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RSSDI endorses the IDF Position Statement on 1 h post load plasma glucose for diagnosis of intermediate hyperglycemia and type 2 diabetes

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Abstract

The Oral Glucose Tolerance Test (OGTT) remains a gold standard for diagnosis of diabetes and prediabetes all over the world and also in India. The original OGTT was a five sample test which included fasting, 30, 60, 90, and 120 min. Later, the test was modified in the US to two sample test 0 and 120 min, i.e., fasting and 2 h after 75 g glucose and this has been in practice all over the world. Traditional diabetologists continue to measure some of the intermediate samples, particularly the 60 min or 1 h value which identifies individuals even before the fasting or 2 h value becomes abnormal. Thus, even before the stage of prediabetes when one has a normal fasting and 2 h value, a raised 1 h value above 155 mg/dl has been shown to predict who will progress to diabetes. A group of 22 international experts recently got together and the IDF Position Statement on the 1 h value was published which shows why the 1 h value in the OGTT should be reintroduced in the routine lab testing of OGTT. This article is an endorsement of the IDF Position Statement on the 1 h value. Introducing the 1 h value in the OGTT is particularly relevant to India which has one of the fastest conversions of prediabetes to diabetes and also a very rapid loss of beta cell function. Identifying early stages of intermediate hyperglycemia can help to prevent diabetes and also reverse the condition.

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References

  1. Conn JW. Interpretation of the glucose tolerance test. The necessity of a standard preparatory diet. Am J Med Sci. 1940;199:555–64. https://doi.org/10.1097/00000441-194004000-00014.

    Article  CAS  Google Scholar 

  2. Jagannathan R, Neves JS, Dorcely B, et al. The Oral Glucose Tolerance Test: 100 years later. Diabetes Metab Syndr Obes. 2020;13:3787–805. https://doi.org/10.2147/DMSO.S246062.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. National Diabetes Data Group. Classification and diagnosis of diabetes mellitus and other categories of glucose intolerance. Diabetes. 1979;28:1039–57. https://doi.org/10.2337/diab.28.12.1039.

    Article  Google Scholar 

  4. Makkar BM, Vasanth Kumar CH, Saboo B, Agarwal S, On behalf of RSSDI 2022 Consensus Group. RSSDI clinical practice recommendations for the management of type 2 diabetes mellitus 2022. Int J Diabetes Dev Ctries. 2022;42(Suppl 1):1–143. https://doi.org/10.1007/s13410-022-01129-5.

    Article  Google Scholar 

  5. Abdul-Ghani MA, Abdul-Ghani T, Stern MPK, et al. Two-step approach for the prediction of future type 2 diabetes risk. Diabetes Care. 2011;34:2108–12. https://doi.org/10.2337/dc10-2201.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Alyass A, Almgren P, Akerlund M, et al. Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts. Diabetologia. 2015;58:87–97. https://doi.org/10.1007/s00125-014-3390-x.

    Article  CAS  PubMed  Google Scholar 

  7. Priya M, Anjana RM, Chiwanga FS, Gokulakrishnan K, Deepa M, Mohan V. 1-hour venous plasma glucose and incident prediabetes and diabetes in Asian Indians. Diabetes Technol Ther. 2013;15:497–502. https://doi.org/10.1089/dia.2013.0025.

    Article  CAS  PubMed  Google Scholar 

  8. Pramodkumar T, Priya M, Jebarani S, Anjana R, Mohan V, Pradeepa R. Metabolic profile of normal glucose-tolerant subjects with elevated 1-h plasma glucose values. Indian J Endocrinol Metab. 2016;20:612–8. https://doi.org/10.4103/2230-8210.19053.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Sai Prasanna N, Amutha A, Pramodkumar TA, et al. The 1h post glucose value best predicts future dysglycemia among normal glucose tolerance subjects. J Diabetes Complications. 2017;31:1592–6. https://doi.org/10.1016/j.jdiacomp.2017.07.017.

    Article  PubMed  Google Scholar 

  10. Kumpatla S, Parveen R, Stanson S, Viswanathan V. Elevated one hour with normal fasting and 2 h plasma glucose helps to identify those at risk for development of type 2 diabetes-11 years observational study from south India. Diabetes Metab Syndr. 2019;13:2733–7. https://doi.org/10.1016/j.dsx.2019.06.029.

    Article  PubMed  Google Scholar 

  11. Bergman M, Buysschaert M, Ceriello A, et al. Current diagnostic criteria identify risk for type 2 diabetes too late. Lancet Diabetes Endocrinol. 2023;11:224–6. https://doi.org/10.1016/S2213-8587(23)00039-6.

    Article  CAS  PubMed  Google Scholar 

  12. Bergman M, Manco M, Satman I, et al. International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes. Diabetes Res Clin Pract. 2024; Published : March 06, 2024. https://doi.org/10.1016/j.diabres.2024.111589.

  13. DeFronzo RA, Abdul-Ghani MA. Preservation of β-cell function: the key to diabetes prevention. J Clin Endocrinol Metab. 2011;96:2354–66. https://doi.org/10.1210/jc.2011-0246.

    Article  CAS  PubMed  Google Scholar 

  14. Staimez LR, Weber MB, Ranjani H, et al. Evidence of reduced β-cell function in Asian Indians with mild dysglycemia. Diabetes Care. 2013;36:2772–8. https://doi.org/10.2337/dc12-2290.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Mohan V, Deepa R, Deepa M, Somannavar S, Datta M. A simplified Indian diabetes risk score for screening for undiagnosed diabetic subjects. J Assoc Physicians India. 2005;53:759–63.

