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The clinical and biochemical profiles of patients with IFG

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Abstract

To study the clinical and biochemical profiles across the different ranges of impaired fasting glucose (IFG) based on American Diabetes Association (ADA) and World Health Organization (WHO) criteria. A cross-sectional study was conducted on 149 subjects, of which 63 belonged to group 1 (IFG = 100–110 mg/dl) and 86 to group 2 (IFG = 111–125 mg/dl). Basic anthropometric and clinical examinations were done for all subjects. Data was collected from patient by a questionnaire, which included the history of hypertension and diabetes and other comorbidities and complications. Biochemical profiles including Fasting Plasma Glucose (FPG), Oral Glucose Tolerance Test (OGTT), HbA1c, Fasting insulin levels and Fasting Lipid Profile were measured. Assessment of insulin resistance and beta cell function was done by Homeostasis Model Assessment (HOMA). Data were analysed using SPSS software version 15 and p < 0.05 considered as statistically significant. Family history of diabetes, prevalence of hypertension and higher BMI were noted to be significant higher in group 2 compared to group 1. Clustering of cardiovascular risk factors suggesting metabolic syndrome was also much higher in group 2 (60.5 vs 39.7% p value = 0.012). Impaired glucose tolerance was significantly higher in group 2 (73.3 vs 28.6 p < 0.001) denoting more glycemia. Insulin resistance (HOMA-IR) was significantly higher in group 2 (p = 0.001). Beta cell function (HOMA-β) was also higher in group 2 but not statistically significant (p = 110). In IFG, the higher range of blood sugar 111 to 125 mg/dl is associated with more glycemia, cardiovascular risk factors and insulin resistance. Beta cell function though higher in this group is inadequate to compensate for higher insulin resistance.

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References

  1. National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes. 1979;28(12):1039–57.

    Article  Google Scholar 

  2. World Health Organisation. Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care. 1997;20(7):1183–97.

  3. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med. 2006 May 1;23(5):469–80.

    Article  CAS  PubMed  Google Scholar 

  4. Cassidy JP, Luzio SD, Marino MT, Baughman RA. Quantification of human serum insulin concentrations in clinical pharmacokinetic or bioequivalence studies: what defines the “best method”? Clin Chem Lab Med. 2012 Apr 1;50(4):663–6.

    Article  CAS  PubMed  Google Scholar 

  5. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modelling. Diabetes Care. 2004;27:1487–95.

    Article  PubMed  Google Scholar 

  6. Nishio K, Fukui T, Tsunoda F, Kawamura K, Itoh S, Konno N, et al. Insulin resistance as a predictor for restenosis after coronary stenting. Int J Cardiol. 2005;103:128–34.

    Article  PubMed  Google Scholar 

  7. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972 Jun 1;18(6):499–502.

    CAS  Google Scholar 

  8. Wagner R, Thorand B, Osterhoff MA, Muller G, Bohm A, Meisinger C, et al. Family history of diabetes is associated with higher risk for prediabetes: a multicentre analysis from the German Center for Diabetes Research. Diabetologia. 2013;56(10):2176–80. https://doi.org/10.1007/s00125-013-3002-1.

    Article  CAS  PubMed  Google Scholar 

  9. Morio M, Inoue M, Inoue K, Akimoto K. Impaired fasting glucose as an independent risk factor for hypertension among healthy middle-aged Japanese subjects with optimal blood pressure: the Yuport Medical Checkup Centre retrospective cohort study. Diabetol Metab Syndr. 2013;5(1):81. https://doi.org/10.1186/758-5996-5-81.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Mohan V, Deepa M, Anjana RM, Lanthorn H, Deepa R. Incidence of diabetes and pre-diabetes in a selected urban south Indian population (CUPS-19). J Assoc Physicians India. 2008;56:152–7.

    CAS  PubMed  Google Scholar 

  11. Reaven GM. Relationship between insulin resistance and hypertension. Diabetes Care. 1991;14(11):33–8.

    Article  PubMed  Google Scholar 

  12. Thompson JL, Herman CJ, Allen P, Helitzer DL, Wilson ND, Whyte AN, et al. Associations between body mass index, cardiorespiratory fitness, metabolic syndrome, and impaired fasting glucose in young, urban native American women. Metab Syndr Relat Disord. 2007;5(1):45–54. https://doi.org/10.1089/met.2006.0015.

