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Erschienen in: Wiener klinische Wochenschrift 3-4/2024

09.10.2023 | original article

Insulin resistance is a cardiovascular risk factor in hypertensive adults without type 2 diabetes mellitus

verfasst von: Rafael Garcia-Carretero, Oscar Vazquez-Gomez, Ruth Gil-Prieto, Angel Gil-de-Miguel

Erschienen in: Wiener klinische Wochenschrift | Ausgabe 3-4/2024

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Summary

Background

Metabolic syndrome refers to the association among several cardiovascular risk factors: obesity, dyslipidemia, hyperglycemia, and hypertension. It is associated with increased cardiovascular risk and the development of type 2 diabetes mellitus. Insulin resistance is the underlying mechanism of metabolic syndrome, although its role in increased cardiovascular risk has not been directly identified.

Objective

We investigated the association between insulin resistance and increased cardiovascular risk in hypertensive adults without diabetes mellitus.

Design and participants

We enrolled participants without diabetes from an outpatient setting in a retrospective, longitudinal study. Several demographic, clinical, and laboratory parameters were recorded during the observation period. Plasma insulin and homeostatic model assessment for insulin resistance (HOMA-IR) were used to determine insulin resistance and four cardiovascular events (acute coronary disease, acute cerebrovascular disease, incident heart failure, and cardiovascular mortality) were combined into a single outcome. Logistic regression and Cox proportional hazards models were fitted to evaluate the association between covariates and outcomes.

Results

We included 1899 hypertensive adults without diabetes with an average age of 53 years (51.3% women, 23% had prediabetes, and 64.2% had metabolic syndrome). In a logistic regression analysis, male sex (odds ratio, OR = 1.66) having high levels of low-density lipoprotein (LDL, OR = 1.01), kidney function (OR = 0.97), and HOMA-IR (OR = 1.06) were associated with the incidence of cardiovascular events; however, in a survival multivariate analysis, only HOMA-IR (hazard ratio, HR 1.4, 95% confidence interval, CI: 1.05–1.87, p = 0.02) and body mass index (HR 1.05, 95% CI: 1.02–1.08, p = 0.002) were considered independent prognostic variables for the development of incident cardiovascular events.

