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Can clinical factors estimate insulin resistance in type 1 diabetes?
Open accessAbstract
An insulin resistance syndrome (IRS) score was developed based on clinical risk factors in adults with childhood-onset type 1 diabetes in the Epidemiology of Diabetes Complications (EDC) Study and was validated using euglycemic-hyperinsulinemic clamp studies. Hypertension, waist-to-hip ratio (WHR), triglyceride and HDL cholesterol levels, family history of type 2 diabetes, and glycemic control were risk factors used to define the score. A score of 1 (lowest likelihood IRS) to 3 (highest likelihood IRS) was assigned for each risk factor. Eligible subjects (n = 24) were recruited from the EDC cohort based on tertile of IRS score. Subjects received an overnight insulin infusion to normalize glucose levels, then underwent a 3-h euglycemic-hyperinsulinemic (60 mU x m(-2) x min(-1)) clamp. Glucose disposal rate (GDR) was determined during the last 30 min of the clamp. The GDR differed significantly by IRS group (9.65 +/- 2.99, 8.02 +/- 1.39, and 5.68 +/- 2.16 mg x kg(-1) x min(-1), P < 0.01). The GDR was inversely correlated with the IRS score (r = -0.64, P < 0.01). Using linear regression, the combination of risk factors that yielded the highest adjusted r2 value (0.57, P < 0.001) were WHR, hypertension, and HbA1. This study found that clinical risk factors can be used to identify subjects with type 1 diabetes who are insulin resistant, and it provides validation of a score based on clinical factors to determine the extent of insulin resistance in type 1 diabetes. This score will be applied to the entire EDC population in future studies to determine the effect of insulin resistance on complications.
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“In men with type 1 diabetes, cFT levels were also independently associated with eGDR, a marker of insulin sensitivity in individuals with type 1 diabetes (24), after adjusting for age (P ϭ 0.04).”
From Low testosterone levels are common and associated with insulin resistance in men with diabetes (2008) · cites this paper as [24]
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Type 1 Diabetes Mellitus and Exercise
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Bulum, T., Kolarić, B., & Duvnjak, L. S. (2013) · International Journal of Diabetes in Developing Countries · doi:10.1007/s13410-013-0176-5 · Cited by 4
Claesson, T.-B., Jukka Putaala, A., Shams, S., Salli, E., Gordin, D., Liebkind, R., Forsblom, C. M., Summanen, P. A., Tatlisumak, T., Groop, P., et al. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00027 · Cited by 4
Zawada, A. E., Naskręt, D., Niedźwiecki, P., Grzymislawski, M. B., Zozulińska‐Ziółkiewicz, D., & Dobrowolska, A. (2020) · Advances in Clinical and Experimental Medicine · doi:10.17219/acem/126050 · Cited by 4
Stagi, S., Papacciuoli, V., Ciofi, D., Piccini, B., Farello, G., Toni, S., Ferrari, M., & Chiarelli, F. (2021) · Nutrients · doi:10.3390/nu13103517 · Cited by 6
Kamiński, M., Kulecki, M., Lachowski, P., Kasprzak, D., Kulczycka, A., Kozłowska, M., Klause, D., Uruska, A. A., Michalski, M., & Zozulińska‐Ziółkiewicz, D. (2022) · International Journal of Angiology · doi:10.1055/s-0041-1735209 · Cited by 5
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Characteristics and outcomes of patients with type 1 diabetes admitted with acute coronary syndromes
Nejatian, M. M., Lan, N. S. R., Yeap, B. B., Dwivedi, G., Fegan, P. G., & Ihdayhid, A. R. (2022) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2022.110093 · Cited by 4
Pepa, G. D., Lupoli, R., Masulli, M., Boccia, R., Angelis, R. D., Gianfrancesco, S., Rainone, C., Rivellese, A. A., Annuzzi, G., & Bozzetto, L. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110816 · Cited by 4
Guimarães, J. P. T., Menikdiwela, K. R., Ramalho, T. R. D. O., Queiroz, L. A. D., Kalupahana, N. S., Jancar, S., Ramalingam, L., Martins, J. O., & Moustaïd‐Moussa, N. (2022) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2022.166477 · Cited by 4
Insulin Resistance among Adults with Type 1 Diabetes Mellitus at the Philippine General Hospital
Barrera, J. (2013) · Journal of Diabetes & Metabolism · doi:10.4172/2155-6156.1000315 · Cited by 5
Physical activity and hippocampal volume in middle-aged patients with type 1 diabetes
Nunley, K. A., Leckie, R. L., Orchard, T. J., Costacou, T., Aizenstein, H. J., Jennings, J. R., Erickson, K. I., & Rosano, C. (2017) · Neurology · doi:10.1212/wnl.0000000000003805 · Cited by 5
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Metadata
- Authors
- Williams, K. V., Erbey, J. R., Becker, D., Arslanian, S., & Orchard, T. J.
- Affiliations
- University of Pittsburgh (US)
- Venue
- Diabetes
- Publisher
- American Diabetes Association
- Published
- 2000-04-01
- Volume
- 49
- Issue
- 4
- Pages
- 626-632
- ISSN
- 0012-1797 (ISSN-L)
- 1939-327X
- OpenAlex
- W2143570364
- Cited by
- 640
- References
- 11
- Citations by year
- 2026: 66 · 2025: 94 · 2024: 47 · 2023: 42 · 2022: 38 · 2021: 39 · 2020: 27 · 2019: 15 · 2018: 26 · 2017: 16 · 2016: 17 · 2015: 23 · 2014: 22 · 2013: 25 · 2012: 16
- FWCI
- 4.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Diabetes and Digestive and Kidney Diseases (2 T32 DK07052-22, T32DK007052)
- National Center for Research Resources (5M01-RRR00084)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Keywords
- insulin resistance, type 1 diabetes, childhood-onset diabetes, clinical risk factors, waist-to-hip ratio, hypertension, glycemic control, HbA1c, glucose disposal rate, hyperinsulinemic-euglycemic clamp
- MeSH terms
- Adult, Blood Glucose, Blood Pressure, Body Constitution, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Female, Glycated Hemoglobin, Humans, Insulin, Insulin Resistance, Cholesterol, HDL, Male, Middle Aged, Risk Factors, Triglycerides, Glucose Clamp Technique, Logistic Models
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