    Article  PubMed  Google Scholar 

  13. Lee DC, Sui X, Church TS, Lee IM, Blair SN. Associations of cardiorespiratory fitness and obesity with risks of impaired fasting glucose and type 2 diabetes in men. Diabetes Care. 2009;32(2):257–62. https://doi.org/10.2337/dc08-1377.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Shweta Sahai DV, Sharma S. Impaired fasting glucose: a study of its prevalence documented at a tertiary care centre of central India and its association with anthropometric variables. J Indian Acad Clin Med. 2011;12(3):187–92.

    Google Scholar 

  15. Lorenzo C, Wagenknecht LE, Hanley AJ, Rewers MJ, Karter AJ, Haffner SM. A1C between 5.7 and 6.4% as a marker for identifying pre-diabetes, insulin sensitivity and secretion, and cardiovascular risk factors: the Insulin Resistance Atherosclerosis Study (IRAS). Diabetes Care. 2010;33(9):2104–9. https://doi.org/10.2337/dc10-0679.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Mohan V, Vijayachandrika V, Gokulakrishnan K, 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. https://doi.org/10.2337/dc09-1694.

    Article  CAS  PubMed  Google Scholar 

  17. Nathan DM, Davidson MB, DeFronzo RA, Heine RJ, Henry RR, Pratley R, et al. Impaired fasting glucose and impaired glucose tolerance: implications for care. Diabetes Care. 2007;30(3):753–9.

    Article  CAS  Google Scholar 

  18. Meyer C, Pimenta W, Woerle HJ, Van Haeften T, Szoke E, Mitrakou A, et al. Different mechanisms for impaired fasting glucose and impaired postprandial glucose tolerance in humans. Diabetes Care. 2006;29(8):1909–14.

    Article  CAS  PubMed  Google Scholar 

  19. Festa A, D’Agostino R Jr, Hanley AJ, Karter AJ, Saad MF, Haffner SM. Differences in insulin resistance in nondiabetic subjects with isolated impaired glucose tolerance or isolated impaired fasting glucose. Diabetes. 2004;53(6):1549–55.

    Article  CAS  PubMed  Google Scholar 

  20. Wasada T, Kuroki H, Katsumori K, Arii H, Sato A, Aoki K. Who are more insulin resistant, people with IFG or people with IGT? Diabetologia. 2004;47(4):758–9.

    Article  CAS  PubMed  Google Scholar 

  21. Snehalatha C, Ramachandran A, Sivasankari S, Satyavani K, Vijay V. Insulin secretion and action show differences in impaired fasting glucose and in impaired glucose tolerance in Asian Indians. Diabetes Metab Res Rev. 2003;19(4):329–32.

    Article  CAS  PubMed  Google Scholar 

  22. Prentki M, Nolan CJ. Islet beta cell failure in type 2 diabetes. J Clin Invest. 2006;116(7):1802–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Meigs JB, Rutter MK, Sullivan LM, Fox CS, D’Agostino RB Sr, Wilson PW. Impact of insulin resistance on risk of type 2 diabetes and cardiovascular disease in people with metabolic syndrome. Diabetes Care. 2007;30(5):1219–25.

    Article  CAS  PubMed  Google Scholar 

  24. Gupta AK, Prieto-Merino D, Dahlöf B, Sever PS, Poulter NR. Metabolic syndrome, impaired fasting glucose and obesity, as predictors of incident diabetes in 14 120 hypertensive patients of ASCOT-BPLA: comparison of their relative predictability using a novel approach. Diabet Med. 2011;28(8):941–7.

    Article  CAS  PubMed  Google Scholar 

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Correspondence to Sudha Vidyasagar.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants included in the study.

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Khan, Z.A.W., Vidyasagar, S., Varma, D.M. et al. The clinical and biochemical profiles of patients with IFG. Int J Diabetes Dev Ctries 39, 94–99 (2019). https://doi.org/10.1007/s13410-018-0650-1

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  • DOI: https://doi.org/10.1007/s13410-018-0650-1

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