Comparison of the Characteristics of Patients with diabetes as Diagnosed Using Three Different Tests

Jaehoon Choi; Ile Kyu Park

doi:10.3343/lmo.2014.4.2.71

Journal List > Lab Med Online > v.4(2) > 1057259

Go to TopGo to Top Go to BottomGo to Bottom

TOOLS

Choi and Park: Comparison of the Characteristics of Patients with diabetes as Diagnosed Using Three Different Tests

Original Article

Clinical Chemistry

Laboratory Medicine Online 2014; 4(2): 71-76.

Published online: 1 April 2014

DOI: https://doi.org/10.3343/lmo.2014.4.2.71

Comparison of the Characteristics of Patients with diabetes as Diagnosed Using Three Different Tests

Jaehoon Choi, M.D., Ile Kyu Park, M.D.

Department of Laboratory Medicine, Hanyang University School of Medicine, Seoul, Korea.

Corresponding author: Ile Kyu Park. Department of Laboratory Medicine, Hanyang University School of Medicine, 222 Wangsimni-ro, Seongdong-gu, Seoul 133-792, Korea. Tel: +82-31-560-2573, Fax: +82-31-560-2585, ikpark@hanyang.ac.kr

Received 17 April 2013 Revised 2 August 2013 Accepted 5 August 2013

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Diabetes diagnosis can be made using different laboratory tests, including the fasting plasma glucose (FPG) test, 75-g 2-h oral glucose tolerance test (2-h OGTT), and hemoglobin A1c (HbA1c) test; however, these tests have different meanings. This study aimed at comparing patient characteristics based on the diagnosis using each of these 3 tests.

Methods

A total of 750 adults suspected of having diabetes and aged ≥18 years underwent the following tests on the same day: FPG, 2-h OGTT, HbA1c, insulin, general chemistry, and routine urinalysis. The patients were divided into 8 groups based on the combination of positive and negative results of each of the 3 tests, and the characteristics of the patients were compared among groups.

Results

In the group that tested positive for all 3 tests, the FPG, 2-h OGTT, HbA1c, homeostasis model assessment for insulin resistance, alanine transaminase, triglyceride, and urine glucose positive values were higher than those of the group that tested positive using the 2-h OGTT and HbA1c test. In the group that tested positive using the 2-h OGTT, blood urea nitrogen was higher than that of the group that tested positive using the HbA1c test.

Conclusions

The characteristics of the patients differed between the tests that yielded positive diagnostic results. This may be related to the fact that the 3 tests indicate different states of glucose metabolism. The results of the 3 tests were significantly different; therefore, it may be more effective to combine the results of the 3 tests to comprehensively describe patient characteristics.

Keywords: Diabetes mellitus, Diagnosis, Difference

Figures and Tables

Fig. 1

Venn diagram shown 8 groups of the patients classified by each results of separate three tests. Group A: All tests are negative.

Table 1

Characteristics of the patients classified by result of separate three tests

Abbreviations: F, Fasting blood glucose; O, 2hr Oral glucose tolerance test; H, HbA1c.

Table 2

Comparison of biochemical characteristics based on the FBG result difference

^*Chi-square test.

Abbreviations: FBG, Fasting blood glucose; 2hr-OGTT, Oral glucose tolerance test; HbA1c, Hemoglobin A1c; N, Negative; P, Positive; HOMA-IR, Homeostatic model assessment-insulin resistant.

Table 3

Comparison of biochemical characteristics based on the different results between 2hr-OGTT and HbA1c

^*Chi-square test.

Abbreviations: FBG, Fasting blood glucose; 2hr-OGTT, Oral glucose tolerance test; HbA1c, Hemoglobin A1c; N, Negative; P, Positive; HOMA-IR, Homeostatic model assessment-insulin resistant.

Notes

This article is available from http://www.labmedonline.org

References

1. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care. 1997; 20:1183–1197.

2. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2010; 33:S1. S11–S61.