Conclusion

Insulin resistance and obesity are useful for assessing cardiovascular risk in hypertensive people without diabetes but with preserved kidney function. This work demonstrates the predictive value of the measurement of insulin, and therefore of insulin resistance, in an outpatient setting and attending to high-risk patients.
Literatur
1.
Zurück zum Zitat James DE, Stöckli J, Birnbaum MJ. The aetiology and molecular landscape of insulin resistance. Nat Rev Mol Cell Biol. 2021;22(11):751–71. Nov.CrossRefPubMed James DE, Stöckli J, Birnbaum MJ. The aetiology and molecular landscape of insulin resistance. Nat Rev Mol Cell Biol. 2021;22(11):751–71. Nov.CrossRefPubMed
2.
Zurück zum Zitat Laakso M, Kuusisto J. Insulin resistance and hyperglycaemia in cardiovascular disease development. Nat Rev Endocrinol. 2014;10(5):293–302. May.CrossRefPubMed Laakso M, Kuusisto J. Insulin resistance and hyperglycaemia in cardiovascular disease development. Nat Rev Endocrinol. 2014;10(5):293–302. May.CrossRefPubMed
3.
Zurück zum Zitat Fonseca VA. Defining and characterizing the progression of type 2 diabetes. Diabetes care. 2009 Nov;32 Suppl 2:S151–6. Fonseca VA. Defining and characterizing the progression of type 2 diabetes. Diabetes care. 2009 Nov;32 Suppl 2:S151–6.
4.
Zurück zum Zitat Weyer C, Tataranni PA, Bogardus C, Pratley RE. Insulin Resistance and Insulin Secretory Dysfunction Are Independent Predictors of Worsening of Glucose Tolerance During Each Stage of Type 2 Diabetes Development. Diabetes Care. 2001;24(1):89–94.CrossRefPubMed Weyer C, Tataranni PA, Bogardus C, Pratley RE. Insulin Resistance and Insulin Secretory Dysfunction Are Independent Predictors of Worsening of Glucose Tolerance During Each Stage of Type 2 Diabetes Development. Diabetes Care. 2001;24(1):89–94.CrossRefPubMed
5.
Zurück zum Zitat UKPDS. U.K. Prospective Diabetes Study 16: Overview of 6 Years’ Therapy of Type II Diabetes: A Progressive Disease. Diabetes. 1995;44(11):1249–58.CrossRef UKPDS. U.K. Prospective Diabetes Study 16: Overview of 6 Years’ Therapy of Type II Diabetes: A Progressive Disease. Diabetes. 1995;44(11):1249–58.CrossRef
6.
Zurück zum Zitat Li M, Chi X, Wang Y, Setrerrahmane S, Xie W, Xu H. Trends in insulin resistance: insights into mechanisms and therapeutic strategy. Sig Transduct Target Ther. 2022;6;7(1):1–25. Jul. Li M, Chi X, Wang Y, Setrerrahmane S, Xie W, Xu H. Trends in insulin resistance: insights into mechanisms and therapeutic strategy. Sig Transduct Target Ther. 2022;6;7(1):1–25. Jul.
7.
Zurück zum Zitat King GL, Park K, Li Q. Selective Insulin Resistance and the Development of Cardiovascular Diseases in Diabetes: The 2015 Edwin Bierman Award Lecture. Diabetes. 2016;65(6):1462–71. Jun.CrossRefPubMedPubMedCentral King GL, Park K, Li Q. Selective Insulin Resistance and the Development of Cardiovascular Diseases in Diabetes: The 2015 Edwin Bierman Award Lecture. Diabetes. 2016;65(6):1462–71. Jun.CrossRefPubMedPubMedCentral
8.
Zurück zum Zitat Ormazabal V, Nair S, Elfeky O, Aguayo C, Salomon C, Zuñiga FA. Association between insulin resistance and the development of cardiovascular disease. Cardiovasc Diabetol. 2018;31;17(1):122. Aug.CrossRef Ormazabal V, Nair S, Elfeky O, Aguayo C, Salomon C, Zuñiga FA. Association between insulin resistance and the development of cardiovascular disease. Cardiovasc Diabetol. 2018;31;17(1):122. Aug.CrossRef
9.
Zurück zum Zitat Reaven G. Insulin resistance and coronary heart disease in nondiabetic individuals. Arterioscler Thromb Vasc Biol. 2012;32(8):1754–9. Aug.CrossRefPubMed Reaven G. Insulin resistance and coronary heart disease in nondiabetic individuals. Arterioscler Thromb Vasc Biol. 2012;32(8):1754–9. Aug.CrossRefPubMed
10.
Zurück zum Zitat Zethelius B, Lithell H, Hales CN, Berne C. Insulin sensitivity, proinsulin and insulin as predictors of coronary heart disease. A population-based 10-year, follow-up study in 70-year old men using the euglycaemic insulin clamp. Diabetologia. 2005;48(5):862–7. May.CrossRefPubMed Zethelius B, Lithell H, Hales CN, Berne C. Insulin sensitivity, proinsulin and insulin as predictors of coronary heart disease. A population-based 10-year, follow-up study in 70-year old men using the euglycaemic insulin clamp. Diabetologia. 2005;48(5):862–7. May.CrossRefPubMed
11.
