chen PC, Sacks DB. Effects of haemoglobin variants and chemically modified derivatives on assays for glycohemoglobin. Clin Chem 2001;47(2):153-63.
29. Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1C assay into estimated average glucose values. Diabetes Care 2008;31(8):1473-8.
30. Singh M, Shin S. Changes in erythrocyte aggregation and deformability in diabetes mellitus: A brief review. Indian J Exp Biol 2009;47(1):7-15.
31. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2011;34(1):S11-61.
32. Khanam S, Begum N, Hoque AM. Relationship of hemoglobin, packed cell volume and total count of RBC with the severity of chronic renal failure. Chattagram Maa-O-Shishu Hosp Med Coll J 2013;12(2):31-4.
33. Sakpa CL, Idemudia JO. Relationship between glycated haemoglobin, fasting plasma glucose, packed cell volume and albumin creatinine ratio in diabetic patients in South-South Nigeria. Br J Med Med Res 2014;4(2):766-75.