3. Nathan DM, Turgeon H, Regan S. Relationship between glycated haemoglobin levels and mean glucose levels over time. Diabetologia. 2007; 50:2239–2244.

4. Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. A1c-Derived Average Glucose Study Group. Translating the A1C assay into estimated average glucose values. Diabetes Care. 2008; 31:1473–1478.

5. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28:412–419.

6. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care. 2004; 27:1487–1495.

7. National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes. 1979; 28:1039–1057.

8. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2012; 35:S1. S64–S71.

9. Sacks DB. A1C versus glucose testing: a comparison. Diabetes Care. 2011; 34:518–523.

10. Edelman SV. Type II diabetes mellitus. Adv Intern Med. 1998; 43:449–500.

11. Guyton AC, Hall JE, editors. Gyuton and Hall Textbook of Medical Physiology. 12th edition. Saunders: Elsevier;2011.

12. Esteghamati A, Noshad S, Khalilzadeh O, Khalili M, Zandieh A, Nakhjavani M. Insulin resistance is independently associated with liver aminotransferases in diabetic patients without ultrasound signs of nonalcoholic fatty liver disease. Metab Syndr Relat Disord. 2011; 9:111–117.

13. Koskinen J, Magnussen CG, Kähönen M, Loo BM, Marniemi J, Jula A, et al. Association of liver enzymes with metabolic syndrome and carotid atherosclerosis in young adults. The Cardiovascular Risk in Young Finns Study. Ann Med. 2012; 44:187–195.

14. Yun JE, Kim SY, Kang HC, Lee SJ, Kimm H, Jee SH. Alanine aminotransferase is associated with metabolic syndrome independently of insulin resistance. Circ J. 2011; 75:964–969.

15. Gao F, Pan JM, Hou XH, Fang QC, Lu HJ, Tang JL, et al. Liver enzymes concentrations are closely related to prediabetes: findings of the Shanghai Diabetes Study II (SHDS II). Biomed Environ Sci. 2012; 25:30–37.

16. Angulo P. Nonalcoholic fatty liver disease. N Engl J Med. 2002; 346:1221–1231.

17. Yueh CY, Chen JH, Lee LW, Lu CW, Parekh B, Chi CC. Elevated alanine aminotransferase is associated with metabolic syndrome but not consistently associated with impaired fasting glucose or type 2 diabetes mellitus. Diabetes Res Clin Pract. 2011; 94:64–70.

18. Andres R. Aging and diabetes. Med Clin North Am. 1971; 55:835–846.

19. Reaven GM. Does age affect glucose tolerance? Geriatrics. 1977; 32:51–54.

20. Carrera T, Bonamusa L, Almirall L, Navarro JM. Should age and sex be taken into account in the determination of HbA1c reference range? Diabetes Care. 1998; 21:2193–2194.

21. Yang YC, Lu FH, Wu JS, Chang CJ. Age and sex effects on HbA1c. A study in a healthy Chinese population. Diabetes Care. 1997; 20:988–991.

22. Burden ML, Basi M, Burden AC. HbA1c local reference ranges: Effects of age, sex and ethnicity. Practical Diabetes Int. 1999; 16:211–214.

23. Inoue M, Inoue K, Akimoto K. Effects of age and sex in the diagnosis of type 2 diabetes using glycated haemoglobin in Japan: the Yuport Medical Checkup Centre study. PLoS One. 2012; 7:e40375.

24. World Health Organization. Definition, diagnosis and classification of diabetes mellitus and its complications: report of a WHO consultation. Part 1: diagnosis and classification of diabetes mellitus. Geneva: World Health Organization;1999.

25. Lee YW, Cha YJ, Chae SL, Song J, Yun YM, Park HI, et al. Effectiveness of sodium fluoride as a glycolysis inhibitor on blood glucose measurement: comparison of blood glucose using specimens from the Korea National Health and Nutrition Examination survey. Korean J Lab Med. 2009; 29:524–528.

TOOLS

Similar articles