Zurück zum Zitat Wang T, Li M, Zeng T, Hu R, Xu Y, Xu M, et al. Association Between Insulin Resistance and Cardiovascular Disease Risk Varies According to Glucose Tolerance Status: A Nationwide Prospective Cohort Study. Diabetes Care. 2022;45(8):1863–72. Aug.CrossRefPubMedPubMedCentral Wang T, Li M, Zeng T, Hu R, Xu Y, Xu M, et al. Association Between Insulin Resistance and Cardiovascular Disease Risk Varies According to Glucose Tolerance Status: A Nationwide Prospective Cohort Study. Diabetes Care. 2022;45(8):1863–72. Aug.CrossRefPubMedPubMedCentral
12.
Zurück zum Zitat Ellulu MS, Patimah I, Khaza’ai H, Rahmat A, Abed Y. Obesity and inflammation: the linking mechanism and the complications. Arch Med Sci. 2017;13(4):851–63. Jun.CrossRefPubMed Ellulu MS, Patimah I, Khaza’ai H, Rahmat A, Abed Y. Obesity and inflammation: the linking mechanism and the complications. Arch Med Sci. 2017;13(4):851–63. Jun.CrossRefPubMed
13.
Zurück zum Zitat Scarpellini E, Tack J. Obesity and Metabolic Syndrome: An Inflammatory. Cond Ddi. 2012;30(2):148–53. Scarpellini E, Tack J. Obesity and Metabolic Syndrome: An Inflammatory. Cond Ddi. 2012;30(2):148–53.
14.
Zurück zum Zitat Garcia-Carretero R, Vigil-Medina L, Barquero-Perez O. The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus. Metabolic Syndrome and Related Disorders [Internet]. 2021 Feb 16; Available from: https://doi.org/10.1089/met.2020.0139 Garcia-Carretero R, Vigil-Medina L, Barquero-Perez O. The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus. Metabolic Syndrome and Related Disorders [Internet]. 2021 Feb 16; Available from: https://​doi.​org/​10.​1089/​met.​2020.​0139
15.
Zurück zum Zitat Sarwar N, Aspelund T, Eiriksdottir G, Gobin R, Seshasai SRK, Forouhi NG, et al. Markers of dysglycaemia and risk of coronary heart disease in people without diabetes: Reykjavik prospective study and systematic review. Plos Med. 2010;7(5):e1000278. May.CrossRefPubMedPubMedCentral Sarwar N, Aspelund T, Eiriksdottir G, Gobin R, Seshasai SRK, Forouhi NG, et al. Markers of dysglycaemia and risk of coronary heart disease in people without diabetes: Reykjavik prospective study and systematic review. Plos Med. 2010;7(5):e1000278. May.CrossRefPubMedPubMedCentral
16.
Zurück zum Zitat Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;14;444(7121):840–6. Dec.CrossRef Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;14;444(7121):840–6. Dec.CrossRef
17.
Zurück zum Zitat Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–12.CrossRefPubMedPubMedCentral Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009;150(9):604–12.CrossRefPubMedPubMedCentral
18.
Zurück zum Zitat Unger T, Borghi C, Charchar F, Khan NA, Poulter NR, Prabhakaran D, et al. 2020 International Society of Hypertension Global Hypertension Practice Guidelines. Hypertension. 2020;75(6):1334–57. Jun.CrossRefPubMed Unger T, Borghi C, Charchar F, Khan NA, Poulter NR, Prabhakaran D, et al. 2020 International Society of Hypertension Global Hypertension Practice Guidelines. Hypertension. 2020;75(6):1334–57. Jun.CrossRefPubMed
19.
Zurück zum Zitat Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2018. Diabetes Care. 2018 Jan 1;41(Supplement 1):S13 LP–S27. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes—2018. Diabetes Care. 2018 Jan 1;41(Supplement 1):S13 LP–S27.
20.
Zurück zum Zitat Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation and treatment of high blood cholesterol in adults (Adult Treatment Panel III), JAMA. 2001 May 16;285(19):2486–97. Executive summary of the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation and treatment of high blood cholesterol in adults (Adult Treatment Panel III), JAMA. 2001 May 16;285(19):2486–97.
21.
Zurück zum Zitat R Core Team. A Language and Environment for Statistical Computing [Internet]. Vienna, Austria. Available from: https://www.r-project.org: R Foundation for Statistical Computing; 2020. R Core Team. A Language and Environment for Statistical Computing [Internet]. Vienna, Austria. Available from: https://​www.​r-project.​org: R Foundation for Statistical Computing; 2020.
22.
Zurück zum Zitat Bradburn MJ, Clark TG, Love SB, Altman DG. Survival analysis part II: multivariate data analysis—an introduction to concepts and methods. Br J Cancer. 2003;4;89(3):431–6. Aug.CrossRef Bradburn MJ, Clark TG, Love SB, Altman DG. Survival analysis part II: multivariate data analysis—an introduction to concepts and methods. Br J Cancer. 2003;4;89(3):431–6. Aug.CrossRef