    CAS  PubMed  Google Scholar 

  16. Mohan V, Sandeep S, Deepa M, Gokulakrishnan K, Datta M, Deepa R. A diabetes risk score helps identify metabolic syndrome and cardiovascular risk in Indians-the Chennai Urban Rural Epidemiology Study (CURES-38). Diabetes Obes Metab. 2007;9:337–43. https://doi.org/10.1111/j.1463-1326.2006.00612.x.

    Article  CAS  PubMed  Google Scholar 

  17. Mohan V, Anbalagan VP. Expanding role of the madras diabetes research foundation - indian diabetes risk score in clinical practice. Indian J Endocrinol Metab. 2013;17:31–6. https://doi.org/10.4103/2230-8210.107825.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Mohan V, Goldhaber-Fiebert JD, Radha V, Gokulakrishnan K. Screening with OGTT alone or in combination with the Indian diabetes risk score or genotyping of TCF7L2 to detect undiagnosed type 2 diabetes in Asian Indians. Indian J Med Res. 2011;133:294–9.

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Bala S, Pandve H, Kamala K, Dhanalakshmi A, Sarikonda H. Performance of Indian diabetic risk score as a screening tool of diabetes among women of industrial urban area. J Family Med Prim Care. 2019;8:3569–73. https://doi.org/10.4103/jfmpc.jfmpc_799_19.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Singh MM, Mangla V, Pangtey R, Garg S. Risk assessment of diabetes using the Indian Diabetes Risk Score: a study on young medical students from Northern India. Indian J Endocrinol Metab. 2019;23:86–90. https://doi.org/10.4103/ijem.IJEM_623_18.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Rooney MR, Fang M, Ogurtsova K, et al. Global prevalence of prediabetes. Diabetes Care. 2023;46:1388–94. https://doi.org/10.2337/dc22-2376.

    Article  CAS  PubMed  Google Scholar 

  22. Mohan V, Unnikrishnan R, Anjana RM. Comment on Rooney et al. Global prevalence of prediabetes. Diabetes Care 2023;46:1388-1394. Diabetes Care. 2023;46:e220. https://doi.org/10.2337/dc23-1606.

    Article  PubMed  Google Scholar 

  23. Anjana RM, Unnikrishnan R, Deepa M, ICMR-INDIAB Collaborative Study Group, et al. Metabolic non-communicable disease health report of India: the ICMR-INDIAB national cross-sectional study (ICMR-INDIAB-17). Lancet Diabetes Endocrinol. 2023;11:474–89. https://doi.org/10.1016/S2213-8587(23)00119-5.

    Article  PubMed  Google Scholar 

  24. Sattar N, Gill JM. Type 2 diabetes in migrant south Asians: mechanisms, mitigation, and management. Lancet Diabetes Endocrinol. 2015;3:1004–16. https://doi.org/10.1016/S2213-8587(15)00326-5.

    Article  PubMed  Google Scholar 

  25. Anjana RM, Shanthi Rani CS, Deepa M, et al. Incidence of diabetes and prediabetes and predictors of progression among Asian Indians: 10-year follow-up of the Chennai Urban Rural Epidemiology Study (CURES). Diabetes Care. 2015;38:1441–8. https://doi.org/10.2337/dc14-2814.

    Article  PubMed  Google Scholar 

  26. Ahlqvist E, Storm P, Käräjämäki A, et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol. 2018;6:361–9. https://doi.org/10.1016/S2213-8587(18)30051-2.

    Article  PubMed  Google Scholar 

  27. Anjana RM, Baskar V, Nair ATN, et al. Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study. BMJ Open Diabetes Res Care. 2020;8:e001506. https://doi.org/10.1136/bmjdrc-2020-001506.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Das S, Samal KC, Baliarsinha AK, Tripathy BB. Lean (underweight) NIDDM - peculiarities and differences in metabolic and hormonal status - a pilot study. J Assoc Physicians India. 1995;43:339–42.

    CAS  PubMed  Google Scholar 

  29. Mohan V, Vijayaprabha R, Rema M, et al. Clinical profile of lean NIDDM in South India. Diabetes Res Clin Pract. 1997;2:101–8. https://doi.org/10.1016/s0168-8227(97)00088-0.

    Article  Google Scholar 

  30. Unnikrishnan R, Anjana RM, Mohan V. Diabetes in South Asians: is the phenotype different? Diabetes. 2014;63:53–5. https://doi.org/10.2337/db13-1592.

    Article  CAS  PubMed  Google Scholar 

  31. Gujral UP, Pradeepa R, Weber MB, Narayan KM, Mohan V. Type 2 diabetes in South Asians: similarities and differences with white Caucasian and other populations. Ann N Y Acad Sci. 2013;1281:51. https://doi.org/10.1111/j.1749-6632.2012.06838.x.

    Article  PubMed  PubMed Central  Google Scholar 

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Sahay, R., Mohan, V., Agarwal, S. et al. RSSDI endorses the IDF Position Statement on 1 h post load plasma glucose for diagnosis of intermediate hyperglycemia and type 2 diabetes. Int J Diabetes Dev Ctries 44, 216–219 (2024). https://doi.org/10.1007/s13410-024-01345-1

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