23.
Zurück zum Zitat Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis part I: basic concepts and first analyses. Br J Cancer. 2003;89(2):232–8. Jul.CrossRefPubMedPubMedCentral Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis part I: basic concepts and first analyses. Br J Cancer. 2003;89(2):232–8. Jul.CrossRefPubMedPubMedCentral
24.
Zurück zum Zitat Allen M, Poggiali D, Whitaker K, Marshall TR, Kievit RA. Raincloud plots: a multi-platform tool for robust data visualization. Wellcome Open Res. 2019;1;4:63–63. Apr.CrossRef Allen M, Poggiali D, Whitaker K, Marshall TR, Kievit RA. Raincloud plots: a multi-platform tool for robust data visualization. Wellcome Open Res. 2019;1;4:63–63. Apr.CrossRef
25.
Zurück zum Zitat Lakka HM, Salonen JT, Tuomilehto J, Kaplan GA, Lakka TA. Obesity and weight gain are associated with increased incidence of hyperinsulinemia in non-diabetic men. Horm Metab Res. 2002;34(9):492–8. Sep.CrossRefPubMed Lakka HM, Salonen JT, Tuomilehto J, Kaplan GA, Lakka TA. Obesity and weight gain are associated with increased incidence of hyperinsulinemia in non-diabetic men. Horm Metab Res. 2002;34(9):492–8. Sep.CrossRefPubMed
27.
Zurück zum Zitat Ye J. Role of insulin in the pathogenesis of free fatty acid-induced insulin resistance in skeletal muscle. Endocr Metab Immune Disord Drug Targets. 2007;7(1):65–74. Mar.MathSciNetCrossRefPubMed Ye J. Role of insulin in the pathogenesis of free fatty acid-induced insulin resistance in skeletal muscle. Endocr Metab Immune Disord Drug Targets. 2007;7(1):65–74. Mar.MathSciNetCrossRefPubMed
28.
Zurück zum Zitat Ye J, McGuinness OP. Inflammation during obesity is not all bad: evidence from animal and human studies. Am J Physiol Endocrinol Metab. 2013;304(5):E466–77. Mar.CrossRefPubMed Ye J, McGuinness OP. Inflammation during obesity is not all bad: evidence from animal and human studies. Am J Physiol Endocrinol Metab. 2013;304(5):E466–77. Mar.CrossRefPubMed
29.
Zurück zum Zitat Lau DCW, Dhillon B, Yan H, Szmitko PE, Adipokines VS. molecular links between obesity and atheroslcerosis. Am J Physiol Heart Circ Physiol. 2005;288(5):H2031–41. May.CrossRefPubMed Lau DCW, Dhillon B, Yan H, Szmitko PE, Adipokines VS. molecular links between obesity and atheroslcerosis. Am J Physiol Heart Circ Physiol. 2005;288(5):H2031–41. May.CrossRefPubMed
30.
Zurück zum Zitat Cinti S, Mitchell G, Barbatelli G, Murano I, Ceresi E, Faloia E, et al. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J Lipid Res. 2005;46(11):2347–55. Nov.CrossRefPubMed Cinti S, Mitchell G, Barbatelli G, Murano I, Ceresi E, Faloia E, et al. Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans. J Lipid Res. 2005;46(11):2347–55. Nov.CrossRefPubMed
31.
Zurück zum Zitat Halberg N, Wernstedt-Asterholm I, Scherer PE. The adipocyte as an endocrine cell. Endocrinology and metabolism clinics of North America. 2008 Sep;37(3):753–68, x–xi. Halberg N, Wernstedt-Asterholm I, Scherer PE. The adipocyte as an endocrine cell. Endocrinology and metabolism clinics of North America. 2008 Sep;37(3):753–68, x–xi.
32.
Zurück zum Zitat Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735–52. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation. 2005;112(17):2735–52.
33.
Zurück zum Zitat Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the Metabolic Syndrome A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International A. Circulation. 2009;120(16):1640–5. Alberti K, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the Metabolic Syndrome A Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International A. Circulation. 2009;120(16):1640–5.
34.
Zurück zum Zitat Haidara M, Mikhailidis DP, Yassin HZ, Dobutovic B, Smiljanic KT, Soskic S, et al. Evaluation of the possible contribution of antioxidants administration in metabolic syndrome. Curr Pharm Des. 2011;17(33):3699–712. Nov.CrossRefPubMed Haidara M, Mikhailidis DP, Yassin HZ, Dobutovic B, Smiljanic KT, Soskic S, et al. Evaluation of the possible contribution of antioxidants administration in metabolic syndrome. Curr Pharm Des. 2011;17(33):3699–712. Nov.CrossRefPubMed
35.
Zurück zum Zitat Gluvic Z, Zaric B, Resanovic I, Obradovic M, Mitrovic A, Radak D, et al. Link between Metabolic Syndrome and Insulin Resistance. Curr Vasc Pharmacol. 2017;15(1):30–9.CrossRefPubMed Gluvic Z, Zaric B, Resanovic I, Obradovic M, Mitrovic A, Radak D, et al. Link between Metabolic Syndrome and Insulin Resistance. Curr Vasc Pharmacol. 2017;15(1):30–9.CrossRefPubMed
36.
Zurück zum Zitat Stokić E, Kupusinac A, Tomić-Naglić D, Zavišić BK, Mitrović M, Smiljenić D, et al. Obesity and vitamin D deficiency: trends to promote a more proatherogenic cardiometabolic risk profile. Angiology. 2015;66(3):237–43. Mar.CrossRefPubMed Stokić E, Kupusinac A, Tomić-Naglić D, Zavišić BK, Mitrović M, Smiljenić D, et al. Obesity and vitamin D deficiency: trends to promote a more proatherogenic cardiometabolic risk profile. Angiology. 2015;66(3):237–43. Mar.CrossRefPubMed
37.
Zurück zum Zitat Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, et al. C‑reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet. 2010;9;375(9709):132–40. Jan. Emerging Risk Factors Collaboration, Kaptoge S, Di Angelantonio E, Lowe G, Pepys MB, Thompson SG, et al. C‑reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet. 2010;9;375(9709):132–40. Jan.
38.
Zurück zum Zitat Ridker PM. From C‑Reactive Protein to Interleukin‑6 to Interleukin-1: Moving Upstream To Identify Novel Targets for Atheroprotection. Circ Res. 2016;8;118(1):145–56. Jan.CrossRef Ridker PM. From C‑Reactive Protein to Interleukin‑6 to Interleukin-1: Moving Upstream To Identify Novel Targets for Atheroprotection. Circ Res. 2016;8;118(1):145–56. Jan.CrossRef
39.
Zurück zum Zitat DeFronzo RA. Insulin resistance, lipotoxicity, type 2 diabetes and atherosclerosis: the missing links. The Claude Bernard Lecture 2009. Diabetologia. 2010;53(7):1270–87. Jul.CrossRefPubMedPubMedCentral DeFronzo RA. Insulin resistance, lipotoxicity, type 2 diabetes and atherosclerosis: the missing links. The Claude Bernard Lecture 2009. Diabetologia. 2010;53(7):1270–87. Jul.CrossRefPubMedPubMedCentral
40.
Zurück zum Zitat Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and β‑cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;1;28(7):412–9. Jul.CrossRef Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and β‑cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;1;28(7):412–9. Jul.CrossRef
41.
Zurück zum Zitat Stern SE, Williams K, Ferrannini E, DeFronzo RA, Bogardus C, Stern MP. Identification of individuals with insulin resistance using routine clinical measurements. Diabetes. 2005;54(2):333–9. Feb.CrossRefPubMed Stern SE, Williams K, Ferrannini E, DeFronzo RA, Bogardus C, Stern MP. Identification of individuals with insulin resistance using routine clinical measurements. Diabetes. 2005;54(2):333–9. Feb.CrossRefPubMed
42.
Zurück zum Zitat Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord. 2013;16;13:47. Oct.CrossRef Gayoso-Diz P, Otero-González A, Rodriguez-Alvarez MX, Gude F, García F, De Francisco A, et al. Insulin resistance (HOMA-IR) cut-off values and the metabolic syndrome in a general adult population: effect of gender and age: EPIRCE cross-sectional study. BMC Endocr Disord. 2013;16;13:47. Oct.CrossRef
43.
Zurück zum Zitat Lamounier-Zepter V, Ehrhart-Bornstein M, Bornstein SR. Insulin resistance in hypertension and cardiovascular disease. Best Pract Res Clin Endocrinol Metab. 2006;20(3):355–67. Sep.CrossRefPubMed Lamounier-Zepter V, Ehrhart-Bornstein M, Bornstein SR. Insulin resistance in hypertension and cardiovascular disease. Best Pract Res Clin Endocrinol Metab. 2006;20(3):355–67. Sep.CrossRefPubMed
44.
Zurück zum Zitat Eddy D, Schlessinger L, Kahn R, Peskin B, Schiebinger R. Relationship of insulin resistance and related metabolic variables to coronary artery disease: a mathematical analysis. Diabetes Care. 2009;32(2):361–6. Feb.CrossRefPubMedPubMedCentral Eddy D, Schlessinger L, Kahn R, Peskin B, Schiebinger R. Relationship of insulin resistance and related metabolic variables to coronary artery disease: a mathematical analysis. Diabetes Care. 2009;32(2):361–6. Feb.CrossRefPubMedPubMedCentral
Metadaten
Titel
Insulin resistance is a cardiovascular risk factor in hypertensive adults without type 2 diabetes mellitus
verfasst von
Rafael Garcia-Carretero
Oscar Vazquez-Gomez
Ruth Gil-Prieto
Angel Gil-de-Miguel
Publikationsdatum
09.10.2023
Verlag
Springer Vienna
Erschienen in
Wiener klinische Wochenschrift / Ausgabe 3-4/2024
Print ISSN: 0043-5325
Elektronische ISSN: 1613-7671
DOI
https://doi.org/10.1007/s00508-023-02278-1

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